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1. Cardiac CT and MRI radiomics: systematic review of the literature and radiomics quality score assessment

Author: Andrea Ponsiglione, Marco De Giorgi, Arnaldo Stanzione, Alberto Cuocolo, Raffaele Ascione, Carmela Nappi, Michele Gambardella, Massimo Imbriaco, Renato Cuocolo, Ponsiglione, Andrea, Stanzione, Arnaldo, Cuocolo, Renato, Ascione, Raffaele, Gambardella, Michele, De Giorgi, Marco, Nappi, Carmela, Cuocolo, Alberto, and Imbriaco, Massimo
Subjects: medicine.medical_specialty, Web of science, Systematic review, Cardiovascular system, Magnetic resonance imaging, Multidetector computed tomography, Multidetector computed tomography, Magnetic resonance imaging, Radiomics, Cardiovascular system, Systematic review, Humans, Radiography, Magnetic Resonance Imaging, Tomography, X-Ray Computed, medicine, Radiology, Nuclear Medicine and imaging, Methodological quality, Tomography, Neuroradiology, medicine.diagnostic_test, business.industry, General Medicine, X-Ray Computed, Quartile, Quality Score, Radiology, business, Medical doctor
Abstract: To systematically review and evaluate the methodological quality of studies using magnetic resonance imaging (MRI) and computed tomography (CT) radiomics for cardiac applications. Multiple medical literature archives (PubMed, Web of Science, and EMBASE) were systematically searched to retrieve original studies focused on cardiac MRI and CT radiomics applications. Two researchers in consensus assessed each investigation using the radiomics quality score (RQS). Subgroup analyses were performed to assess whether the total RQS varied according to study aim, journal quartile, imaging modality, and first author category. From a total of 1961 items, 53 articles were finally included in the analysis. Overall, the studies reached a median total RQS of 7 (IQR, 4–12), corresponding to a percentage score of 19.4% (IQR, 11.1–33.3%). Item scores were particularly low due to lack of prospective design, cost-effectiveness analysis, and open science. Median RQS percentage score was significantly higher in papers where the first author was a medical doctor and in those published on first quartile journals. The overall methodological quality of radiomics studies in cardiac MRI and CT is still lacking. A higher degree of standardization of the radiomics workflow and higher publication standards for studies are required to allow its translation into clinical practice. • RQS has been recently proposed for the overall assessment of the methodological quality of radiomics-based studies. • The 53 included studies on cardiac MRI and CT radiomics applications reached a median total RQS of 7 (IQR, 4–12), corresponding to a percentage of 19.4% (IQR, 11.1–33.3%). • A more standardized methodology in the radiomics workflow is needed, especially in terms of study design, validation, and open science, in order to translate the results to clinical applications.
Published: 2022

2. Risk of appendiceal neoplasm after interval appendectomy for complicated appendicitis: A systematic review and meta-analysis

Author: Ruggero Lionetti, Michele D'Ambra, Francesco Corcione, Umberto Bracale, Roberta Green, Marcello De Luca, Alberto Cuocolo, Roberto Peltrini, Valeria Cantoni, Carolina Bartolini, Peltrini, Roberto, Cantoni, Valeria, Green, Roberta, Lionetti, Ruggero, D'Ambra, Michele, Bartolini, Carolina, De Luca, Marcello, Bracale, Umberto, Cuocolo, Alberto, and Corcione, Francesco
Subjects: medicine.medical_specialty, Adenoma, Complicated appendiciti, Adenocarcinoma, law.invention, Randomized controlled trial, Appendiceal neoplasm, law, Internal medicine, medicine, Appendectomy, Humans, Neoplasm, Appendicular inflammatory ma, Interval appendectomy, Randomized Controlled Trials as Topic, Retrospective Studies, business.industry, Complicated appendicitis, Appendicitis, medicine.disease, Mucinous Neoplasm, Appendiceal Neoplasms, Meta-analysis, Surgery, business
Abstract: Background Non-operative management is often the treatment of choice in cases of complicated appendicitis and routine interval appendectomy is not usually recommended. Actually, recent studies show an alarming number of appendiceal neoplasms following interval appendectomy. The aim of this study is to evaluate the prevalence of appendiceal neoplasms and their histological types after interval appendectomy for complicated appendicitis in adults. Methods A comprehensive literature search of the PubMed, Scopus and Web of Science databases was conducted according to the PRISMA statement. Studies reporting appendiceal neoplasm rates after interval appendectomy and histopathological characteristics were included. The most recent World Health Organization (WHO) classification of malignant tumours was considered. A pooled prevalence analysis for both prevalence and pathology was performed. Results A total of eight studies was included: seven retrospective series and one randomized controlled trial. The pooled prevalence of neoplasms after interval appendectomy was 11% (95% CI 7-15; I2 = 37.5%, p = 0.13). Appendiceal mucinous neoplasms occurred in 43% (95% CI 19-68), adenocarcinoma in 29% (95% CI 6-51), appendiceal neuroendocrine neoplasm in 21% (95% CI 6-36), globet cell carcinoma in 13% (95% CI -2-28), adenoma or serrated lesions in 20% (95% CI -0-41) of cases. Conclusion The risk of appendiceal neoplasm in patients treated with interval appendectomy for complicated appendicitis is 11%; mucinous neoplasm is the most common histopathological type. Further studies should investigate this association in order to clarify the biological pathway and clinical implications.
Published: 2021

3. Ventilation/perfusion SPECT: One more promising resource to fight the medical Hydra

Author: Mario Petretta, Alberto Cuocolo, Cuocolo, Alberto, and Petretta, Mario
Subjects: medicine.medical_specialty, Resource (biology), business.industry, MEDLINE, Medicine, Radiology, Nuclear Medicine and imaging, Lernaean Hydra, Cardiology and Cardiovascular Medicine, business, Intensive care medicine, Ventilation/perfusion ratio
Abstract: NA
Published: 2021

4. Incremental value of 18F-FDG cardiac PET imaging over dobutamine stress echocardiography in predicting myocardial ischemia in patients with suspected coronary artery disease

Author: Letizia Spinelli, Roberta Assante, Mario Petretta, Ciro Mainolfi, Carmela Nappi, Adriana D'Antonio, Pietro Buongiorno, Teresa Mannarino, Emilia Zampella, Wanda Acampa, Alberto Cuocolo, Mariarosaria Panico, Valeria Gaudieri, Zampella, Emilia, Assante, Roberta, Acampa, Wanda, Gaudieri, Valeria, Nappi, Carmela, Mannarino, Teresa, D’Antonio, Adriana, Buongiorno, Pietro, Panico, Mariarosaria, Mainolfi, Ciro Gabriele, Spinelli, Letizia, Petretta, Mario, and Cuocolo, Alberto
Subjects: medicine.medical_specialty, Myocardial ischemia, business.industry, Dobutamine stress echocardiography, Ischemia, medicine.disease, Coronary artery disease, Cardiac PET, Internal medicine, medicine, Cardiology, Radiology, Nuclear Medicine and imaging, In patient, Cardiology and Cardiovascular Medicine, business, Perfusion, Cardiac imaging
Abstract: Background. To assess the incremental value of 18F-fluorodeoxyglucose (FDG) cardiac positron emission tomography (PET) over dobutamine stress echocardiography (DSE) in predicting myocardial ischemia in patients with suspected coronary artery disease (CAD). Methods. Forty-one patients with suspected CAD underwent within 7 days apart rest-stress cardiac PET with 82Rb and DSE followed by cardiac 18F-FDG PET imaging. 18F-FDG images were scored on a 0 (no discernible uptake) to 2 (intense uptake) scale. Logistic regression analysis was performed to identify predictors of stress-induced ischemia. The incremental value of 18F-FDG PET over DSE in detecting ischemia at 82Rb PET cardiac imaging was assessed by the likelihood ratio chi-square and net reclassification index. Results. On 82Rb-PET imaging, myocardial ischemia (ischemic total perfusion defect > 5%) was detected in 20 (49%) patients. Inducible ischemia was found in 22 (54%) patients on DSE (biphasic or worsening response pattern in > 1 segment) and in 21 (51%) patients on 18FFDG PET (uptake score of 2 in ‡ 1 segment). 18F-FDG PET resulted as statistically significant predictor of ischemia on 82Rb-PET. The addition of 18F-FDG PET to DSE increased the likelihood of ischemia on 82Rb-PET (P < .05). 18F-FDG PET was able to reclassify the probability of stress-induced myocardial ischemia on both patient and vessel analyses. Conclusion. 18F-FDG PET performed after dobutamine stress test may provide incremental value to DSE in the evaluation of myocardial ischemia. These results suggest that stress induced myocardial ischemia can be imaged directly using 18F-FDG PET after dobutamine stress test.
Published: 2021

5. Comparing the Prognostic Value of Stress Myocardial Perfusion Imaging by Conventional and Cadmium-Zinc Telluride Single-Photon Emission Computed Tomography through a Machine Learning Approach

Author: Carmela Nappi, Mario Petretta, Leandro Donisi, Teresa Mannarino, Roberta Green, Emilia Zampella, Vincenzo Sannino, Andrea Genova, Alessia Giordano, Alberto Cuocolo, Valeria Cantoni, Giuseppe Cesarelli, Valeria Gaudieri, Wanda Acampa, Giovanni De Simini, Roberta Assante, Adriana D'Antonio, Carlo Ricciardi, Cantoni, Valeria, Green, Roberta, Ricciardi, Carlo, Assante, Roberta, Donisi, Leandro, Zampella, Emilia, Cesarelli, Giuseppe, Nappi, Carmela, Sannino, Vincenzo, Gaudieri, Valeria, Mannarino, Teresa, Genova, Andrea, De Simini, Giovanni, Giordano, Alessia, D'Antonio, Adriana, Acampa, Wanda, Petretta, Mario, Cuocolo, Alberto, and D’Antonio, Adriana
Subjects: Male, Article Subject, Computer applications to medicine. Medical informatics, R858-859.7, Coronary Artery Disease, Single-photon emission computed tomography, Machine learning, computer.software_genre, General Biochemistry, Genetics and Molecular Biology, Machine Learning, Myocardial perfusion imaging, Naive Bayes classifier, medicine, Humans, Myocardial infarction, Aged, Tomography, Emission-Computed, Single-Photon, Univariate analysis, General Immunology and Microbiology, medicine.diagnostic_test, business.industry, Applied Mathematics, Myocardial Perfusion Imaging, Computational Biology, General Medicine, Middle Aged, Prognosis, medicine.disease, Random forest, Support vector machine, Zinc, Modeling and Simulation, Exercise Test, Female, Neural Networks, Computer, Artificial intelligence, Tellurium, business, computer, Algorithms, Emission computed tomography, Research Article, Cadmium
Abstract: We compared the prognostic value of myocardial perfusion imaging (MPI) by conventional- (C-) single-photon emission computed tomography (SPECT) and cadmium-zinc-telluride- (CZT-) SPECT in a cohort of patients with suspected or known coronary artery disease (CAD) using machine learning (ML) algorithms. A total of 453 consecutive patients underwent stress MPI by both C-SPECT and CZT-SPECT. The outcome was a composite end point of all-cause death, cardiac death, nonfatal myocardial infarction, or coronary revascularization procedures whichever occurred first. ML analysis performed through the implementation of random forest (RF) and k -nearest neighbors (KNN) algorithms proved that CZT-SPECT has greater accuracy than C-SPECT in detecting CAD. For both algorithms, the sensitivity of CZT-SPECT (96% for RF and 60% for KNN) was greater than that of C-SPECT (88% for RF and 53% for KNN). A preliminary univariate analysis was performed through Mann-Whitney tests separately on the features of each camera in order to understand which ones could distinguish patients who will experience an adverse event from those who will not. Then, a machine learning analysis was performed by using Matlab (v. 2019b). Tree, KNN, support vector machine (SVM), Naïve Bayes, and RF were implemented twice: first, the analysis was performed on the as-is dataset; then, since the dataset was imbalanced (patients experiencing an adverse event were lower than the others), the analysis was performed again after balancing the classes through the Synthetic Minority Oversampling Technique. According to KNN and SVM with and without balancing the classes, the accuracy ( p value = 0.02 and p value = 0.01) and recall ( p value = 0.001 and p value = 0.03) of the CZT-SPECT were greater than those obtained by C-SPECT in a statistically significant way. ML approach showed that although the prognostic value of stress MPI by C-SPECT and CZT-SPECT is comparable, CZT-SPECT seems to have higher accuracy and recall.
Published: 2021

6. The diagnostic role of total-body 18F-FDG PET/CT in patients with multiple tumors: a report of the association of thyroid cancer with lung or renal tumors

Author: Leandra Piscopo, Emilia Zampella, Michele Klain, Mariarosaria Manganelli, Simone Maurea, Marina De Risi, Fabio Volpe, Alberto Cuocolo, Valeria Gaudieri, Klain, Michele, Maurea, Simone, Gaudieri, Valeria, Zampella, Emilia, Volpe, Fabio, Manganelli, Mariarosaria, Piscopo, Leandra, De Risi, Marina, and Cuocolo, Alberto
Subjects: medicine.medical_specialty, Lung, business.industry, Total body, medicine.disease, medicine.anatomical_structure, medicine, Radiology, Nuclear Medicine and imaging, Fdg pet ct, In patient, Radiology, Multiple tumors, business, Thyroid cancer
Abstract: NA
Published: 2021

7. Advanced imaging tools for evaluating cardiac morphological and functional impairment in hypertensive disease

Author: Maria Virginia Manzi, Bruno Trimarco, Maria Assunta Elena Rao, Carmine Morisco, Raffaele Izzo, Maria Lembo, Alberto Cuocolo, Costantino Mancusi, Lembo, Maria, Manzi, Maria Virginia, Mancusi, Costantino, Morisco, Carmine, Rao, Maria Assunta Elena, Cuocolo, Alberto, Izzo, Raffaele, and Trimarco, Bruno
Subjects: Pressure overload, medicine.medical_specialty, Functional impairment, Physiology, business.industry, Disease progression, Echocardiography, Three-Dimensional, Heart, Cardiovascular System, Organ damage, Hypertensive disease, Echocardiography, Internal medicine, Hypertension, Internal Medicine, Cardiology, medicine, Humans, Cardiovascular Injury, Cardiology and Cardiovascular Medicine, Cardiac magnetic resonance, business, Subclinical infection
Abstract: Arterial hypertension represents a systemic burden, and it is responsible of various morphological, functional and tissue modifications affecting the heart and the cardiovascular system. Advanced imaging techniques, such as speckle tracking and three-dimensional echocardiography, cardiac magnetic resonance, computed tomography and PET-computed tomography, are able to identify cardiovascular injury at different stages of arterial hypertension, from subclinical alterations and overt organ damage to possible complications related to pressure overload, thus giving a precious contribution for guiding timely and appropriate management and therapy, in order to improve diagnostic accuracy and prevent disease progression. The present review focuses on the peculiarity of different advanced imaging tools to provide information about different and multiple morphological and functional aspects involved in hypertensive cardiovascular injury. This evaluation emphasizes the usefulness of the emerging multiimaging approach for a comprehensive overview of arterial hypertension induced cardiovascular damage.
Published: 2021

8. Prostate Volume Estimation on MRI: Accuracy and Effects of Ellipsoid and Bullet-Shaped Measurements on PSA Density

Author: Arnaldo Stanzione, Stefano Giusto Picchi, Martina Di Stasi, Gianluca Armando Di Fiore, Massimo Imbriaco, Andrea Ponsiglione, Mario Petretta, Renato Cuocolo, Francesco Verde, Stanzione, Arnaldo, Ponsiglione, Andrea, Di Fiore, Gianluca Armando, Picchi, Stefano Giusto, Di Stasi, Martina, Verde, Francesco, Petretta, Mario, Imbriaco, Massimo, and Cuocolo, Renato
Subjects: Male, Prostate biopsy, Magnetic Resonance Imaging, Prostate volume, Prostate specific antigen density, Bullet-shaped formula, Prostate cancer, Intraclass correlation, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, symbols.namesake, 0302 clinical medicine, Prostate, medicine, Humans, Radiology, Nuclear Medicine and imaging, Retrospective Studies, Reproducibility, Receiver operating characteristic, medicine.diagnostic_test, business.industry, Prostatic Neoplasms, Reproducibility of Results, Magnetic resonance imaging, Prostate-Specific Antigen, Magnetic Resonance Imaging, Bonferroni correction, medicine.anatomical_structure, Concordance correlation coefficient, ROC Curve, 030220 oncology & carcinogenesis, symbols, business, Nuclear medicine
Abstract: Rationale and Objectives PSA density (PSAd), an important decision-making parameter for patients with suspected prostate cancer (PCa), is dependent on magnetic resonance imaging prostate volume (PV) estimation. We aimed to compare the accuracy of the ellipsoid and bullet-shaped formulas with manual whole-gland segmentation as reference standard and to evaluate the corresponding PSAd diagnostic accuracy in predicting clinically significant PCa. Materials and Methods We retrospectively analysed 195 patients with suspected PCa who underwent magnetic resonance imaging and prostate biopsy. Patients with PCa were categorized according to ISUP score. PV and corresponding PSAd were calculated with manual segmentation (mPV and mPSAd) as well as with ellipsoid (ePV and ePSAd) and bullet-shaped (bPV and bPSAd) formulas. Inter and intra-reader reproducibility were assessed with Lin's concordance correlation coefficient and the intraclass correlation coefficient (ICC). A 2-way analysis of variance with post-hoc Bonferroni test was used for assessing PV differences. Predictive values of PSAd calculated with different methods for detecting clinically significant PCa were evaluated by receiver operating characteristic curve analysis and Youden's index. Results Both intra (ρ = 0.99, ICC = 0.99) and inter-reader (ρ = 0.98, ICC = 0.98) reproducibility were excellent. No significant difference was found between ePV and reference standard (p = 1.00). bPV was significantly different from both (p = 0.00). PSAd (mPSAd/ePSAd cut-off ≥ 0.15, bPSAd cut-off ≥ 0.12) had sensitivity = 69–70%, specificity = 72–75%, areas under the curve = 0.757–0.760 (p = 0.70–0.88). Conclusions Our work shows that when using bullet-shaped formula, a different PSAd cut-off must be considered to avoid PCa under-diagnosis and inaccurate risk-stratification.
Published: 2021

9. Effects of Interobserver Variability on 2D and 3D CT- and MRI-Based Texture Feature Reproducibility of Cartilaginous Bone Tumors

Author: Domenico Albano, Carmelo Messina, Salvatore Gitto, Renato Cuocolo, Ilaria Emili, Vito Chianca, Laura Tofanelli, Massimo Imbriaco, Luca Maria Sconfienza, Gitto, Salvatore, Cuocolo, Renato, Emili, Ilaria, Tofanelli, Laura, Chianca, Vito, Albano, Domenico, Messina, Carmelo, Imbriaco, Massimo, and Sconfienza, Luca Maria
Subjects: Artificial intelligence, Future studies, Intraclass correlation, Chondrosarcoma, Bone Neoplasms, Article, Region of interest, Neoplasms, Artificial intelligence, Chondroma, Chondrosarcoma, Neoplasms, Radiomics, Texture analysis, Humans, Medicine, Radiology, Nuclear Medicine and imaging, Segmentation, Texture feature, Retrospective Studies, Observer Variation, Reproducibility, Radiomics, Radiological and Ultrasound Technology, medicine.diagnostic_test, business.industry, Reproducibility of Results, Magnetic resonance imaging, medicine.disease, Magnetic Resonance Imaging, Computer Science Applications, Texture analysis, Feature (computer vision), Tomography, X-Ray Computed, business, Nuclear medicine, Chondroma
Abstract: This study aims to investigate the influence of interobserver manual segmentation variability on the reproducibility of 2D and 3D unenhanced computed tomography (CT)- and magnetic resonance imaging (MRI)-based texture analysis. Thirty patients with cartilaginous bone tumors (10 enchondromas, 10 atypical cartilaginous tumors, 10 chondrosarcomas) were retrospectively included. Three radiologists independently performed manual contour-focused segmentation on unenhanced CT and T1-weighted and T2-weighted MRI by drawing both a 2D region of interest (ROI) on the slice showing the largest tumor area and a 3D ROI including the whole tumor volume. Additionally, a marginal erosion was applied to both 2D and 3D segmentations to evaluate the influence of segmentation margins. A total of 783 and 1132 features were extracted from original and filtered 2D and 3D images, respectively. Intraclass correlation coefficient ≥ 0.75 defined feature stability. In 2D vs. 3D contour-focused segmentation, the rates of stable features were 74.71% vs. 86.57% (p p = 0.142), and 95.66% vs. 94.97% (p = 0.554) for CT and T1-weighted and T2-weighted images, respectively. Margin shrinkage did not improve 2D (p = 0.343) and performed worse than 3D (p p = 0.191), and those derived from T1-weighted and T2-weighted images were 76.0% vs. 78.2% (p = 0.285). 2D and 3D radiomic features of cartilaginous bone tumors extracted from unenhanced CT and MRI are reproducible, although some degree of interobserver segmentation variability highlights the need for reliability analysis in future studies.
Published: 2021

10. Ileal inflammatory pseudotumor in adolescent male patient with prior Burkitt lymphoma: A challenging diagnosis

Author: Alberto Cuocolo, Maria Elena Errico, Nicoletta Marra, Dalila De Lucia, Adriana D'Antonio, Salvatore Buffardi, Ciro Mainolfi, Gaia Mango, Mainolfi, Ciro Gabriele, D'Antonio, Adriana, Mango, Gaia, De Lucia, Dalila, Buffardi, Salvatore, Marra, Nicoletta, Errico, Maria Elena, and Cuocolo, Alberto
Subjects: medicine.medical_specialty, Positron emission tomography/computed tomography, R895-920, Molecular imaging, Case Report, Asymptomatic, 030218 nuclear medicine & medical imaging, Inflammatory pseudotumor, Medical physics. Medical radiology. Nuclear medicine, 03 medical and health sciences, 0302 clinical medicine, medicine, Radiology, Nuclear Medicine and imaging, Fever of unknown origin, medicine.diagnostic_test, business.industry, Histopathological analysis, Burkitt lymphoma, medicine.disease, Lymphoma, stomatognathic diseases, Positron emission tomography, Male patient, Radiology, 18F-fluorodeoxyglucose, medicine.symptom, business, 030217 neurology & neurosurgery, Rare disease
Abstract: Inflammatory pseudotumor is a rare benign mesenchymal pediatric neoplasm, that can mimic tumoral residue or relapse at metabolic imaging with nonspecific clinical presentation and difficult diagnosis. We present the case of a 14year old male patient with fever of unknown origin and large ileal mass, diagnosed with and treated for Burkitt lymphoma, who performed several 18-fluoro-deoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) scans, during and after first line chemotherapy, showing persistent and focal uptake, while ileal mass volume decreased dramatically and the patient was clinically asymptomatic. Histopathological analysis of residual ileal mass was suggestive for xanthomatous pseudotumor, a type of inflammatory pseudotumor. No more treatment was performed and a short-term follow up with 18F-FDG PET/CT showed tracer uptake intensity decreasing progressively over the next few months. This case reports an uncommon presentation of a rare disease, inflammatory pseudotumor of the small bowel developed at the site of treated Burkitt lymphoma, underscoring the potential role of 18F-FDG PET/CT imaging in the diagnosis and management of these rare neoplasms, particularly in asymptomatic patients.
Published: 2021

11. Ablation rate after radioactive iodine therapy in patients with differentiated thyroid cancer at intermediate or high risk of recurrence: a systematic review and a meta-analysis

Author: Martin Schlumberger, Michele Klain, Emilia Zampella, Mario Petretta, Mariarosaria Manganelli, Fabio Volpe, Alberto Cuocolo, Carmela Nappi, Elisa Caiazzo, Valeria Cantoni, Roberta Green, Leandra Piscopo, Klain, Michele, Nappi, Carmela, Zampella, Emilia, Cantoni, Valeria, Green, Roberta, Piscopo, Leandra, Volpe, Fabio, Manganelli, Mariarosaria, Caiazzo, Elisa, Petretta, Mario, Schlumberger, Martin, and Cuocolo, Alberto
Subjects: medicine.medical_specialty, medicine.medical_treatment, Population, 030209 endocrinology & metabolism, 131I, Adenocarcinoma, Iodine Radioisotopes, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, medicine, Recurrent disease, Humans, Radiology, Nuclear Medicine and imaging, In patient, Thyroid Neoplasms, 030212 general & internal medicine, education, Thyroid cancer, Retrospective Studies, education.field_of_study, High risk, business.industry, Intermediate risk, General Medicine, Differentiated thyroid cancer, Ablation, medicine.disease, Meta-analysis, Orthopedic surgery, Thyroidectomy, Original Article, Radioactive iodine therapy, Neoplasm Recurrence, Local, business
Abstract: Purpose We performed a systematic review and a meta-analysis to investigate the successful ablation rate after radioiodine (RAI) administration in patients with differentiated thyroid cancer (DTC) at intermediate-high risk of recurrence. Methods A comprehensive literature search of the PubMed, Scopus, and Web of Science databases was conducted according to the PRISMA statement. Results The final analysis included 9 studies accounting for 3103 patients at intermediate-high risk of recurrence. In these patients, the successful ablation rates ranged from 51 to 94% with a 71% pooled successful ablation and were higher in intermediate (72%) than in high (52%)-risk patients. Despite the rigorous inclusion standards, a significant heterogeneity among the evaluated studies was observed. Higher administered RAI activities are associated with a lower successful ablation rate in the whole population and in the subgroup of high-risk patients. Furthermore, pooled recurrence rate in intermediate-risk patients achieving successful ablation was only 2% during the subsequent 6.4-year follow-up while the pooled recurrence rate was 14% in patients who did not achieve a successful ablation. Conclusion In a large sample of 3103 patients at intermediate-high risk of persistent/recurrent disease, 71% of patients achieved a successful ablation. In these intermediate-risk patients, the probability of subsequent recurrence is low and most recurrence occurred in those with already abnormal findings at the first control.
Published: 2021

12. Handcrafted MRI radiomics and machine learning: Classification of indeterminate solid adrenal lesions

Author: Valeria Romeo, Giovanni Aprea, Renato Cuocolo, Marialaura Del Basso De Caro, Elia Guadagno, Roberta Galatola, Francesco Verde, Simone Maurea, Arnaldo Stanzione, Pier Paolo Mainenti, Stanzione, Arnaldo, Cuocolo, Renato, Verde, Francesco, Galatola, Roberta, Romeo, Valeria, Mainenti Pier, Paolo, Aprea, Giovanni, Guadagno, Elia, DEL BASSO DE CARO, Marialaura, and Maurea, Simone
Subjects: Adenoma, Support Vector Machine, Computer science, Feature extraction, Biomedical Engineering, Biophysics, Feature selection, 030218 nuclear medicine & medical imaging, Machine Learning, 03 medical and health sciences, 0302 clinical medicine, medicine, Humans, Radiology, Nuclear Medicine and imaging, Oncocytoma, Magnetic resonance imaging,Machine learning,Adrenal glands,Chemical shift imaging,Neoplasms, Retrospective Studies, business.industry, Pattern recognition, medicine.disease, Magnetic Resonance Imaging, Support vector machine, Statistical classification, Feature (computer vision), Test set, Artificial intelligence, F1 score, business, 030217 neurology & neurosurgery
Abstract: Purpose To assess a radiomic machine learning (ML) model in classifying solid adrenal lesions (ALs) without fat signal drop on chemical shift (CS) as benign or malignant. Method 55 indeterminate ALs (21 lipid poor adenomas, 15 benign pheocromocytomas, 1 oncocytoma, 12 metastases, 6 primary tumors) showing no fat signal drop on CS were retrospectively included. Manual 3D segmentation on T2-weighted and CS images was performed for subsequent radiomic feature extraction. After feature stability testing and an 80–20% train-test split, the train set was balanced via oversampling. Following a multi-step feature selection, an Extra Trees model was tuned with 5-fold stratified cross-validation in the train set and then tested on the hold-out test set. Results A total of 3396 features were extracted from each AL, of which 133 resulted unstable while none had low variance (< 0.01). Highly correlated (r > 0.8) features were also excluded, leaving 440 parameters. Among these, Support Vector Machine 5-fold stratified cross-validated recursive feature elimination selected a subset of 6 features. ML obtained a cross-validation accuracy of 0.94 on the train and 0.91 on the test sets. Precision, recall and F1 score were respectively 0.92, 0.91 and 0.91. Conclusions Our MRI handcrafted radiomics and ML pipeline proved useful to characterize benign and malignant solid indeterminate adrenal lesions.
Published: 2021

13. Neuroradiological findings in Alagille syndrome

Author: Ferdinando Caranci, Lorenzo Ugga, Renato Cuocolo, Raffaele Iorio, Fabiola Di Dato, Teresa Perillo, Alessandra D'Amico, D'Amico, Alessandra, Perillo, Teresa, Cuocolo, Renato, Ugga, Lorenzo, Di Dato, Fabiola, Caranci, Ferdinando, Iorio, Raffaele, D'Amico, A., Perillo, T., Cuocolo, R., Ugga, L., Di Dato, F., Caranci, F., and Iorio, R.
Subjects: Pathology, medicine.medical_specialty, Notch signaling pathway, Review Article, Vertebral anomalies, Craniosynostosis, Cholestasis, Alagille syndrome, Temporal bone, medicine, Humans, Radiology, Nuclear Medicine and imaging, business.industry, Skull, Cerebral Vein, Brain, General Medicine, Cerebral Arteries, medicine.disease, Cerebral Veins, Magnetic Resonance Imaging, Spine, Vertebra, Cerebral Angiography, Cerebral Arterie, Alagille Syndrome, medicine.anatomical_structure, Face, Neuroradiography, Cardiac defects, business, Human
Abstract: Alagille syndrome (ALGS) is a multisystemic disease caused by mutations in genes of Notch pathway, which regulates embryonic cell differentiation and angiogenesis. Clinically, ALGS is characterized by cholestasis, cardiac defects, characteristic facial features, skeletal and ophthalmologic abnormalities. The aim of this review is to illustrate neuroradiological findings in ALGS, which are less well-known and prevalent, including cerebrovascular anomalies (such as aneurysms, dolichoectasia, Moyamoya syndrome and venous peculiarities), Chiari 1 malformation, craniosynostosis, intracranial hypertension, and vertebral anomalies (namely butterfly vertebra, hemivertebra, and craniocervical junction anomalies). Rarer cerebral midline malformations and temporal bone anomalies have also been described.
Published: 2022

14. Relationship between epicardial adipose tissue and coronary vascular function in patients with suspected coronary artery disease and normal myocardial perfusion imaging

Author: Wanda Acampa, Carmela Nappi, Mario Petretta, Renato Cuocolo, Andrea Ponsiglione, Alberto Cuocolo, Serena Dell'Aversana, Roberta Assante, Massimo Imbriaco, Valeria Gaudieri, Teresa Mannarino, Emilia Zampella, Nappi, Carmela, Ponsiglione, Andrea, Acampa, Wanda, Gaudieri, Valeria, Zampella, Emilia, Assante, Roberta, Cuocolo, Renato, Mannarino, Teresa, Dell'Aversana, Serena, Petretta, Mario, Imbriaco, Massimo, and Cuocolo, Alberto
Subjects: medicine.medical_specialty, Coronary Artery Disease, 030204 cardiovascular system & hematology, Coronary Angiography, 030218 nuclear medicine & medical imaging, Coronary artery disease, 03 medical and health sciences, Myocardial perfusion imaging, 0302 clinical medicine, Positron Emission Tomography Computed Tomography, Internal medicine, Heart rate, medicine, Humans, Radiology, Nuclear Medicine and imaging, PET-CT, medicine.diagnostic_test, business.industry, Myocardial Perfusion Imaging, General Medicine, Blood flow, medicine.disease, Coronary Vessels, Coronary Calcium Score, Adipose Tissue, Positron emission tomography, Cardiology, Cardiology and Cardiovascular Medicine, business, Pericardium, Perfusion
Abstract: Aims We evaluated the relationship between epicardial adipose tissue (EAT) and coronary vascular function assessed by rubidium-82 (82Rb) positron emission tomography/computed tomography (PET/CT) in patients with suspected coronary artery disease (CAD). Methods and results The study population included 270 patients with suspected CAD and normal myocardial perfusion at stress–rest 82Rb PET/CT. Coronary artery calcium (CAC) score and EAT volume were measured. Absolute myocardial blood flow (MBF) was computed in mL/min/ from the dynamic rest and stress imaging. Myocardial perfusion reserve (MPR) was defined as the ratio of hyperaemic to baseline MBF and it was considered reduced when 0 (n = 156). Conclusion In patients with suspected CAD and normal myocardial perfusion, EAT volume predicts hyperaemic MBF and reduced MPR, confirming that visceral pericardium fat may influence coronary vascular function. Thus, EAT evaluation has a potential role in the early identification of coronary vascular dysfunction.
Published: 2019

15. Diagnostic performance of myocardial perfusion imaging with conventional and CZT single-photon emission computed tomography in detecting coronary artery disease: A meta-analysis

Author: Emilia Zampella, Wanda Acampa, Alberto Cuocolo, Mario Petretta, Eugenio Di Vaia, Valeria Gaudieri, Renato Cuocolo, Valeria Cantoni, Carmela Nappi, Roberta Green, Roberta Assante, Teresa Mannarino, Cantoni, Valeria, Green, Roberta, Acampa, Wanda, Zampella, Emilia, Assante, Roberta, Nappi, Carmela, Gaudieri, Valeria, Mannarino, Teresa, Cuocolo, Renato, Di Vaia, Eugenio, Petretta, Mario, and Cuocolo, Alberto
Subjects: medicine.medical_specialty, Quality Assurance, Health Care, CAD, Coronary Artery Disease, 030204 cardiovascular system & hematology, Single-photon emission computed tomography, 030218 nuclear medicine & medical imaging, Coronary artery disease, 03 medical and health sciences, Myocardial perfusion imaging, 0302 clinical medicine, medicine, Humans, Gamma Cameras, Radiology, Nuclear Medicine and imaging, Tomography, Emission-Computed, Single-Photon, medicine.diagnostic_test, business.industry, Myocardial Perfusion Imaging, Area under the curve, medicine.disease, Invasive coronary angiography, Zinc, Meta-analysis, Diameter stenosis, Radiology, Tellurium, Cardiology and Cardiovascular Medicine, business, Cadmium
Abstract: Background. We performed a meta-analysis to compare the diagnostic performance of conventional SPECT (C-SPECT) and cadmium-zinc-telluride (CZT)-SPECT systems in detecting angiographically proven coronary artery disease (CAD). Methods. Studies published between January 2000 and February 2018 were identified by database search. We included studies assessing C-SPECT or CZT-SPECT as a diagnostic test to evaluate patients for the presence of CAD, defined as at least 50% diameter stenosis on invasive coronary angiography. A study was eligible regardless of whether patients were referred for suspected or known CAD. Results. We identified 40 eligible articles (25 C-SPECT and 15 CZT-SPECT studies) including 7334 patients (4997 in C-SPECT and 2337 in CZT-SPECT studies). The pooled sensitivity and specificity were 85% and 66% for C-SPECT and 89% and 69% for CZT-SPECT imaging studies. The area under the curve was slightly higher for CZT-SPECT (0.89) compared to C-SPECT (0.83); accordingly, the summary diagnostic OR was 17 for CZT-SPECT and 11 for C-SPECT. The accuracy of the two tests slightly differs between C-SPECT and CZT-SPECT (chi-square 11.28, P < .05). At meta-regression analysis, no significant association between both sensitivity and specificity and demographical and clinical variables considered was found for C-SPECT and CZT-SPECT studies. Conclusions. C-SPECT and CZT-SPECT have good diagnostic performance in detecting angiographic proven CAD, with a slightly higher accuracy for CZT-SPECT. This result supports the use of the novel gamma cameras in clinical routine practices also considering the improvements in acquisition time and radiation exposure reduction.
Published: 2019

16. MRI based radiomics in nasopharyngeal cancer: Systematic review and perspectives using radiomic quality score (RQS) assessment

Author: Gaia Spadarella, Alberto Cuocolo, Lorenzo Ugga, Giuseppina Calareso, Renato Cuocolo, Enrico Garanzini, Spadarella, Gaia, Calareso, Giuseppina, Garanzini, Enrico, Ugga, Lorenzo, Cuocolo, Alberto, and Cuocolo, Renato
Subjects: medicine.medical_specialty, Nasopharyngeal neoplasm, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Radiomics, Medicine, Humans, Radiology, Nuclear Medicine and imaging, Prospective Studies, Nasopharyngeal Carcinoma, medicine.diagnostic_test, business.industry, Head and neck cancer, Magnetic resonance imaging, Nasopharyngeal Neoplasms, General Medicine, medicine.disease, Prognosis, Magnetic Resonance Imaging, Nasopharyngeal carcinoma, 030220 oncology & carcinogenesis, Quality Score, Mann–Whitney U test, Biomarker (medicine), Radiology, business
Abstract: Background MRI based radiomics has the potential to better define tumor biology compared to qualitative MRI assessment and support decisions in patients affected by nasopharyngeal carcinoma. Aim of this review was to systematically evaluate the methodological quality of studies using MRI- radiomics for nasopharyngeal cancer patient evaluation. Methods A systematic search was performed in PUBMED, WEB OF SCIENCE and SCOPUS using “MRI, magnetic resonance imaging, radiomic, texture analysis, nasopharyngeal carcinoma, nasopharyngeal cancer” in all possible combinations. The methodological quality of study included ( = 24) was evaluated according to the RQS (Radiomic quality score). Subgroup, for journal type (imaging/clinical) and biomarker (prognostic/predictive), and correlation, between RQS and journal Impact Factor, analyses were performed. Mann-Whitney U test and Spearman’s correlation were performed. P value < .05 were defined as statistically significant. Results Overall, no studies reported a phantom study or a test re-test for assessing stability in image, biological correlation or open science data. Only 8% of them included external validation. Almost half of articles (45%) performed multivariable analysis with non-radiomics features. Only 1 study was prospective (4%). The mean RQS was 7.5 ± 5.4. No significant differences were detected between articles published in clinical/imaging journal and between studies with a predictive or prognostic biomarker. No significant correlation was found between total RQS and Impact Factor of the year of publication (p always > 0.05). Conclusions Radiomic articles in nasopharyngeal cancer are mostly of low methodological quality. The greatest limitations are the lack of external validation, biological correlates, prospective design and open science.
Published: 2021

17. Clinical value of radiomics and machine learning in breast ultrasound: a multicenter study for differential diagnosis of benign and malignant lesions

Author: Simone Maurea, Luigi Insabato, Massimo Imbriaco, Francesco Verde, Renato Cuocolo, M. Amitrano, Valeria Romeo, Roberta Apolito, Annalisa Vitale, Anna Maria Cascone, Antonello Accurso, Maria Rosaria Argenzio, Arnaldo Stanzione, Annarita Gencarelli, Antonio Ventimiglia, Arturo Brunetti, Roberta Buonocore, Romeo, Valeria, Cuocolo, Renato, Apolito, Roberta, Stanzione, Arnaldo, Ventimiglia, Antonio, Vitale, Annalisa, Verde, Francesco, Accurso, Antonello, Amitrano, Michele, Insabato, Luigi, Gencarelli, Annarita, Buonocore, Roberta, Argenzio, Maria Rosaria, Cascone, Anna Maria, Imbriaco, Massimo, Maurea, Simone, and Brunetti, Arturo
Subjects: medicine.medical_specialty, education, Machine learning, computer.software_genre, 030218 nuclear medicine & medical imaging, Diagnosis, Differential, Machine Learning, 03 medical and health sciences, 0302 clinical medicine, McNemar's test, Breast cancer, Diagnosis, Ultrasound, Medicine, Humans, Radiology, Nuclear Medicine and imaging, Breast, Breast ultrasound, Neuroradiology, Retrospective Studies, Ultrasonography, Mammary, medicine.diagnostic_test, business.industry, General Medicine, medicine.disease, Confidence interval, Random forest, Female, Ultrasonography, Mammary, 030220 oncology & carcinogenesis, Test set, Differential, Radiology, Artificial intelligence, business, computer
Abstract: Objectives We aimed to assess the performance of radiomics and machine learning (ML) for classification of non-cystic benign and malignant breast lesions on ultrasound images, compare ML’s accuracy with that of a breast radiologist, and verify if the radiologist’s performance is improved by using ML. Methods Our retrospective study included patients from two institutions. A total of 135 lesions from Institution 1 were used to train and test the ML model with cross-validation. Radiomic features were extracted from manually annotated images and underwent a multistep feature selection process. Not reproducible, low variance, and highly intercorrelated features were removed from the dataset. Then, 66 lesions from Institution 2 were used as an external test set for ML and to assess the performance of a radiologist without and with the aid of ML, using McNemar’s test. Results After feature selection, 10 of the 520 features extracted were employed to train a random forest algorithm. Its accuracy in the training set was 82% (standard deviation, SD, ± 6%), with an AUC of 0.90 (SD ± 0.06), while the performance on the test set was 82% (95% confidence intervals (CI) = 70–90%) with an AUC of 0.82 (95% CI = 0.70–0.93). It resulted in being significantly better than the baseline reference (p = 0.0098), but not different from the radiologist (79.4%, p = 0.815). The radiologist’s performance improved when using ML (80.2%), but not significantly (p = 0.508). Conclusions A radiomic analysis combined with ML showed promising results to differentiate benign from malignant breast lesions on ultrasound images. Key Points • Machine learning showed good accuracy in discriminating benign from malignant breast lesions • The machine learning classifier’s performance was comparable to that of a breast radiologist • The radiologist’s accuracy improved with machine learning, but not significantly
Published: 2021

18. Deep Myometrial Infiltration of Endometrial Cancer on MRI: A Radiomics-Powered Machine Learning Pilot Study

Author: Arnaldo Stanzione, Valeria Romeo, Fulvio Zullo, Renata Del Grosso, Renato Cuocolo, Simone Maurea, Pier Paolo Mainenti, Luigi Insabato, Anna Nardiello, Antonio Raffone, Antonio Travaglino, Giuseppe Bifulco, Stanzione, A., Cuocolo, R., Del Grosso, R., Nardiello, A., Romeo, V., Travaglino, A., Raffone, A., Bifulco, G., Zullo, F., Insabato, L., Maurea, S., and Mainenti, P. P.
Subjects: Population, Feature extraction, Decision tree, Pilot Projects, Feature selection, Deep myometrial invasion, Machine learning, computer.software_genre, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Endometrial cancer, Humans, Medicine, Radiology, Nuclear Medicine and imaging, Segmentation, education, Retrospective Studies, education.field_of_study, Radiomics, Receiver operating characteristic, business.industry, Magnetic Resonance Imaging, Endometrial Neoplasms, Random forest, 030220 oncology & carcinogenesis, Test set, Female, Artificial intelligence, business, computer, MRI
Abstract: Rationale and Objectives To evaluate an MRI radiomics-powered machine learning (ML) model's performance for the identification of deep myometrial invasion (DMI) in endometrial cancer (EC) patients and explore its clinical applicability. Materials and Methods Preoperative MRI scans of EC patients were retrospectively selected. Three radiologists performed whole-lesion segmentation on T2-weighted images for feature extraction. Feature robustness was tested before randomly splitting the population in training and test sets (80/20% proportion). A multistep feature selection was applied to the first, excluding noninformative, low variance features and redundant, highly-intercorrelated ones. A Random Forest wrapper was used to identify the most informative among the remaining. An ensemble of J48 decision trees was tuned and finalized in the training set using 10-fold cross-validation, and then assessed on the test set. A radiologist evaluated all MRI scans without and with the aid of ML to detect the presence of DMI. McNemars's test was employed to compare the two readings. Results Of the 54 patients included, 17 had DMI. In all, 1132 features were extracted. After feature selection, the Random Forest wrapper identified the three most informative which were used for ML training. The classifier reached an accuracy of 86% and 91% and areas under the Receiver Operating Characteristic curve of 0.92 and 0.94 in the cross-validation and final testing, respectively. The radiologist performance increased from 82% to 100% when using ML (p = 0.48). Conclusion We proved the feasibility of a radiomics-powered ML model for DMI detection on MR T2-w images that might help radiologists to increase their performance.
Published: 2021

19. Assessment of therapy response to Regorafenib by 18F-DOPA-PET/CT in patients with recurrent high-grade gliomas: a case series

Author: Alessandro Villa, Maria Pia Mazzaferro, Pasqualina Giordano, Marilena Sicignano, Luigi Mansi, Alberto Negro, Alberto Cuocolo, Valeria Gaudieri, Marco Spadafora, Fiorenzo Squame, Francesca Maria Giugliano, Eugenio Di Giorgio, Di Giorgio, Eugenio, Cuocolo, Alberto, Mansi, Luigi, Sicignano, Marilena, Squame, Fiorenzo, Gaudieri, Valeria, Giordano, Pasqualina, Giugliano, Francesca Maria, Mazzaferro, Maria Pia, Negro, Alberto, Villa, Alessandro, and Spadafora, Marco
Subjects: PET-CT, medicine.diagnostic_test, business.industry, medicine.medical_treatment, Magnetic resonance imaging, Interventional radiology, Gold standard (test), 030218 nuclear medicine & medical imaging, Radiation therapy, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, chemistry, 030220 oncology & carcinogenesis, Regorafenib, Medicine, Radiology, Nuclear Medicine and imaging, In patient, business, Nuclear medicine, Perfusion
Abstract: Purpose: Regorafenib (REG) has been recently approved for the treatment of relapsed glioblastoma. Contrast-enhanced (CE) magnetic resonance (MR) imaging represents the gold standard for diagnosis and surveillance of brain tumors. We evaluated the potential role of 18F-DOPA PET/CT in determining the response to REG in a case series of patients with recurrence of high-grade gliomas. Methods: Three patients with recurrence of high-grade gliomas underwent CE-MR and 18F-DOPA PET/CT within 1 week before and at 8-week intervals after REG therapy. 18F-DOPA PET was analyzed using qualitative and quantitative approaches. For the quantitative analysis, maximum (SUVmax), mean standardized uptake values (SUVmean) and metabolic tumor volume (MTV) were obtained. Results: In two patients, an early metabolic response to REG treatment, both visually and in terms of reduction of SUVmax, SUVmean and MTV, was observed. In one subject, no metabolic response was detected. Metabolic PET data were in agreement with morphological and perfusion MRI data in two patients. In one patient, while 18F-DOPA was able to correctly diagnose a metabolic response to REG, MRI had misdiagnosed a pseudo-progression of the disease. Discussion: These preliminary findings suggest that 18F-DOPA PET/CT allows an early and reliable assessment of metabolic response to the REG treatment. A major advantage of PET seems to be obtained in patients in whom MR is unable to differentiate non-response vs tumor pseudo-progression.
Published: 2021

20. Prognostic value of coronary flow reserve in patients with suspected or known coronary artery disease referred to PET myocardial perfusion imaging: A meta-analysis

Author: Mario Petretta, Emilia Zampella, Renato Cuocolo, Wanda Acampa, Roberta Green, Valeria Cantoni, Carmela Nappi, Teresa Mannarino, Roberta Assante, Alberto Cuocolo, Valeria Gaudieri, Green, Roberta, Cantoni, Valeria, Acampa, Wanda, Assante, Roberta, Zampella, Emilia, Nappi, Carmela, Gaudieri, Valeria, Mannarino, Teresa, Cuocolo, Renato, Petretta, Mario, and Cuocolo, Alberto
Subjects: medicine.medical_specialty, Coronary Artery Disease, 030204 cardiovascular system & hematology, 030218 nuclear medicine & medical imaging, Coronary artery disease, 03 medical and health sciences, Myocardial perfusion imaging, 0302 clinical medicine, Predictive Value of Tests, Internal medicine, Medicine, Humans, Radiology, Nuclear Medicine and imaging, Adverse effect, medicine.diagnostic_test, business.industry, Hazard ratio, Myocardial Perfusion Imaging, Coronary flow reserve, medicine.disease, Prognosis, Confidence interval, Fractional Flow Reserve, Myocardial, Meta-analysis, Positron-Emission Tomography, Cardiology, Cardiology and Cardiovascular Medicine, business, Mace
Abstract: Background. We performed a meta- a meta-analysis to evaluate the prognostic value of coronary flow reserve (CFR) assessed by cardiac positron emission tomography (PET) imaging in patients with suspected or known coronary artery disease (CAD). Methods. Studies published until April 2019 were identified by database search. We included studies if they evaluated CFR by PET providing data on adjusted hazard ratio (HR) for the occurrence of adverse events. Annualized event rates were calculated and the incidence rate ratios (IRR) with 95% confidence interval (CI) were estimated to compare patients with impaired and preserved CFR. Results. We identified 13 eligible articles including 11,867 patients with a follow-up ranging from 0.6 to 7.1 years. The HR for the occurrence of major adverse cardiac events (MACE) was reported in 11 studies and pooled HR was 1.93 (95% CI 1.65-2.27). The HR for the occurrence of hard events was reported in 5 studies and pooled HR was 3.11 (95% CI 1.88-5.14). Six studies reported data useful to calculate separately the incidence rate of MACE in patients with preserved and impaired CFR and pooled IRR was 2.26 (CI 95% 1.79-2.85). Three studies reported data useful to calculate separately the incidence rate of hard events in patients with preserved and impaired CFR and pooled IRR was 4.12 (CI 95% 3.08-5.51). At meta-regression analysis we found an association between HR for MACE and gender, diabetes and hypertension, while no significant association was found between HR for hard events and demographic and clinical variables. Conclusions. In patients with suspected or known CAD an impaired CFR is associated with adverse cardiovascular events. However, the large heterogeneity in study population underlines the need for further investigations to maximize the prognostic role of CFR.
Published: 2021

21. Artificial intelligence applied to neuroimaging data in Parkinsonian syndromes: Actuality and expectations

Author: Rossella Villa, Renato Cuocolo, Arnaldo Stanzione, Lorenzo Ugga, Annalisa Vitale, Valeria Romeo, Vitale, Annalisa, Villa, Rossella, Ugga, Lorenzo, Romeo, Valeria, Stanzione, Arnaldo, and Cuocolo, Renato
Subjects: Parkinson's disease, Neuroimaging, Context (language use), 02 engineering and technology, Disease, Progressive supranuclear palsy, Parkinsonian Disorders, Artificial Intelligence, 0502 economics and business, QA1-939, 0202 electrical engineering, electronic engineering, information engineering, medicine, Humans, Pathological, parkinsonism, Aged, Motivation, business.industry, Applied Mathematics, Parkinsonism, 05 social sciences, General Medicine, medicine.disease, atypical parkinsonism, Computational Mathematics, machine learning, Clinical research, Modeling and Simulation, parkinson's disease, 020201 artificial intelligence & image processing, Supranuclear Palsy, Progressive, Artificial intelligence, General Agricultural and Biological Sciences, business, TP248.13-248.65, Mathematics, 050203 business & management, Biotechnology, Machine Learning, Parkinsonism, Artificial Intelligence, Parkinson's Disease, Atypical Parkinsonism
Abstract: Idiopathic Parkinson's Disease (iPD) is a common motor neurodegenerative disorder. It affects more frequently the elderly population, causing a significant emotional burden both for the patient and caregivers, due to the disease-related onset of motor and cognitive disabilities. iPD's clinical hallmark is the onset of cardinal motor symptoms such as bradykinesia, rest tremor, rigidity, and postural instability. However, these symptoms appear when the neurodegenerative process is already in an advanced stage. Furthermore, the greatest challenge is to distinguish iPD from other similar neurodegenerative disorders, "atypical parkinsonisms", such as Multisystem Atrophy, Progressive Supranuclear Palsy and Cortical Basal Degeneration, since they share many phenotypic manifestations, especially in the early stages. The diagnosis of these neurodegenerative motor disorders is essentially clinical. Consequently, the diagnostic accuracy mainly depends on the professional knowledge and experience of the physician. Recent advances in artificial intelligence have made it possible to analyze the large amount of clinical and instrumental information in the medical field. The application machine learning algorithms to the analysis of neuroimaging data appear to be a promising tool for identifying microstructural alterations related to the pathological process in order to explain the onset of symptoms and the spread of the neurodegenerative process. In this context, the search for quantitative biomarkers capable of identifying parkinsonian patients in the prodromal phases of the disease, of correctly distinguishing them from atypical parkinsonisms and of predicting clinical evolution and response to therapy represent the main goal of most current clinical research studies. Our aim was to review the recent literature and describe the current knowledge about the contribution given by machine learning applications to research and clinical management of parkinsonian syndromes.
Published: 2021

22. International Impact of COVID-19 on the Diagnosis of Heart Disease

Author: Einstein, A. J., Shaw, L. J., Hirschfeld, C., Williams, M. C., Villines, T. C., Better, N., Vitola, J. V., Cerci, R., Dorbala, S., Raggi, P., Choi, A. D., Lu, B., Sinitsyn, V., Sergienko, V., Kudo, T., Norgaard, B. L., Maurovich-Horvat, P., Campisi, R., Milan, E., Louw, L., Allam, A. H., Bhatia, M., Malkovskiy, E., Goebel, B., Cohen, Y., Randazzo, M., Narula, J., Pascual, T. N. B., Pynda, Y., Dondi, M., Gerd Hinterleitner, Paez D., Yao, Lu, Olga, Morozova, Zhuoran, Xu, Juan, Lopez-Mattei, Purvi, Parwani, Mohammad Nawaz Nasery, Artan, Goda, Ervina, Shirka, Rabie, Benlabgaa, Salah, Bouyoucef, Abdelkader, Medjahedi, Qais, Nailli, Mariela, Agolti, Roberto Nicolas Aguero, Maria Del Carmen Alak, Lucia Graciela Alberguina, Guillermo, Arroñada, Andrea, Astesiano, Alfredo, Astesiano, Carolina Bas Norton, Pablo, Benteo, Juan, Blanco, Juan Manuel Bonelli, Jose Javier Bustos, Raul, Cabrejas, Jorge, Cachero, Alejandro, Canderoli, Silvia, Carames, Patrícia, Carrascosa, Ricardo, Castro, Oscar, Cendoya, Luciano Martin Cognigni, Carlos, Collaud, Claudia, Cortes, Javier, Courtis, Daniel, Cragnolino, Mariana, Daicz, Alejandro De La Vega, Silvia Teresa De Maria, Horacio Del Riego, Fernando, Dettori, Alejandro, Deviggiano, Laura, Dragonetti, Mario, Embon, Ruben Emilio Enriquez, Jorge, Ensinas, Fernando, Faccio, Adolfo, Facello, Diego, Garofalo, Ricardo, Geronazzo, Natalia, Gonza, Lucas, Gutierrez, Miguel Angel Guzzo, Victor, Hasbani, Melina, Huerin, Victor, Jäger, Julio Manuel Lewkowicz, Maria Nieves, A López De Munaín, Jose Maria Lotti, Alejandra, Marquez, Osvaldo, Masoli, Edgardo, Mastrovito, Matias, Mayoraz, Graciela Eva Melado, Anibal, Mele, Maria Fernanda Merani, Alejandro Horacio Meretta, Susana, Molteni, Marcos, Montecinos, Eduardo, Noguera, Carlos, Novoa, Claudio Pereyra Sueldo, Sebastian Perez Ascani, Pablo, Pollono, Maria Paula Pujol, Alejandro, Radzinschi, Gustavo, Raimondi, Marcela, Redruello, Marina, Rodríguez, Matías, Rodríguez, Romina Lorena Romero, Arturo Romero Acuña, Federico, Rovaletti, Lucas San Miguel, Lucrecia, Solari, Bruno, Strada, Sonia, Traverso, Sonia Simona Traverzo, Maria Del Huerto Velazquez Espeche, Juan Sebastian Weihmuller, Juan, Wolcan, Susana, Zeffiro, Mari, Sakanyan, Scott, Beuzeville, Raef, Boktor, Patrick, Butler, Jennifer, Calcott, Loretta, Carr, Virgil, Chan, Charles, Chao, Woon, Chong, Mark, Dobson, D'Arne, Downie, Girish, Dwivedi, Barry, Elison, Jean, Engela, Roslyn, Francis, Anand, Gaikwad, Ashok Gangasandra Basavaraj, Bruce, Goodwin, Robert, Greenough, Christian, Hamilton-Craig, Victar, Hsieh, Subodh, Joshi, Karin, Lederer, Kenneth, Lee, Joseph, Lee, John, Magnussen, Nghi, Mai, Gordon, Mander, Fiona, Murton, Dee, Nandurkar, Johanne, Neill, Edward, O'Rourke, Patricia, O'Sullivan, George, Pandos, Kunthi, Pathmaraj, Alexander, Pitman, Rohan, Poulter, Manuja, Premaratne, David, Prior, Lloyd, Ridley, Natalie, Rutherford, Hamid, Salehi, Connor, Saunders, Luke, Scarlett, Sujith, Seneviratne, Deepa, Shetty, Ganesh, Shrestha, Jonathan, Shulman, Vijay, Solanki, Tony, Stanton, Murch, Stuart, Michael, Stubbs, Ian, Swainson, Kim, Taubman, Andrew, Taylor, Paul, Thomas, Steven, Unger, Anthony, Upton, Shankar, Vamadevan, William Van Gaal, Johan, Verjans, Demetrius, Voutnis, Victor, Wayne, Peter, Wilson, David, Wong, Kirby, Wong, John, Younger, Gudrun, Feuchtner, Siroos, Mirzaei, Konrad, Weiss, Natallia, Maroz-Vadalazhskaya, Olivier, Gheysens, Filip, Homans, Rodrigo, Moreno-Reyes, Agnès, Pasquet, Veronique, Roelants, Caroline, M Van De Heyning, Raúl Araujo Ríos, Valentina, Soldat-Stankovic, Sinisa, Stankovic, Maria Helena Albernaz Siqueira, Augusto, Almeida, Paulo Henrique Alves Togni, Jose Henrique Andrade, Luciana, Andrade, Carlos, Anselmi, Roberta, Araújo, Guilherme, Azevedo, Sabbrina, Bezerra, Rodrigo, Biancardi, Gabriel Blacher Grossman, Simone, Brandão, Diego Bromfman Pianta, Lara, Carreira, Bruno, Castro, Tien, Chang, Fernando Cunali Jr, Roberto, Cury, Roberto, Dantas, Fernando de Amorim Fernandes, Andrea De Lorenzo, Robson De Macedo Filho, Fernanda, Erthal, Fabio, Fernandes, Juliano, Fernandes, Thiago Ferreira De Souza, Wilson Furlan Alves, Bruno, Ghini, Luiz, Goncalves, Ilan, Gottlieb, Marcelo, Hadlich, Vinícius, Kameoka, Ronaldo, Lima, Adna, Lima, Rafael Willain Lopes, Ricardo Machado, E Silva, Tiago, Magalhães, Fábio Martins Silva, Luiz Eduardo Mastrocola, Fábio, Medeiros, José Claudio Meneghetti, Vania, Naue, Danilo, Naves, Roberto, Nolasco, Cesar, Nomura, Joao Bruno Oliveira, Eduardo, Paixao, Filipe Penna De Carvalho, Ibraim, Pinto, Priscila, Possetti, Mayra, Quinta, Rodrigo Rizzo Nogueira Ramos, Ricardo, Rocha, Alfredo, Rodrigues, Carlos, Rodrigues, Leila, Romantini, Adelina, Sanches, Sara, Santana, Leonardo Sara da Silva, Paulo, Schvartzman, Cristina Sebastião Matushita, Tiago, Senra, Afonso, Shiozaki, Maria Eduarda Menezes de Siqueira, Cristiano, Siqueira, Paola, Smanio, Carlos Eduardo Soares, José Soares Junior, Marcio Sommer Bittencourt, Bernardo, Spiro, Cláudio Tinoco Mesquita, Jorge, Torreao, Rafael, Torres, Marly, Uellendahl, Guilherme Urpia Monte, Otávia, Veríssimo, Estevan Vieira Cabeda, Felipe Villela Pedras, Roberto, Waltrick, Marcello, Zapparoli, Hamid, Naseer, Marina, Garcheva-Tsacheva, Irena, Kostadinova, Youdaline, Theng, Gad, Abikhzer, Rene, Barette, Benjamin, Chow, Dominique, Dabreo, Matthias, Friedrich, Ria, Garg, Mohammed Nassoh Hafez, Chris, Johnson, Marla, Kiess, Jonathon, Leipsic, Eugene, Leung, Robert, Miller, Anastasia, Oikonomou, Stephan, Probst, Idan, Roifman, Gary, Small, Vikas, Tandon, Adwait, Trivedi, James, White, Katherine, Zukotynski, Jose, Canessa, Gabriel Castro Muñoz, Carmen, Concha, Pablo, Hidalgo, Cesar, Lovera, Teresa, Massardo, Luis Salazar Vargas, Pedro, Abad, Harold, Arturo, Sandra, Ayala, Luis, Benitez, Alberto, Cadena, Carlos, Caicedo, Antonio Calderón Moncayo, Sharon, Gomez, Claudia, T Gutierrez Villamil, Claudia, Jaimes, Juan Luis Londoño Blair, Luz, Pabon, Mauricio, Pineda, Juan Carlos Rojas, Diego, Ruiz, Manuel Valencia Escobar, Andres, Vasquez, Damiana, Vergel, Alejandro, Zuluaga, Isabel Berrocal Gamboa, Gabriel, Castro, Ulises, González, Ana, Baric, Tonci, Batinic, Maja, Franceschi, Maja Hrabak Paar, Mladen, Jukic, Petar, Medakovic, Viktor, Persic, Marina, Prpic, Ante, Punda, Juan Felipe Batista, Juan Manuel Gómez Lauchy, Yamile Marcos Gutierrez, Rayner, Menéndez, Amalia, Peix, Luis, Rochela, Christoforos, Panagidis, Ioannis, Petrou, Vaclav, Engelmann, Milan, Kaminek, Vladimír, Kincl, Otto, Lang, Milan, Simanek, Jawdat, Abdulla, Morten, Bøttcher, Mette, Christensen, Lars Christian Gormsen, Philip, Hasbak, Søren, Hess, Paw, Holdgaard, Allan, Johansen, Kasper, Kyhl, Kristian Altern Øvrehus, Niels Peter Rønnow Sand, Rolf, Steffensen, Anders, Thomassen, Zerahn, Bo, Alfredo, Perez, Giovanni Alejandro Escorza Velez, Mayra Sanchez Velez, Islam Shawky Abdel Aziz, Mahasen, Abougabal, Taghreed, Ahmed, Ahmed, Asfour, Mona, Hassan, Alia, Hassan, Ahmed, Ibrahim, Sameh, Kaffas, Ahmed, Kandeel, Mohamed Mandour Ali, Ahmad, Mansy, Hany, Maurice, Sherif, Nabil, Mahmoud, Shaaban, Ana Camila Flores, Anne, Poksi, Juhani, Knuuti, Velipekka, Kokkonen, Martti, Larikka, Valtteri, Uusitalo, Matthieu, Bailly, Samuel, Burg, Jean-François, Deux, Vincent, Habouzit, Fabien, Hyafil, Olivier, Lairez, Franck, Proffit, Hamza, Regaieg, Laure, Sarda-Mantel, Vania, Tacher, Roman, P Schneider, Harold, Ayetey, George, Angelidis, Aikaterini, Archontaki, Sofia, Chatziioannou, Ioannis, Datseris, Christina, Fragkaki, Panagiotis, Georgoulias, Sophia, Koukouraki, Maria, Koutelou, Eleni, Kyrozi, Evangelos, Repasos, Petros, Stavrou, Pipitsa, Valsamaki, Carla, Gonzalez, Goleat, Gutierrez, Alejandro, Maldonado, Klara, Buga, Ildiko, Garai, Erzsébet, Schmidt, Balint, Szilveszter, Edit, Várady, Nilesh, Banthia, Jinendra Kumar Bhagat, Rishi, Bhargava, Vivek, Bhat, Partha, Choudhury, Vijay Sai Chowdekar, Aparna, Irodi, Shashank, Jain, Elizabeth, Joseph, Sukriti, Kumar, Girijanandan, Mahapatra, Deepanjan, Mitra, Bhagwant Rai Mittal, Ahmad, Ozair, Chetan, Patel, Tapan, Patel, Ravi, Patel, Shivani, Patel, Sudhir, Saxena, Shantanu, Sengupta, Santosh, Singh, Bhanupriya, Singh, Ashwani, Sood, Atul, Verma, Erwin, Affandi, Padma Savenadia Alam, Edison, Edison, Gani, Gunawan, Habusari, Hapkido, Basuki, Hidayat, Aulia, Huda, Anggoro Praja Mukti, Djoko, Prawiro, Erwin Affandi Soeriadi, Hilman, Syawaluddin, Amjed, Albadr, Majid, Assadi, Farshad, Emami, Golnaz, Houshmand, Majid, Maleki, Maryam Tajik Rostami, Seyed Rasoul Zakavi, Eed Abu Zaid, Svetlana, Agranovich, Yoav, Arnson, Rachel, Bar-Shalom, Alex, Frenkel, Galit, Knafo, Rachel, Lugassi, Israel Shlomo Maor Moalem, Maya, Mor, Noam, Muskal, Sara, Ranser, Aryeh, Shalev, Domenico, Albano, Pierpaolo, Alongi, Gaspare, Arnone, Elisa, Bagatin, Sergio, Baldari, Matteo, Bauckneht, Paolo, Bertelli, Francesco, Bianco, Rachele, Bonfiglioli, Roberto, Boni, Andrea, Bruno, Isabella, Bruno, Elena, Busnardo, Elena, Califaretti, Luca, Camoni, Aldo, Carnevale, Roberta, Casoni, Armando Ugo Cavallo, Giorgio, Cavenaghi, Franca, Chierichetti, Marcello, Chiocchi, Corrado, Cittanti, Mauro, Colletta, Umberto, Conti, Alberto, Cossu, Alberto, Cuocolo, Marco, Cuzzocrea, Maria Luisa De Rimini, Giuseppe De Vincentis, Eleonora Del Giudice, Alberico Del Torto, DELLA TOMMASINA, Veronica, Rexhep, Durmo, Erba, PAOLA ANNA, Laura, Evangelista, Riccardo, Faletti, Evelina, Faragasso, Mohsen, Farsad, Paola, Ferro, Luigia, Florimonte, Viviana, Frantellizzi, Fabio Massimo Fringuelli, Marco, Gatti, Angela, Gaudiano, Alessia, Gimelli, Raffaele, Giubbini, Francesca, Giuffrida, Salvatore, Ialuna, Riccardo, Laudicella, Lucia, Leccisotti, Lucia, Leva, Liga, Riccardo, Carlo, Liguori, Giampiero, Longo, Margherita, Maffione, Maria Elisabetta Mancini, Claudio, Marcassa, Barbara, Nardi, Sara, Pacella, Giovanna, Pepe, Gianluca, Pontone, Sabina, Pulizzi, Natale, Quartuccio, Lucia, Rampin, Fabrizio, Ricci, Pierluigi, Rossini, Giuseppe, Rubini, Vincenzo, Russo, Gian Mauro Sacchetti, Gianmario, Sambuceti, Massimo, Scarano, Roberto, Sciagrà, Massimiliano, Sperandio, Antonella, Stefanelli, Guido, Ventroni, Stefania, Zoboli, Dainia, Baugh, Duane, Chambers, Ernest, Madu, Felix, Nunura, Hiroshi, Asano, Chimura Misato Chimura, Shinichiro, Fujimoto, Koichiro, Fujisue, Tomohisa, Fukunaga, Yoshimitsu, Fukushima, Kae, Fukuyama, Jun, Hashimoto, Yasutaka, Ichikawa, Nobuo, Iguchi, Masamichi, Imai, Anri, Inaki, Hayato, Ishimura, Satoshi, Isobe, Toshiaki, Kadokami, Takao, Kato, Shinichiro, Kumita, Hirotaka, Maruno, Hiroyuki, Mataki, Masao, Miyagawa, Ryota, Morimoto, Masao, Moroi, Shigeki, Nagamachi, Kenichi, Nakajima, Tomoaki, Nakata, Ryo, Nakazato, Mamoru, Nanasato, Masanao, Naya, Takashi, Norikane, Yasutoshi, Ohta, Satoshi, Okayama, Atsutaka, Okizaki, Yoichi, Otomi, Hideki, Otsuka, Masaki, Saito, Sakata Yasushi Sakata, Masayoshi, Sarai, Daisuke, Sato, Shinya, Shiraishi, Yoshinobu, Suwa, Kentaro, Takanami, Kazuya, Takehana, Junichi, Taki, Nagara, Tamaki, Yasuyo, Taniguchi, Hiroki, Teragawa, Nobuo, Tomizawa, Kenichi, Tsujita, Kyoko, Umeji, Yasushi, Wakabayashi, Shinichiro, Yamada, Shinya, Yamazaki, Tatsuya, Yoneyama, Mohammad, Rawashdeh, Daultai, Batyrkhanov, Tairkhan, Dautov, Khalid, Makhdomi, Kevin, Ombati, Faridah, Alkandari, Masoud, Garashi, Tchoyoson Lim Coie, Sonexay, Rajvong, Artem, Kalinin, Marika, Kalnina, Mohamad, Haidar, Renata, Komiagiene, Giedre, Kviecinskiene, Mindaugas, Mataciunas, Donatas, Vajauskas, Christian, Picard, Noor Khairiah, A Karim, Luise, Reichmuth, Anthony, Samuel, Mohammad Aaftaab Allarakha, Ambedhkar Shantaram Naojee, Erick, Alexanderson-Rosas, Erika, Barragan, Alejandro Becerril González-Montecinos, Manuel, Cabada, Daniel Calderon Rodriguez, Isabel, Carvajal-Juarez, Violeta, Cortés, Filiberto, Cortés, Erasmo De La Peña, Manlio, Gama-Moreno, Luis, González, Nelsy Gonzalez Ramírez, Moisés, Jiménez-Santos, Luis, Matos, Edgar, Monroy, Martha, Morelos, Mario, Ornelas, Jose Alberto Ortga Ramirez, Andrés, Preciado-Anaya, Óscar Ulises Preciado-Gutiérrez, Adriana Puente Barragan, Sandra Graciela Rosales Uvera, Sigelinda, Sandoval, Miguel Santaularia Tomas, Lilia, M Sierra-Galan, Silvia, Siu, Enrique, Vallejo, Mario, Valles, Marc, Faraggi, Erdenechimeg, Sereegotov, Srdja, Ilic, Nozha, Ben-Rais, Nadia Ismaili Alaoui, Sara, Taleb, Khin Pa Pa Myo, Phyo Si Thu, Ram Kumar Ghimire, Bijoy, Rajbanshi, Peter, Barneveld, Andor, Glaudemans, Jesse, Habets, Klaas Pieter Koopmans, Jeroen, Manders, Stefan, Pool, Arthur, Scholte, Asbjørn, Scholtens, Riemer, Slart, Paul, Thimister, Erik-Jan Van Asperen, Niels, Veltman, Derk, Verschure, Nils, Wagenaar, John, Edmond, Chris, Ellis, Kerryanne, Johnson, Ross, Keenan, Shaw Hua Anthony Kueh, Christopher, Occleshaw, Alexander, Sasse, Andrew, To, Niels Van Pelt, Calum, Young, Teresa, Cuadra, Hector Bladimir Roque Vanegas, Idrissa Adamou Soli, Djibrillou Moussa Issoufou, Tolulope, Ayodele, Chibuzo, Madu, Yetunde, Onimode, Elen, Efros-Monsen, Signe Helene Forsdahl, Jenni-Mari Hildre Dimmen, Arve, Jørgensen, Isabel, Krohn, Pål, Løvhaugen, Anders Tjellaug Bråten, Humoud Al Dhuhli, Faiza Al Kindi, Naeema, Al-Bulushi, Zabah, Jawa, Naima, Tag, Muhammad Shehzad Afzal, Shazia, Fatima, Muhammad Numair Younis, Musab, Riaz, Mohammad, Saadullah, Yariela, Herrera, Dora, Lenturut-Katal, Manuel Castillo Vázquez, José, Ortellado, Afroza, Akhter, Dianbo, Cao, Stephen, Cheung, Dai, Xu, Lianggeng, Gong, Dan, Han, Yang, Hou, Caiying, Li, Tao, Li, Dong, Li, Sijin, Li, Jinkang, Liu, Hui, Liu, Ming Yen Ng, Kai, Sun, Gongshun, Tang, Jian, Wang, Ximing, Wang, Zhao-Qian, Wang, Yining, Wang, Yifan, Wang, Jiang, Wu, Zhifang, Wu, Liming, Xia, Jiangxi, Xiao, Lei, Xu, Youyou, Yang, Yin, Wu, Jianqun, Yu, Yuan, Li, Tong, Zhang, Longjiang, Zhang, Yong-Gao, Zhang, Xiaoli, Zhang, Zhu, Li, Ana, Alfaro, Paz, Abrihan, Asela, Barroso, Eric, Cruz, Marie Rhiamar Gomez, Vincent Peter Magboo, John Michael Medina, Jerry, Obaldo, Davidson, Pastrana, Christian Michael Pawhay, Alvin, Quinon, Jeanelle Margareth Tang, Bettina, Tecson, Kristine Joy Uson, Mila, Uy, Magdalena, Kostkiewicz, Jolanta, Kunikowska, Nuno, Bettencourt, Guilhermina, Cantinho, Antonio, Ferreira, Ghulam, Syed, Samer, Arnous, Said, Atyani, Angela, Byrne, Tadhg, Gleeson, David, Kerins, Conor, Meehan, David, Murphy, Mark, Murphy, John, Murray, Julie, O'Brien, Ji-In, Bang, Henry, Bom, Sang-Geon, Cho, Chae Moon Hong, Su Jin Jang, Yong Hyu Jeong, Won Jun Kang, Ji-Young, Kim, Jaetae, Lee, Chang Kyeong Namgung, Young, So, Kyoung Sook Won, Venjamin, Majstorov, Marija, Vavlukis, Barbara Gužic Salobir, Monika, Štalc, Theodora, Benedek, Imre, Benedek, Raluca, Mititelu, Claudiu Adrian Stan, Alexey, Ansheles, Olga, Dariy, Olga, Drozdova, Nina, Gagarina, Vsevolod Milyevich Gulyaev, Irina, Itskovich, Anatoly, Karalkin, Alexander, Kokov, Ekaterina, Migunova, Viktor, Pospelov, Daria, Ryzhkova, Guzaliya, Saifullina, Svetlana, Sazonova, Irina, Shurupova, Tatjana, Trifonova, Wladimir Yurievich Ussov, Margarita, Vakhromeeva, Nailya, Valiullina, Konstantin, Zavadovsky, Kirill, Zhuravlev, Mirvat, Alasnag, Subhani, Okarvi, Dragana Sobic Saranovic, Felix, Keng, Jia Hao Jason See, Ramkumar, Sekar, Min Sen Yew, Andrej, Vondrak, Shereen, Bejai, George, Bennie, Ria, Bester, Gerrit, Engelbrecht, Osayande, Evbuomwan, Harlem, Gongxeka, Magritha Jv Vuuren, Mitchell, Kaplan, Purbhoo, Khushica, Hoosen, Lakhi, Nico, Malan, Katarina, Milos, Moshe, Modiselle, Stuart, More, Mathava, Naidoo, Leonie, Scholtz, Mboyo, Vangu, Santiago, Aguadé-Bruix, Isabel, Blanco, Antonio, Cabrera, Alicia, Camarero, Irene, Casáns-Tormo, Hug, Cuellar-Calabria, Albert, Flotats, Maria Eugenia Fuentes Cañamero, María Elia García, Amelia, Jimenez-Heffernan, Rubén, Leta, Javier Lopez Diaz, Luis, Lumbreras, Juan Javier Marquez-Cabeza, Francisco, Martin, Anxo Martinez de Alegria, Francisco, Medina, Maria Pedrera Canal, Virginia, Peiro, Virginia, Pubul-Nuñez, Juan Ignacio Rayo Madrid, Cristina Rodríguez Rey, Ricardo Ruano Perez, Joaquín, Ruiz, Gertrudis Sabatel Hernández, Ana, Sevilla, Nahla, Zeidán, Damayanthi, Nanayakkara, Chandraguptha, Udugama, Magnus, Simonsson, Hatem, Alkadhi, Ronny Ralf Buechel, Peter, Burger, Luca, Ceriani, Bart De Boeck, Christoph, Gräni, Alix Juillet de Saint Lager Lucas, Christel, H Kamani, Nadine, Kawel-Boehm, Robert, Manka, John, O Prior, Axel, Rominger, Jean-Paul, Vallée, Benjapa, Khiewvan, Teerapon, Premprabha, Tanyaluck, Thientunyakit, Ali, Sellem, Kemal Metin Kir, Haluk, Sayman, Mugisha Julius Sebikali, Zerida, Muyinda, Yaroslav, Kmetyuk, Pavlo, Korol, Olena, Mykhalchenko, Volodymyr, Pliatsek, Maryna, Satyr, Batool, Albalooshi, Mohamed Ismail Ahmed Hassan, Jill, Anderson, Punit, Bedi, Thomas, Biggans, Anda, Bularga, Russell, Bull, Rajesh, Burgul, John-Paul, Carpenter, Duncan, Coles, David, Cusack, Aparna, Deshpande, John, Dougan, Timothy, Fairbairn, Alexia, Farrugia, Deepa, Gopalan, Alistair, Gummow, Prasad Guntur Ramkumar, Mark, Hamilton, Mark, Harbinson, Thomas, Hartley, Benjamin, Hudson, Nikhil, Joshi, Michael, Kay, Andrew, Kelion, Azhar, Khokhar, Jamie, Kitt, Ken, Lee, Chen, Low, Sze Mun Mak, Ntouskou, Marousa, Jon, Martin, Elisa, Mcalindon, Leon, Menezes, Gareth, Morgan-Hughes, Alastair, Moss, Anthony, Murray, Edward, Nicol, Dilip, Patel, Charles, Peebles, Francesca, Pugliese, Jonathan Carl Luis Rodrigues, Christopher, Rofe, Nikant, Sabharwal, Rebecca, Schofield, Thomas, Semple, Naveen, Sharma, Peter, Strouhal, Deepak, Subedi, William, Topping, Katharine, Tweed, Jonathan, Weir-Mccall, Suhny, Abbara, Taimur, Abbasi, Brian, Abbott, Shady, Abohashem, Sandra, Abramson, Tarek, Al-Abboud, Mouaz, Al-Mallah, Omar, Almousalli, Karthikeyan, Ananthasubramaniam, Mohan Ashok Kumar, Jeffrey, Askew, Lea, Attanasio, Mallory, Balmer-Swain, Richard, R Bayer, Adam, Bernheim, Sabha, Bhatti, Erik, Bieging, Ron, Blankstein, Stephen, Bloom, Sean, Blue, David, Bluemke, Andressa, Borges, Kelley, Branch, Paco, Bravo, Jessica, Brothers, Matthew, Budoff, Renée, Bullock-Palmer, Angela, Burandt, Floyd, W Burke, Kelvin, Bush, Candace, Candela, Elizabeth, Capasso, Joao, Cavalcante, Donald, Chang, Saurav, Chatterjee, Yiannis, Chatzizisis, Michael, Cheezum, Tiffany, Chen, Jennifer, Chen, Marcus, Chen, Andrew, Choi, James, Clarcq, Ayreen, Cordero, Matthew, Crim, Sorin, Danciu, Bruce, Decter, Nimish, Dhruva, Neil, Doherty, Rami, Doukky, Anjori, Dunbar, William, Duvall, Rachael, Edwards, Kerry, Esquitin, Husam, Farah, Emilio, Fentanes, Maros, Ferencik, Daniel, Fisher, Daniel, Fitzpatrick, Cameron, Foster, Tony, Fuisz, Michael, Gannon, Lori, Gastner, Myron, Gerson, Brian, Ghoshhajra, Alan, Goldberg, Brian, Goldner, Jorge, Gonzalez, Rosco, Gore, Sandra, Gracia-López, Fadi, Hage, Agha, Haider, Sofia, Haider, Yasmin, Hamirani, Karen, Hassen, Mallory, Hatfield, Carolyn, Hawkins, Katie, Hawthorne, Nicholas, Heath, Robert, Hendel, Phillip, Hernandez, Gregory, Hill, Stephen, Horgan, Jeff, Huffman, Lynne, Hurwitz, Ami, Iskandrian, Rajesh, Janardhanan, Christine, Jellis, Scott, Jerome, Dinesh, Kalra, Summanther, Kaviratne, Fernando, Kay, Faith, Kelly, Omar, Khalique, Mona, Kinkhabwala, George Kinzfogl Iii, Jacqueline, Kircher, Rachael, Kirkbride, Michael, Kontos, Anupama, Kottam, Joseph, Krepp, Jay, Layer, Steven, H Lee, Jeffrey, Leppo, John, Lesser, Steve, Leung, Howard, Lewin, Diana, Litmanovich, Yiyan, Liu, Kathleen, Magurany, Jeremy, Markowitz, Amanda, Marn, Stephen, E Matis, Michael, Mckenna, Tony, Mcrae, Fernando, Mendoza, Michael, Merhige, David, Min, Chanan, Moffitt, Karen, Moncher, Warren, Moore, Shamil, Morayati, Michael, Morris, Mahmud, Mossa-Basha, Zorana, Mrsic, Venkatesh, Murthy, Prashant, Nagpal, Kyle, Napier, Katarina, Nelson, Prabhjot, Nijjar, Medhat, Osman, Edward, Passen, Amit, Patel, Pravin, Patil, Ryan, Paul, Lawrence, Phillips, Venkateshwar, Polsani, Rajaram, Poludasu, Brian, Pomerantz, Thomas, Porter, Ryan, Prentice, Amit, Pursnani, Mark, Rabbat, Suresh, Ramamurti, Florence, Rich, Hiram Rivera Luna, Austin, Robinson, Kim, Robles, Cesar, Rodríguez, Mark, Rorie, John, Rumberger, Raymond, Russell, Philip, Sabra, Diego, Sadler, Mary, Schemmer, U Joseph Schoepf, Samir, Shah, Nishant, Shah, Sujata, Shanbhag, Gaurav, Sharma, Steven, Shayani, Jamshid, Shirani, Pushpa, Shivaram, Steven, Sigman, Mitch, Simon, Ahmad, Slim, David, Smith, Alexandra, Smith, Prem, Soman, Aditya, Sood, Monvadi Barbara Srichai-Parsia, James, Streeter, Albert, T Ahmed Tawakol, Dustin, Thomas, Randall, Thompson, Tara, Torbet, Desiree, Trinidad, Shawn, Ullery, Samuel, Unzek, Seth, Uretsky, Srikanth, Vallurupalli, Vikas, Verma, Alfonso, Waller, Ellen, Wang, Parker, Ward, Gaby, Weissman, George, Wesbey, Kelly, White, David, Winchester, David, Wolinsky, Sandra, Yost, Michael, Zgaljardic, Omar, Alonso, Mario, Beretta, Rodolfo, Ferrando, Miguel, Kapitan, Fernando, Mut, Omoa, Djuraev, Gulnora, Rozikhodjaeva, Ha Le Ngoc, Son Hong Mai, Xuan Canh Nguyen, Einstein, A. J., Shaw, L. J., Hirschfeld, C., Williams, M. C., Villines, T. C., Better, N., Vitola, J. V., Cerci, R., Dorbala, S., Raggi, P., Choi, A. D., Lu, B., Sinitsyn, V., Sergienko, V., Kudo, T., Norgaard, B. L., Maurovich-Horvat, P., Campisi, R., Milan, E., Louw, L., Allam, A. H., Bhatia, M., Malkovskiy, E., Goebel, B., Cohen, Y., Randazzo, M., Narula, J., Pascual, T. N. B., Pynda, Y., Dondi, M., Paez, D., Cuocolo, A., Einstein, A, Shaw, L, Hirschfeld, C, Williams, M, Villines, T, Better, N, Vitola, J, Cerci, R, Dorbala, S, Raggi, P, Choi, A, Lu, B, Sinitsyn, V, Sergienko, V, Kudo, T, Norgaard, B, Maurovich-Horvat, P, Campisi, R, Milan, E, Louw, L, Allam, A, Bhatia, M, Malkovskiy, E, Goebel, B, Cohen, Y, Randazzo, M, Narula, J, Pascual, T, Pynda, Y, Dondi, M, Paez, D, Pacella, S, and Erba, P
Subjects: INCAPS COVID Investigators Group, Heart disease, Vascular damage Radboud Institute for Health Sciences [Radboudumc 16], Diagnostic Techniques, Cardiovascular, coronavirus, global health, IAEA, Disease, Telehealth, Cardiorespiratory Medicine and Haematology, 030204 cardiovascular system & hematology, Cardiovascular, 0302 clinical medicine, cardiovascular disease, cardiac testing, COVID-19, diagnostic techniques, cardiovascular, health care surveys, heart diseases, humans, international agencies, Pandemic, Global health, 030212 general & internal medicine, COVID-19 Heart Disease, Cause of death, STATEMENT, Heart Disease, International Agencie, Public Health and Health Services, Biomedical Imaging, Cardiology and Cardiovascular Medicine, Human, medicine.medical_specialty, Heart Diseases, 03 medical and health sciences, Clinical Research, medicine, Humans, Personal protective equipment, Heart Disease - Coronary Heart Disease, business.industry, International Agencies, medicine.disease, the, coronaviru, Diagnostic Techniques, Good Health and Well Being, Clinical research, Cardiovascular System & Hematology, Health Care Survey, Health Care Surveys, Emergency medicine, Global Health, business
Abstract: BACKGROUND The coronavirus disease 2019 (COVID-19) pandemic has adversely affected diagnosis and treatment of noncommunicable diseases. Its effects on delivery of diagnostic care for cardiovascular disease, which remains the leading cause of death worldwide, have not been quantified. OBJECTIVES The study sought to assess COVID-19`s impact on global cardiovascular diagnostic procedural volumes and safety practices. METHODS The International Atomic Energy Agency conducted a worldwide survey assessing alterations in cardiovascular procedure volumes and safety practices resulting from COVID-19. Noninvasive and invasive cardiac testing volumes were obtained from participating sites for March and April 2020 and compared with those from March 2019. Availability of personal protective equipment and pandemic-related testing practice changes were ascertained. RESULTS Surveys were submitted from 909 inpatient and outpatient centers performing cardiac diagnostic procedures, in 108 countries. Procedure volumes decreased 42% from March 2019 to March 2020, and 64% from March 2019 to April 2020. Transthoradc echocardiography decreased by 59%, transesophageat echocardiography 76%, and stress tests 78%, which varied between stress modalities. Coronary angiography (invasive or computed tomography) decreased 55% (p < 0.001 for each procedure). hi multivariable regression, significantly greater reduction in procedures occurred for centers in countries with lower gross domestic product. Location in a low-income and lower-middle-income country was associated with an additional 22% reduction in cardiac procedures and less availability of personal protective equipment and teteheatth. CONCLUSIONS COVID-19 was associated with a significant and abrupt reduction in cardiovascular diagnostic testing across the globe, especially affecting the world's economically challenged. Further study of cardiovascular outcomes and COVID-19-related changes in care delivery is warranted. (C) 2021 The Authors. Published by Elsevier on behalf of the American College of Cardiology Foundation.
Published: 2021

23. Whole-body MRI radiomics model to predict relapsed/refractory Hodgkin Lymphoma: A preliminary study

Author: Lorenzo Ugga, Domenico Albano, Massimo Galia, Umberto Ficola, Alessandro Costa, Renato Cuocolo, Massimo Midiri, Roberto Lagalla, Roberta Faraone, Giuseppe Micci, Silvia Albano, Vito Chianca, Vittoria Tarantino, Rosario Paratore, Caterina Patti, Albano D., Cuocolo R., Patti C., Ugga L., Chianca V., Tarantino V., Faraone R., Albano S., Micci G., Costa A., Paratore R., Ficola U., Lagalla R., Midiri M., Galia M., Albano, Domenico, Cuocolo, Renato, Patti, Caterina, Ugga, Lorenzo, Chianca, Vito, Tarantino, Vittoria, Faraone, Roberta, Albano, Silvia, Micci, Giuseppe, Costa, Alessandro, Paratore, Rosario, Ficola, Umberto, Lagalla, Roberto, Midiri, Massimo, and Galia, Massimo
Subjects: Adult, Positron emission tomography, medicine.medical_specialty, Whole body mri, Biomedical Engineering, Biophysics, Vinblastine, Bleomycin, Young Adult, Refractory, Radiomics, Positron Emission Tomography Computed Tomography, Machine learning, Antineoplastic Combined Chemotherapy Protocols, Medicine, Humans, Radiology, Nuclear Medicine and imaging, Magnetic resonance imaging, Positron emission tomography, Machine learning, Texture analysis, Hodgkin Lymphoma, medicine.diagnostic_test, Hodgkin Lymphoma, business.industry, Magnetic resonance imaging, Metabolic tumor volume, Hodgkin Disease, Magnetic Resonance Imaging, Dacarbazine, Texture analysis, Doxorubicin, Relapsed refractory, Hodgkin lymphoma, Female, Radiology, Settore MED/36 - Diagnostica Per Immagini E Radioterapia, business
Abstract: Purpose A strong prognostic score that enables a stratification of newly diagnosed Hodgkin Lymphoma (HL) to identify patients at high risk of refractory/relapsed disease is still needed. Our aim was to investigate the potential value of a radiomics analysis pipeline from whole-body MRI (WB-MRI) exams for clinical outcome prediction in patients with Hodgkin Lymphoma (HL). Materials and methods Index lesions from baseline WB-MRIs of 40 patients (22 females; mean age 31.7 ± 11.4 years) with newly diagnosed HL treated by ABVD chemotherapy regimen were manually segmented on T1-weighted, STIR, and DWI images for texture analysis feature extraction. A machine learning approach based on the Extra Trees classifier and incorporating clinical variables, 18F-FDG-PET/CT-derived metabolic tumor volume, and WB-MRI radiomics features was tested using cross-validation to predict refractory/relapsed disease. Results Relapsed disease was observed in 10/40 patients (25%), two of whom died due to progression of disease and graft versus host disease, while eight reached the complete remission. In total, 1403 clinical and radiomics features were extracted, of which 11 clinical variables and 171 radiomics parameters from both original and filtered images were selected. The 3 best performing Extra Trees classifier models obtained an equivalent highest mean accuracy of 0.78 and standard deviation of 0.09, with a mean AUC of 0.82 and standard deviation of 0.08. Conclusions Our preliminary results demonstrate that a combined machine learning and texture analysis model to predict refractory/relapsed HL on WB-MRI exams is feasible and may help in the clinical outcome prediction in HL patients.
Published: 2021

24. The cardiac conundrum: a systematic review and bibliometric analysis of authorship in cardiac magnetic resonance imaging studies

Author: Francesco Verde, Renato Cuocolo, Valeria Cantoni, Valeria Romeo, Iolanda Capaldo, Ludovica D’Acierno, Valentina Picariello, Elena Augusta Vola, Giulia Lassandro, Arnaldo Stanzione, Roberta Green, Lorenzo Ugga, Massimo Imbriaco, Alberto Cuocolo, Andrea Ponsiglione, Giuseppe Pontillo, Serena Dell'Aversana, Mario Petretta, Cuocolo, Renato, Ponsiglione, Andrea, Dell’Aversana, Serena, D’Acierno, Ludovica, Lassandro, Giulia, Ugga, Lorenzo, Romeo, Valeria, Vola, Elena Augusta, Stanzione, Arnaldo, Verde, Francesco, Picariello, Valentina, Capaldo, Iolanda, Pontillo, Giuseppe, Cantoni, Valeria, Green, Roberta, Petretta, Mario, Cuocolo, Alberto, and Imbriaco, Massimo
Subjects: lcsh:Medical physics. Medical radiology. Nuclear medicine, medicine.medical_specialty, Bibliometric analysis, lcsh:R895-920, health care facilities, manpower, and services, education, 030204 cardiovascular system & hematology, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, Magnetic resonance imaging, Systematic review, Heart, Magnetic resonance imaging, 0302 clinical medicine, Cardiac magnetic resonance imaging, health services administration, medicine, Radiology, Nuclear Medicine and imaging, Journal Impact Factors, Neuroradiology, medicine.diagnostic_test, business.industry, General surgery, Critical Review, Heart, Interventional radiology, Systematic review, business
Abstract: Purpose We aimed to assess the role of radiologists, cardiologists, and other medical and non-medical figures in cardiac magnetic resonance imaging (MRI) research in the last 34 years, focusing on first and last authorship, number of published studies, and journal impact factors (IF). Methods Articles in the field of cardiac MRI were considered in this systematic review and retrospective bibliometric analysis. For included studies, the first and last authors were categorized as cardiologists, radiologists/nuclear medicine physicians, medical doctors (MD) with specialties in both cardiology and radiology/nuclear medicine, and other MD and non-MD. Differences in the number of papers published overall and by year and institution location for the first and last author category were assessed. Mean IF differences between author categories were also investigated. Results A total of 2053 articles were included in the final analysis. For the first authors (n = 2011), 52% were cardiologists, 22% radiologists/nuclear medicine physicians, 16% other MD, 10% other non-MD, and 1% both cardiologists and radiologists/nuclear medicine physicians. Similarly, the last authors (n = 2029) resulted 54% cardiologists, 22% radiologists/nuclear medicine physicians, 15% other MD, 8% other non-MD, and 2% both cardiologists and radiologists/nuclear medicine physicians. No significant differences due to institution location in the first and last authorship proportions were found. Average journal IF was significantly higher for cardiologist first and last authors when compared to that of radiologists/nuclear medicine physicians (both p < 0.0001). Conclusion Over 50% of studies in the field of cardiac MRI published in the last 34 years are conducted by cardiologists.
Published: 2020

25. Does left ventricular function predict cardiac outcome in Anderson–Fabry disease?

Author: Alberto Cuocolo, Bruno Trimarco, Letizia Spinelli, Eleonora Riccio, Giovanni Esposito, Antonio Pisani, Massimo Imbriaco, Giuseppe Giugliano, Camilla Russo, Spinelli, Letizia, Giugliano, Giuseppe, Pisani, Antonio, Imbriaco, Massimo, Riccio, Eleonora, Russo, Camilla, Cuocolo, Alberto, Trimarco, Bruno, and Esposito, Giovanni
Subjects: Adult, Male, medicine.medical_specialty, Diastole, Anderson-Fabry disease, Ventricular tachycardia, Risk Assessment, Ventricular Function, Left, Ventricular Dysfunction, Left, Predictive Value of Tests, Risk Factors, Interquartile range, Internal medicine, Ventricular Pressure, medicine, Humans, Radiology, Nuclear Medicine and imaging, Sinus rhythm, Myocardial work, Retrospective Studies, Original Paper, Univariate analysis, Anderson–Fabry disease, LV longitudinal strain, Ejection fraction, business.industry, Atrial fibrillation, Middle Aged, Prognosis, medicine.disease, Echocardiography, Doppler, Adverse cardiac event, Heart failure, Cardiology, Fabry Disease, Female, Cardiomyopathies, Cardiology and Cardiovascular Medicine, business
Abstract: In Anderson–Fabry disease (AFD) the impact of left ventricular (LV) function on cardiac outcome is unknown. Noninvasive LV pressure–strain loop analysis is a new echocardiographic method to estimate myocardial work (MW). We aimed to evaluate whether LV function was associated with outcome and whether MW had a prognostic value in AFD. Ninety-six AFD patients (41.8 ± 14.7 years, 43.7% males) with normal LV ejection fraction were retrospectively evaluated. Inclusion criteria were sinus rhythm and ≥ 2-year follow-up. Standard echocardiography measurements, myocardial mechano-energetic efficiency (MEE) index, global longitudinal strain (GLS) and MW were evaluated. Adverse cardiac events were defined as composite of cardiac death, malignant ventricular tachycardia, atrial fibrillation and severe heart failure development. During a median follow-up of 63 months (interquartile range 37–85), 14 events occurred. Patient age, cardiac biomarkers, LV mass index, left atrium volume, E/Ea ratio, LV ejection fraction, MEE index, GLS and all MW indices were significantly related to adverse outcome at univariate analysis. After adjustment for clinical and echocardiographic parameters, which were significant at univariate analysis, GLS and MW resulted independent predictors of adverse events (p
Published: 2020

26. Management of differentiated thyroid cancer through nuclear medicine facilities during Covid-19 emergency: the telemedicine challenge

Author: Michele Klain, Martin Schlumberger, Mariarosaria Manganelli, Carmela Nappi, Alberto Cuocolo, Leandra Piscopo, Simone Maurea, Marina De Risi, Elisa Caiazzo, Fabio Volpe, Klain, Michele, Nappi, Carmela, Maurea, Simone, De Risi, Marina, Volpe, Fabio, Caiazzo, Elisa, Piscopo, Leandra, Manganelli, Mariarosaria, Schlumberger, Martin, and Cuocolo, Alberto
Subjects: Male, Medical surveillance, Telemedicine, Coronavirus disease 2019 (COVID-19), medicine.medical_treatment, Office visits, 131I, Telehealth, Thyroid cancer, 030218 nuclear medicine & medical imaging, Iodine Radioisotopes, 03 medical and health sciences, 0302 clinical medicine, Outpatients, Pandemic, Ambulatory Care, medicine, Humans, Radiology, Nuclear Medicine and imaging, Thyroid Neoplasms, Pandemics, Retrospective Studies, SARS-CoV-2, business.industry, Thyroidectomy, General Medicine, medicine.disease, Italy, Radiology Nuclear Medicine and imaging, 030220 oncology & carcinogenesis, Original Article, Medical emergency, Nuclear Medicine, Southern Italy, Covid-19, business, Delivery of Health Care
Abstract: Purpose To investigate whether a telemedicine service (TMS) carried out during the Covid-19 pandemic impacted on management of patients with differentiated thyroid cancer (DTC). Methods We retrospectively reviewed the number and the findings of outpatient visits in DTC subjects referred between March 11, 2020, and May 31, 2020, during the Covid-19 pandemic at the Radiometabolic Unit of the University of Naples Federico II. Office visits scheduled in March and May 2020 were converted in teleconsultation reaching all patients planned for an in-ward access to advise them to use the TMS for all clinical necessity. The number and the findings of DTC patients evaluated by in-ward access in the corresponding period of 2019 were also assessed for direct comparison. Results The number of outpatient visits performed by TMS during the pandemic (n = 445) and by in-ward access in the corresponding period of 2019 (n = 525) was comparable with only 15% of outpatient evaluations missed. Conclusions Our findings demonstrate the utility of telemedicine tools to avoid the potential negative impact of interruption or postponement of diagnostic and/or therapeutic procedures. Therefore, investments in medical network system development, including the implementation of telehealth approaches, should be encouraged at national and international levels.
Published: 2020

27. Artificial intelligence and pituitary adenomas: A review

Author: Lorenzo Ugga, Elvira Guerriero, Renato Cuocolo, Guerriero, Elvira, Ugga, Lorenzo, and Cuocolo, Renato
Subjects: business.industry, Medicine, General Medicine, Artificial intelligence, business
Published: 2020

28. Persisting Embryonal Infundibular Recess in Morning Glory Syndrome: Clinical Report of a Novel Association

Author: Mario Cirillo, A. Grandone, Renata Conforti, Lorenzo Ugga, Renato Cuocolo, Alessandra D'Amico, D'Amico, A., Ugga, L., Cuocolo, R., Cirillo, M., Grandone, A., Conforti, R., D'Amico, A, Ugga, L, Cuocolo, Maria Rosaria, Cirillo, M, Grandone, A, and Conforti, R
Subjects: Male, Adolescent, Morning glory disc anomaly, Optic Disk, Infundibular recess, Glory, Pediatrics, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, Optic Nerve Disease, 0302 clinical medicine, Clinical report, Optic Nerve Diseases, medicine, Humans, Abnormalities, Multiple, Radiology, Nuclear Medicine and imaging, Third Ventricle, Morning, Pituitary stalk, business.industry, Syndrome, Anatomy, medicine.anatomical_structure, Child, Preschool, Pituitary Gland, Neurology (clinical), Differential diagnosis, business, 030217 neurology & neurosurgery, OPTIC-NERVE, Human, Optic disc
Abstract: SUMMARY: Morning glory syndrome is characterized by a congenital optic disc defect that resembles the eponymous flower. We present the MR imaging findings of 2 pediatric patients with morning glory disc anomaly and persisting embryonal infundibular recess, another rare malformative finding, a previously unreported association. Neuroradiologists should be aware of the possible presence of a persisting embryonal infundibular recess in patients with morning glory syndrome, to aid in the differential diagnosis including other pituitary malformations such as pituitary stalk duplication.
Published: 2019

29. Machine learning for the identification of clinically significant prostate cancer on MRI: a meta-analysis

Author: Massimo Imbriaco, Roberta Green, Arnaldo Stanzione, Valeria Romeo, Lorenzo Ugga, Andrea Ponsiglione, Maria Brunella Cipullo, Renato Cuocolo, Valeria Cantoni, Cuocolo, Renato, Cipullo, Maria Brunella, Stanzione, Arnaldo, Romeo, Valeria, Green, Roberta, Cantoni, Valeria, Ponsiglione, Andrea, Ugga, Lorenzo, and Imbriaco, Massimo
Subjects: Male, medicine.medical_specialty, Funnel plot, Biopsy, medicine.medical_treatment, Subgroup analysis, Machine learning, computer.software_genre, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, Magnetic resonance imaging, 0302 clinical medicine, Prevalence, Humans, Medicine, Meta-analysi, Radiology, Nuclear Medicine and imaging, Diagnosis, Computer-Assisted, Prostatectomy, Receiver operating characteristic, business.industry, General Medicine, Publication bias, Reference Standards, Confidence interval, Study heterogeneity, ROC Curve, Area Under Curve, 030220 oncology & carcinogenesis, Meta-analysis, Prostatic neoplasms, Radiology, Artificial intelligence, business, computer, Algorithms
Abstract: The aim of this study was to systematically review the literature and perform a meta-analysis of machine learning (ML) diagnostic accuracy studies focused on clinically significant prostate cancer (csPCa) identification on MRI. Multiple medical databases were systematically searched for studies on ML applications in csPCa identification up to July 31, 2019. Two reviewers screened all papers independently for eligibility. The area under the receiver operating characteristic curves (AUC) was pooled to quantify predictive accuracy. A random-effects model estimated overall effect size while statistical heterogeneity was assessed with the I2 value. A funnel plot was used to investigate publication bias. Subgroup analyses were performed based on reference standard (biopsy or radical prostatectomy) and ML type (deep and non-deep). After the final revision, 12 studies were included in the analysis. Statistical heterogeneity was high both in overall and in subgroup analyses. The overall pooled AUC for ML in csPCa identification was 0.86, with 0.81–0.91 95% confidence intervals (95%CI). The biopsy subgroup (n = 9) had a pooled AUC of 0.85 (95%CI = 0.79–0.91) while the radical prostatectomy one (n = 3) of 0.88 (95%CI = 0.76–0.99). Deep learning ML (n = 4) had a 0.78 AUC (95%CI = 0.69–0.86) while the remaining 8 had AUC = 0.90 (95%CI = 0.85–0.94). ML pipelines using prostate MRI to identify csPCa showed good accuracy and should be further investigated, possibly with better standardisation in design and reporting of results. • Overall pooled AUC was 0.86 with 0.81–0.91 95% confidence intervals. • In the reference standard subgroup analysis, algorithm accuracy was similar with pooled AUCs of 0.85 (0.79–0.91 95% confidence intervals) and 0.88 (0.76–0.99 95% confidence intervals) for studies employing biopsies and radical prostatectomy, respectively. • Deep learning pipelines performed worse (AUC = 0.78, 0.69–0.86 95% confidence intervals) than other approaches (AUC = 0.90, 0.85–0.94 95% confidence intervals).
Published: 2020

30. Comparison of simultaneous 18F-2-[18F] FDG PET/MR and PET/CT in the follow-up of patients with differentiated thyroid cancer

Author: Marco Salvatore, Emilia Zampella, Martin Schlumberger, Emanuele Nicolai, Carmela Nappi, Alessia Giordano, Leandra Piscopo, Valeria Romeo, Cavaliere Carlo, Michele Klain, Leonardo Pace, Alberto Cuocolo, Valeria Gaudieri, Klain, Michele, Nappi, Carmela, Nicolai, Emanuele, Romeo, Valeria, Piscopo, Leandra, Giordano, Alessia, Gaudieri, Valeria, Zampella, Emilia, Pace, Leonardo, Carlo, Cavaliere, Salvatore, Marco, Schlumberger, Martin, and Cuocolo, Alberto
Subjects: FDG, PET/CT, medicine.medical_treatment, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Differentiated thyroid cancer, PET/MR, Medicine, Radiology, Nuclear Medicine and imaging, Thyroid cancer, Fluorodeoxyglucose, PET-CT, medicine.diagnostic_test, business.industry, Thyroid, Thyroidectomy, General Medicine, medicine.disease, Radiation therapy, medicine.anatomical_structure, 030220 oncology & carcinogenesis, Thyroglobulin, business, Nuclear medicine, Emission computed tomography, medicine.drug
Abstract: Aims 18F-FDG PET/CT is the most accurate imaging modality in differentiated thyroid cancer (DTC) patients with either an aggressive histology, an absence of radioiodine uptake in neoplastic foci, or in the absence of imaging abnormalities in patients with an elevated serum thyroglobulin (Tg) level that progresses with time. We evaluated the diagnostic performance of FDG PET/MR in comparison with that of PET/CT. Methods and results Following the injection of a single 18F-FDG activity, PET/MR and PET/CT were sequentially performed in 40 consecutive patients with DTC previously treated with total thyroidectomy and radioiodine ablation. All patients were then followed up for at least 6 months. PET/MR was positive in 11 patients and PET/CT in 10. PET/MR detected 33 tumor foci and PET/CT 30. During the follow-up of the 12 patients with negative initial PET studies and with a detectable serum Tg, only one patient had a neck recurrence and the administration of an empiric high activity of 131I in the other 11 patients did not reveal any tumor focus. In the 17 patients with an initial serum Tg level < 2 ng/mL, no recurrence occurred. Conclusion This study confirms the high diagnostic accuracy of FDG PET studies in DTC patients with elevated serum Tg levels and shows that PET/MR brings similar information as compared to PET/CT imaging.
Published: 2020

31. FDG-PET/CT imaging during the Covid-19 emergency: a southern Italian perspective

Author: Alberto Cuocolo, Silvana Del Vecchio, Ciro Mainolfi, Alessandra Annunziata, Mario Petretta, Ludovica Attanasio, Claudia Bombace, Simone Maurea, Maurea, Simone, Mainolfi, Ciro Gabriele, Bombace, Claudia, Annunziata, Alessandra, Attanasio, Ludovica, Petretta, Mario, Del Vecchio, Silvana, and Cuocolo, Alberto
Subjects: medicine.medical_specialty, Fluorine Radioisotopes, Coronavirus disease 2019 (COVID-19), Thymoma, Pneumonia, Viral, Standardized uptake value, 030218 nuclear medicine & medical imaging, Imaging, 03 medical and health sciences, Betacoronavirus, 0302 clinical medicine, Fluorodeoxyglucose F18, Positron Emission Tomography Computed Tomography, Pandemic, medicine, Humans, Radiology, Nuclear Medicine and imaging, Laryngeal Neoplasms, Pandemics, Retrospective Studies, Fluorodeoxyglucose, business.industry, SARS-CoV-2, Carcinoma, COVID-19, Retrospective cohort study, General Medicine, medicine.disease, FDG-PET/CT, Pneumonia, Italy, Radiology Nuclear Medicine and imaging, 030220 oncology & carcinogenesis, Ct technique, Fdg pet ct, Original Article, Radiology, Southern Italy, Radiopharmaceuticals, business, Coronavirus Infections, Procedures and Techniques Utilization, medicine.drug
Abstract: Purpose To assess the impact of the Covid-19 pandemic on FDG-PET/CT work volume and to evaluate the occurrence of abnormal imaging findings suspicious or potentially diagnostic for interstitial pneumonia by Covid-19 infection in south Italy. Methods We retrospectively reviewed the number and the findings of FDG-PET/CT studies acquired between February and April 2020 during the Covid-19 pandemic at the University of Napoli Federico II. The number and the findings of FDG-PET/CT studies acquired in the corresponding period of 2019 were also assessed for direct comparison. Results The number of FDG-PET/CT studies performed during the pandemic (n = 299) and in the corresponding period of 2019 (n = 335) were comparable. The percentage of abnormal FDG-PET/CT findings, suspicious for interstitial pneumonia by Covid-19 infection, was significantly higher during the pandemic (9%) compared with that found in the corresponding period of 2019 (4%) (χ2 5.45, P = 0.02). No significant differences were observed in the distribution of Covid-19 reporting and data system (CO-RADS) classification and in the maximum standardized uptake value between the pandemic (2.6 ± 2.2) and the corresponding period of 2019 (3.2 ± 1.4). Of note, patients with abnormal imaging findings during the pandemic time had clinical data and/or laboratory tests negative for Covid-19 infection. Conclusion Despite the restrictive medical measures for the emergency, the number of FDG-PET/CT studies was unchanged during the pandemic compared with the previous year. Our findings also indicate that Covid-19 infection was contained in our series of patients from southern Italy.
Published: 2020

32. Quantification of myocardial perfusion reserve by CZT-SPECT: A head to head comparison with 82Rubidium PET imaging

Author: Adriana D'Antonio, Giovanni De Simini, Ciro Mainolfi, Emilia Zampella, Teresa Mannarino, Roberta Assante, Carmela Nappi, Alberto Cuocolo, Andrea Genova, Wanda Acampa, Valeria Gaudieri, Pietro Buongiorno, Mario Petretta, Acampa, Wanda, Zampella, Emilia, Assante, Roberta, Genova, Andrea, De Simini, Giovanni, Mannarino, Teresa, D'Antonio, Adriana, Gaudieri, Valeria, Nappi, Carmela, Buongiorno, Pietro, Mainolfi, Ciro Gabriele, Petretta, Mario, and Cuocolo, Alberto
Subjects: Coronary angiography, business.industry, Head to head, Area under the curve, Diagnostic and prognostic application, Pet imaging, Blood flow, 030204 cardiovascular system & hematology, Perfusion reserve, Myocardial blood flow, 030218 nuclear medicine & medical imaging, Patient management, 03 medical and health sciences, PET, 0302 clinical medicine, SPECT, Medicine, CAD, Radiology, Nuclear Medicine and imaging, Cardiology and Cardiovascular Medicine, business, Nuclear medicine, Cardiac imaging
Abstract: BACKGROUND: We measured myocardial blood flow (MBF) and perfusion reserve (MPR) by dynamic CZT-SPECT and 82Rb-PET in patients with suspected or known coronary artery disease (CAD) and compared the accuracy of the two methods in predicting obstructive CAD. METHODS: Twenty-five patients with available coronary angiography data underwent 99mTc-sestamibi CZT-SPECT and 82Rb-PET cardiac imaging. Stress and rest MBF and MPR were calculated by both methods and compared. Diagnostic accuracies of CZT-SPECT and PET were also assessed using a receiver-operator-characteristic curve. RESULTS: CZT-SPECT yielded similar baseline MBF, but higher hyperemic MBF and MPR values compared to PET. There was a modest correlation between the two methods for MPR (r = 0.56, P < .01). MPR by CZT-SPECT showed a good ability in identify a reduced MPR by PET, with an area under the curve of 0.85. A MPR cut-off of 2.5 was identified by CZT-SPECT for detection of abnormal MPR by PET, with a sensitivity, specificity and accuracy of 86%, 73% and 80%. The area under the curve for the identification of obstructive CAD by regional MPR were 0.83 for CZT-SPECT and 0.84 for PET (P = .90). At CZT-SPECT, a regional MPR of 2.1 provided the best trade-off between sensitivity and specificity for identifying obstructive CAD. Diagnostic accuracy of CZT-SPECT and PET using respective cut-off values was comparable (P = .62). CONCLUSION: Hyperemic MBF and MPR values obtained by CZT-SPECT are higher than those measured by 82Rb-PET imaging, with a moderate correlation between the two methods. CZT-SPECT shows good diagnostic accuracy for the identification of obstructive CAD. These findings may encourage the use of this new technique to a better risk stratification and patient management.
Published: 2020

33. Left ventricular radial strain impairment precedes hypertrophy in Anderson–Fabry disease

Author: Letizia Spinelli, Antonio Pisani, Andrea Ponsiglione, Bruno Trimarco, Giuseppe Giugliano, Eleonora Riccio, Massimo Imbriaco, Giovanni Esposito, Carmela Nappi, Alberto Cuocolo, Spinelli, Letizia, Giugliano, Giuseppe, Imbriaco, Massimo, Esposito, Giovanni, Nappi, Carmela, Riccio, Eleonora, Ponsiglione, Andrea, Pisani, Antonio, Cuocolo, Alberto, and Trimarco, Bruno
Subjects: Adult, Male, medicine.medical_specialty, Population, Concentric hypertrophy, Speckle tracking echocardiography, Anderson-Fabry disease, 030204 cardiovascular system & hematology, Ventricular Function, Left, Strain, 030218 nuclear medicine & medical imaging, Muscle hypertrophy, Ventricular Dysfunction, Left, Young Adult, 03 medical and health sciences, 0302 clinical medicine, Predictive Value of Tests, Fibrosis, Internal medicine, Humans, Medicine, Radiology, Nuclear Medicine and imaging, Prospective Studies, education, Cardiac imaging, Aged, Echocardiography, Doppler, Pulsed, education.field_of_study, Anderson–Fabry disease, Ejection fraction, Ventricular Remodeling, business.industry, Speckle-tracking echocardiography, Middle Aged, medicine.disease, Echocardiography, Doppler, Color, Case-Control Studies, Disease Progression, Cardiology, Fabry Disease, Female, Hypertrophy, Left Ventricular, Cardiology and Cardiovascular Medicine, business, Radial stress
Abstract: In Anderson-Fabry disease (AFD), left ventricular (LV) radial function has been scarcely investigated. We hypothesized that LV function may be affected by disease specific mechanisms and sought to comprehensively evaluate LV radial, circumferential and longitudinal function in a large population of AFD patients looking at the influence of LV geometry and fibrosis. We prospectively studied 94 consecutive AFD patients (41.5 ± 14.5 years; 41 men) with preserved LV ejection fraction (EF) utilizing speckle-tracking echocardiography. A subset of patients underwent gadolinium-enhanced cardiac magnetic resonance. Cases were compared to 48 healthy subjects matched for age and sex. LV concentric hypertrophy was found in 33 AFD patients while LV concentric remodeling (relative wall thickness ≥ 0.43) in 16 out 61 patients with normal LV mass. AFD patients had lower radial, longitudinal and circumferential strains than controls, independently by LV geometry pattern. Patients with LV hypertrophy showed reduced global longitudinal strain (p
Published: 2020

34. A machine learning-based approach to directly compare the diagnostic accuracy of myocardial perfusion imaging by conventional and cadmium-zinc telluride SPECT

Author: Giovanni De Simini, Mario Petretta, Wanda Acampa, Valeria Cantoni, Roberta Green, Roberta Assante, Teresa Mannarino, Carmela Nappi, Emilia Zampella, Andrea Genova, Alessia Giordano, Adriana D'Antonio, Carlo Ricciardi, Alberto Cuocolo, Valeria Gaudieri, Cantoni, Valeria, Green, Roberta, Ricciardi, Carlo, Assante, Roberta, Zampella, Emilia, Nappi, Carmela, Gaudieri, Valeria, Mannarino, Teresa, Genova, Andrea, De Simini, Giovanni, Giordano, Alessia, D’Antonio, Adriana, Acampa, Wanda, Petretta, Mario, and Cuocolo, Alberto
Subjects: Population, Diagnostic accuracy, CAD, Coronary Artery Disease, 030204 cardiovascular system & hematology, Machine learning, computer.software_genre, 030218 nuclear medicine & medical imaging, Machine Learning, 03 medical and health sciences, Myocardial perfusion imaging, chemistry.chemical_compound, 0302 clinical medicine, medicine, Humans, Radiology, Nuclear Medicine and imaging, Sensitivity (control systems), education, Tomography, Emission-Computed, Single-Photon, education.field_of_study, medicine.diagnostic_test, business.industry, Myocardial Perfusion Imaging, Cadmium zinc telluride, Zinc, chemistry, Known Coronary Artery Disease, Artificial intelligence, Tellurium, Cardiology and Cardiovascular Medicine, business, computer, Emission computed tomography, Cadmium
Abstract: Background. We evaluated the performance of conventional (C) single-photon emission computed tomography (SPECT) and cadmium-zinc-telluride (CZT)-SPECT in a large cohort of patients with suspected or known coronary artery disease (CAD) and compared the diagnostic accuracy of the two systems using machine learning (ML) algorithms. Methods and Results. A total of 517 consecutive patients underwent stress myocardial perfusion imaging (MPI) by both C-SPECT and CZT-SPECT. In the overall population, an excellent correlation between stress MPI data and left ventricular (LV) functional parameters measured by C-SPECT and by CZT-SPECT was observed (all P < .001). ML analysis performed through the implementation of random forest (RF) and k-nearest neighbors (NN) algorithms proved that CZT-SPECT has greater accuracy than C-SPECT in detecting CAD. For both algorithms, the sensitivity of CZT-SPECT (96% for RF and 60% for k-NN) was greater than that of C-SPECT (88% for RF and 53% for k-NN). Conclusions. MPI data and LV functional parameters obtained by CZT-SPECT are highly reproducible and provide good correlation with those obtained by C-SPECT. ML approach showed that the accuracy and sensitivity of CZT-SPECT is greater than C-SPECT in detecting CAD.
Published: 2022

35. 18F-FDG PET/CMR in cardiac sarcoidosis: A wild card in the deck?

Author: Andrea Ponsiglione, Alberto Cuocolo, Massimo Imbriaco, Carmela Nappi, Nappi, Carmela, Ponsiglione, Andrea, Imbriaco, Massimo, and Cuocolo, Alberto
Subjects: Wild card, medicine.medical_specialty, business.industry, medicine, MEDLINE, Radiology, Nuclear Medicine and imaging, Cardiac sarcoidosis, Radiology, Cardiology and Cardiovascular Medicine, business, 18f fdg pet
Published: 2022

36. Correction to: Relation between myocardial blood flow and cardiac events in diabetic patients with suspected coronary artery disease and normal myocardial perfusion imaging

Author: Mario Petretta, Parthiban Arumugam, Alberto Cuocolo, Wanda Acampa, Roberta Assante, Valeria Gaudieri, Carmela Nappi, Ciro Mainolfi, Teresa Mannarino, Emilia Zampella, Adriana D'Antonio, Assante, Roberta, Mainolfi, Ciro Gabriele, Zampella, Emilia, Gaudieri, Valeria, Nappi, Carmela, Mannarino, Teresa, D'Antonio, Adriana, Arumugam, Parthiban, Petretta, Mario, Cuocolo, Alberto, and Acampa, Wanda
Subjects: medicine.medical_specialty, medicine.diagnostic_test, business.industry, Blood flow, medicine.disease, Stress imaging, Coronary artery disease, Myocardial perfusion imaging, Diabetes mellitus, Internal medicine, Cardiology, Medicine, Radiology, Nuclear Medicine and imaging, In patient, Coronary vasodilator, Cardiology and Cardiovascular Medicine, business, Perfusion
Abstract: We assessed the prognostic value of structural abnormalities and coronary vasodilator function in diabetic patients referred to a PET/CT for suspected coronary artery disease (CAD). We studied 451 diabetics and 451 nondiabetics without overt CAD and normal myocardial perfusion. Myocardial blood flow (MBF) was computed from the dynamic rest and stress imaging. Myocardial flow reserve (MFR) was defined as ratio of hyperemic to baseline MBF and was considered reduced when
Published: 2022

37. Dynamic CZT-SPECT in coronary artery disease: Where are we now?

Author: Alberto Cuocolo, Roberta Green, Valeria Cantoni, Adriana D'Antonio, Cantoni, Valeria, Green, Roberta, D'Antonio, Adriana, and Cuocolo, Alberto
Subjects: Tomography, Emission-Computed, Single-Photon, medicine.medical_specialty, business.industry, Myocardial Perfusion Imaging, Coronary Artery Disease, medicine.disease, Coronary artery disease, Internal medicine, Cardiology, Humans, Medicine, Radiology, Nuclear Medicine and imaging, Tellurium, Cardiology and Cardiovascular Medicine, business, Cadmium
Abstract: NA
Published: 2022

38. External validation of the CRAX2MACE model in an Italian cohort of patients with suspected coronary artery disease undergoing stress myocardial perfusion imaging

Author: Adriana D'Antonio, Teresa Mannarino, Wanda Acampa, Pietro Buongiorno, Roberta Assante, Rosario Megna, Roberta Green, Mario Petretta, Carmela Nappi, Alberto Cuocolo, Valeria Cantoni, Valeria Gaudieri, Emilia Zampella, Megna, Rosario, Petretta, Mario, Assante, Roberta, Zampella, Emilia, Nappi, Carmela, Gaudieri, Valeria, Mannarino, Teresa, Green, Roberta, Cantoni, Valeria, Buongiorno, Pietro, D’Antonio, Adriana, Acampa, Wanda, and Cuocolo, Alberto
Subjects: medicine.medical_specialty, medicine.diagnostic_test, Receiver operating characteristic, business.industry, Context (language use), medicine.disease, Coronary artery disease, Myocardial perfusion imaging, Brier score, Internal medicine, Cohort, medicine, Cardiology, Radiology, Nuclear Medicine and imaging, Myocardial infarction, Cardiology and Cardiovascular Medicine, business, CAD, SPECT, MPI, Diagnostic and prognostic application, Mace
Abstract: Background. Prevention and development of diagnostic and therapeutic techniques reduced morbidity and mortality for coronary artery disease (CAD). In this context, the cardiovascular risk assessment for major adverse cardiac events (MACE) at 2-year (CRAX2MACE) model for prediction of 2-year major adverse cardiac events was developed. We performed an external validation of this model. Methods. We included 1003 patients with suspected CAD undergoing stress-rest single photon emission computed tomography myocardial perfusion imaging at our academic center between March 2015 and April 2019. Results. Considering the occurrence of MACE (death from any cause, acute myocardial infarction, or late coronary revascularization), for the CRAX2MACE model the area under the receiver operating characteristic curve was 0.612 and the Brier score was 0.061. The Hosmer–Lemeshow test estimated a non-optimal fit (X2 28, P < .001). Considering only hard events (cardiac death, acute myocardial infarction), the external validation of the CRAX2MACE model revealed a Brier score of 0.053 and an area under the receiver operating characteristic curve of 0.621. Hosmer–Lemeshow test was calculated by deciles and showed a poor fit (X2 31, P < .001). Conclusion. CRAX2MACE model had a limited value for predicting 2-year major adverse cardiovascular events in an external validation cohort of patients with suspected CAD.
Published: 2022

39. T2 mapping of the trapeziometacarpal joint and triangular fibrocartilage complex: a feasibility and reproducibility study at 1.5 T

Author: Domenico Albano, Carmelo Messina, Salvatore Gitto, Vito Chianca, Renato Cuocolo, Arturo Brunetti, Luca Maria Sconfienza, Chianca, V., Albano, D., Cuocolo, R., Messina, C., Gitto, S., Brunetti, A., and Sconfienza, L. M.
Subjects: Adult, Male, Triangular Fibrocartilage, Wrist Joint, Trapeziometacarpal joint, T2 mapping, Reproducibility of Result, Wrist, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Humans, Medicine, Radiology, Nuclear Medicine and imaging, Multislice, Prospective Studies, Observer Variation, Reproducibility, medicine.diagnostic_test, business.industry, Metacarpal Bone, Ultrasound, Reproducibility of Results, Cartilaginous part, Magnetic resonance imaging, General Medicine, Metacarpal Bones, Healthy Volunteer, Magnetic Resonance Imaging, Healthy Volunteers, Feasibility Studie, Prospective Studie, Cartilage, medicine.anatomical_structure, 030220 oncology & carcinogenesis, Feasibility Studies, Trapezoid Bone, Triangular fibrocartilage complex, Female, business, Nuclear medicine, Triangular Fibrocartilage Complex, Human
Abstract: Purpose: To assess the feasibility and reproducibility of T2 relaxation time measurements of the trapeziometacarpal joint (TM) and triangular fibrocartilage complex (TFCC) on healthy subjects at 1.5 T MR. Materials and methods: Thirty-four healthy volunteers underwent an axial oblique multislice multiecho spin-echo sequence of the wrist at 1.5 T, with 10 of them having performed another MR scan on a different 1.5 T scanner. Regions of interest were independently manually drawn by two musculoskeletal radiologists to include the cartilaginous part of the TM and TFCC. Intra-observer, inter-observer and inter-scanner reproducibility of T2 relaxation time measurements was tested using the Bland–Altman method. Results: The mean T2 values obtained by the two radiologists were 29.9 ± 6.5 ms and 30.0 ± 6.1 ms in the TM and 24.5 ± 2.3 ms and 24.6 ± 2.8 ms in the TFCC, respectively. The mean values of the second series of T2 measurements obtained by the senior radiologist were 29.9 ± 6.5 ms and 30.0 ± 6.3 ms in the TM and 24.3 ± 2.9 ms in the TFCC. Inter-observer reproducibility in the TM and in the TFCC was 76% and 82%, respectively. Intra-observer reproducibility in the TM and TFCC was 71% and 76%, respectively. Inter-scanner reproducibility of T2 measurements was 36% in the TM and 85% in the TFCC, respectively. Conclusion: The assessment of T2 relaxation time measurements of the cartilage of the TM and the TFCC seems to be feasible and reproducible, although the inter-scanner reproducibility of T2 measurements of the TM is suboptimal. Further studies including patients are warranted to prove the utility of this tool.
Published: 2019

40. Renal function and cardiac adrenergic impairment in patients affected by heart failure

Author: Stefania Paolillo, Immacolata Esposito, Francesco Renga, Santo Dellegrottaglie, Paola Gargiulo, Caterina Marciano, Carmela Nappi, Fabio Marsico, Roberta Assante, Simona Dell'Aversana, Luca Esposito, Valentina Parisi, Luca Bardi, Pasquale Perrone Filardi, Giuseppe Rengo, Alberto Cuocolo, Dario Leosco, Marsico, Fabio, Paolillo, Stefania, Gargiulo, Paola, Parisi, Valentina, Nappi, Carmela, Assante, Roberta, Dell’Aversana, Simona, Esposito, Immacolata, Renga, Francesco, Esposito, Luca, Bardi, Luca, Rengo, Giuseppe, Dellegrottaglie, Santo, Marciano, Caterina, Leosco, Dario, Cuocolo, Alberto, and Filardi, Pasquale Perrone
Subjects: Male, medicine.medical_specialty, Population, Adrenergic, Renal function, 030204 cardiovascular system & hematology, Kidney, Statistics, Nonparametric, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, Adrenergic Agents, 0302 clinical medicine, renal dysfunction, Internal medicine, Epidemiology, Humans, Medicine, Radiology, Nuclear Medicine and imaging, education, Aged, Heart Failure, glomerular filtration rate, education.field_of_study, Ejection fraction, business.industry, Heart, Middle Aged, medicine.disease, medicine.anatomical_structure, Italy, sympathetic nervous system overactivity, Heart failure, Cardiology, Female, Kidney Diseases, Cardiology and Cardiovascular Medicine, business, Kidney disease
Abstract: Although in heart failure (HF) there is a strict correlation between heart and kidney, no data are available on the potential relationship in HF between renal dysfunction (RD) and the impaired sympathetic innervation. Aim of the present study was to assess the relationship between RD and cardiac sympathetic innervation in HF patients with reduced ejection fraction. Two hundred and sixty-three patients with mild-to-severe HF underwent iodine-123 meta-iodobenzylguanidine myocardial scintigraphy to assess sympathetic innervation, evaluating early and late heart-to-mediastinum (H/M) ratios and washout rate. In all patients, glomerular filtration rate (eGFR) by Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula was assessed. A direct association was found between EPI-eGFR and late H/M (r = .215; P
Published: 2019

41. Nuclear cardiac imaging between implementation and globalization: The key role of integration

Author: Alberto Cuocolo, Carmela Nappi, Mario Petretta, Wanda Acampa, Cuocolo, Alberto, Nappi, Carmela, Acampa, Wanda, and Petretta, Mario
Subjects: Tomography, Emission-Computed, Single-Photon, 2019-20 coronavirus outbreak, Internationality, Coronavirus disease 2019 (COVID-19), business.industry, Computed Tomography Angiography, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Physical Distancing, Cardiology, COVID-19, Coronary Artery Disease, Data science, Globalization, Positron-Emission Tomography, Key (cryptography), Medicine, Humans, Radiology, Nuclear Medicine and imaging, Nuclear Medicine, Cardiology and Cardiovascular Medicine, business, Delivery of Health Care, Cardiac imaging, Editor's Page, Societies, Medical
Abstract: NA
Published: 2021

42. Prevalence of interstitial pneumonia suggestive of COVID-19 at 18F-FDG PET/CT in oncological asymptomatic patients in a high prevalence country during pandemic period: a national multi-centric retrospective study

Author: Albano, Domenico, Bertagna, Francesco, Alongi, Pierpaolo, Baldari, Sergio, Baldoncini, Alfonso, Bartolomei, Mirco, Boccaletto, Franco, Boero, Michele, Borsatti, Eugenio, Bruno, Andrea, Burroni, Luca, Capoccetti, Francesca, Castellani, Massimo, Cervino, Anna Rita, Chierichetti, Franca, Ciarmiello, Andrea, Corso, Angelo, Cuocolo, Alberto, De Rimini, Maria Luisa, Deandreis, Desiree’, Dottorini, Massimo Eugenio, Esposito, Filomena, Farsad, Mohsen, Gasparini, Massimo, Grana, Chiara Maria, Gregianin, Michele, Guerra, Luca, Loreti, Fabio, Lupi, Andrea, Martino, Gianluigi, Milan, Elisa, Modoni, Sergio, Morbelli, Silvia, Muni, Alfredo, Nicolai, Emanuele, Palumbo, Barbara, Papa, Sergio, Papaleo, Alberto, Pellerito, Riccardo, Poti, Carlo, Romano, Pasquale, Rossetti, Claudio, Rossini, Pierluigi, Rubini, Giuseppe, Ruffini, Livia, Sacchetti, Gianmauro, Savelli, Giordano, Schiavariello, Saverio, Sciagrà, Roberto, Sciuto, Rosa, Seregni, Ettore, Sestini, Stelvio, Sicolo, Michele, Spanu, Angela, Storto, Giovanni, Balducci, Massimo Tosti, Trifirò, Giuseppe, Versari, Annibale, Vignati, Alberto, Volterrani, Duccio, Calcagni, Maria Lucia, Marzola, Maria Cristina, Garufo, Antonio, Evangelista, Laura, Maroldi, Roberto, Schillaci, Orazio, Giubbini, Raffaele, Bonacina, M., Laudicella, R., Spallino, M., Palucci, A., Cuzzocrea, M., Donner, M., Maurea, S., Ceci, F., Dei Rossi, F., Tranfaglia, B., Sartorello, A., Gandolfo, P., Buschiazzo, A., Scarale, A., Kirienko, M., Merenda, N., Nappi, A. G., Durmo, R., Vellani, C., Ceriani, V., Albano, D, Bertagna, F, Alongi, P, Baldari, S, Baldoncini, A, Bartolomei, M, Boccaletto, F, Boero, M, Borsatti, E, Bruno, A, Burroni, L, Capoccetti, F, Castellani, M, Cervino, A, Chierichetti, F, Ciarmiello, A, Corso, A, Cuocolo, A, De Rimini, M, Deandreis, D, Dottorini, M, Esposito, F, Farsad, M, Gasparini, M, Grana, C, Gregianin, M, Guerra, L, Loreti, F, Lupi, A, Martino, G, Milan, E, Modoni, S, Morbelli, S, Muni, A, Nicolai, E, Palumbo, B, Papa, S, Papaleo, A, Pellerito, R, Poti, C, Romano, P, Rossetti, C, Rossini, P, Rubini, G, Ruffini, L, Sacchetti, G, Savelli, G, Schiavariello, S, Sciagra, R, Sciuto, R, Seregni, E, Sestini, S, Sicolo, M, Spanu, A, Storto, G, Balducci, M, Trifiro, G, Versari, A, Vignati, A, Volterrani, D, Calcagni, M, Marzola, M, Garufo, A, Evangelista, L, Maroldi, R, Schillaci, O, Giubbini, R, Bonacina, M, Laudicella, R, Spallino, M, Palucci, A, Cuzzocrea, M, Donner, M, Maurea, S, Ceci, F, Dei Rossi, F, Tranfaglia, B, Sartorello, A, Gandolfo, P, Buschiazzo, A, Scarale, A, Kirienko, M, Merenda, N, Nappi, A, Durmo, R, Vellani, C, Ceriani, V, Albano, Domenico, Bertagna, Francesco, Alongi, Pierpaolo, Baldari, Sergio, Baldoncini, Alfonso, Bartolomei, Mirco, Boccaletto, Franco, Boero, Michele, Borsatti, Eugenio, Bruno, Andrea, Burroni, Luca, Capoccetti, Francesca, Castellani, Massimo, Cervino, Anna Rita, Chierichetti, Franca, Ciarmiello, Andrea, Corso, Angelo, Cuocolo, Alberto, De Rimini, Maria Luisa, Deandreis, Desiree', Dottorini, Massimo Eugenio, Esposito, Filomena, Farsad, Mohsen, Gasparini, Massimo, Grana, Chiara Maria, Gregianin, Michele, Guerra, Luca, Loreti, Fabio, Lupi, Andrea, Martino, Gianluigi, Milan, Elisa, Modoni, Sergio, Morbelli, Silvia, Muni, Alfredo, Nicolai, Emanuele, Palumbo, Barbara, Papa, Sergio, Papaleo, Alberto, Pellerito, Riccardo, Poti, Carlo, Romano, Pasquale, Rossetti, Claudio, Rossini, Pierluigi, Rubini, Giuseppe, Ruffini, Livia, Sacchetti, Gianmauro, Savelli, Giordano, Schiavariello, Saverio, Sciagrà, Roberto, Sciuto, Rosa, Seregni, Ettore, Sestini, Stelvio, Sicolo, Michele, Spanu, Angela, Storto, Giovanni, Balducci, Massimo Tosti, Trifirò, Giuseppe, Versari, Annibale, Vignati, Alberto, Volterrani, Duccio, Calcagni, Maria Lucia, Marzola, Maria Cristina, Garufo, Antonio, Evangelista, Laura, Maroldi, Roberto, Schillaci, Orazio, and Giubbini, Raffaele
Subjects: Lung Diseases, medicine.medical_specialty, Coronavirus disease 2019 (COVID-19), Asymptomatic, Incidental finding, Fluorodeoxyglucose F18, Positron Emission Tomography Computed Tomography, Pandemic, Prevalence, medicine, Humans, Radiology, Nuclear Medicine and imaging, 18F-FDG PET/CT, COVID-19, Incidental findings, Interstitial pneumonia, SARS-CoV-2, Italy, Pandemics, Retrospective Studies, Lung Diseases, Interstitial, Settore MED/36 - DIAGNOSTICA PER IMMAGINI E RADIOTERAPIA, Lung, medicine.diagnostic_test, business.industry, F-FDG PET/CT, Interstitial lung disease, Retrospective cohort study, General Medicine, medicine.disease, Pneumonia, medicine.anatomical_structure, Radiology Nuclear Medicine and imaging, Positron emission tomography, Radiology, medicine.symptom, Interstitial, business
Abstract: Purpose To assess the presence and pattern of incidental interstitial lung alterations suspicious of COVID-19 on fluorine-18-fluorodeoxyglucose positron emission tomography (PET)/computed tomography (CT) ([18F]FDG PET/CT) in asymptomatic oncological patients during the period of active COVID-19 in a country with high prevalence of the virus. Methods This is a multi-center retrospective observational study involving 59 Italian centers. We retrospectively reviewed the prevalence of interstitial pneumonia detected during the COVID period (between March 16 and 27, 2020) and compared to a pre-COVID period (January–February 2020) and a control time (in 2019). The diagnosis of interstitial pneumonia was done considering lung alterations of CT of PET. Results Overall, [18F]FDG PET/CT was performed on 4008 patients in the COVID period, 19,267 in the pre-COVID period, and 5513 in the control period. The rate of interstitial pneumonia suspicious for COVID-19 was significantly higher during the COVID period (7.1%) compared with that found in the pre-COVID (5.35%) and control periods (5.15%) (p Conclusions A significant increase of interstitial pneumonia incidentally detected with [18F]FDG PET/CT has been demonstrated during the COVID-19 pandemic. A majority of interstitial pneumonia were FDG-avid. Our results underlined the importance of paying attention to incidental CT findings of pneumonia detected at PET/CT, and these reports might help to recognize early COVID-19 cases guiding the subsequent management.
Published: 2021

43. State of the art of 18F-FDG PET/CT application in inflammation and infection: a guide for image acquisition and interpretation

Author: Francesco Muratore, Martina Sollini, Michela Massollo, Domenico Albano, Luca Burroni, Anna Paola Erba, Laura Evangelista, Sergio Baldari, Chiara Lauri, Alberto Signore, Alberto Nieri, Francesco Bertagna, Alberto Cuocolo, Corinna Altini, Cristina Ferrari, Massimiliano Casali, Francesco Dondi, Giuseppe Rubini, Valentina Lavelli, Brunella Rossi, Gianluca Cassarino, Francesco Bartoli, Andrea Palucci, Napoleone Prandini, Alessia Giordano, Riccardo Laudicella, Natale Quartuccio, Patrizia Gandolfo, Mirco Bartolomei, Annibale Versari, Elena Lazzeri, Angelina Cistaro, Ciro Mainolfi, Laura Vendramin, Adriana D'Antonio, Arnoldo Piccardo, Casali, Massimiliano, Lauri, Chiara, Altini, Corinna, Bertagna, Francesco, Cassarino, Gianluca, Cistaro, Angelina, Erba, Anna Paola, Ferrari, Cristina, Mainolfi, Ciro Gabriele, Palucci, Andrea, Prandini, Napoleone, Baldari, Sergio, Bartoli, Francesco, Bartolomei, Mirco, D’Antonio, Adriana, Dondi, Francesco, Gandolfo, Patrizia, Giordano, Alessia, Laudicella, Riccardo, Massollo, Michela, Nieri, Alberto, Piccardo, Arnoldo, Vendramin, Laura, Muratore, Francesco, Lavelli, Valentina, Albano, Domenico, Burroni, Luca, Cuocolo, Alberto, Evangelista, Laura, Lazzeri, Elena, Quartuccio, Natale, Rossi, Brunella, Rubini, Giuseppe, Sollini, Martina, Versari, Annibale, Signore, Alberto, Casali, M, Lauri, C, Altini, C, Bertagna, F, Cassarino, G, Cistaro, A, Erba, P, Ferrari, C, Mainolfi, C, Palucci, A, Prandini, N, Baldari, S, Bartoli, F, Bartolomei, M, D'Antonio, A, Dondi, F, Gandolfo, P, Giordano, A, Laudicella, R, Massollo, M, Nieri, A, Piccardo, A, Vendramin, L, Muratore, F, Lavelli, V, Albano, D, Burroni, L, Cuocolo, A, Evangelista, L, Lazzeri, E, Quartuccio, N, Rossi, B, Rubini, G, Sollini, M, Versari, A, and Signore, A
Subjects: Inflammation, medicine.medical_specialty, Tuberculosis, medicine.diagnostic_test, business.industry, FDG, Osteomyelitis, Interventional radiology, Disease, medicine.disease, Retroperitoneal fibrosis, Diabetic foot, Imaging, PET, Positron emission tomography, Infective endocarditis, medicine, Radiology, Nuclear Medicine and imaging, Radiology, medicine.symptom, business, Expert Review, Infection
Abstract: Aim The diagnosis, severity and extent of a sterile inflammation or a septic infection could be challenging since there is not one single test able to achieve an accurate diagnosis. The clinical use of 18F-fluorodeoxyglucose ([18F]FDG) positron emission tomography/computed tomography (PET/CT) imaging in the assessment of inflammation and infection is increasing worldwide. The purpose of this paper is to achieve an Italian consensus document on [18F]FDG PET/CT or PET/MRI in inflammatory and infectious diseases, such as osteomyelitis (OM), prosthetic joint infections (PJI), infective endocarditis (IE), prosthetic valve endocarditis (PVE), cardiac implantable electronic device infections (CIEDI), systemic and cardiac sarcoidosis (SS/CS), diabetic foot (DF), fungal infections (FI), tuberculosis (TBC), fever and inflammation of unknown origin (FUO/IUO), pediatric infections (PI), inflammatory bowel diseases (IBD), spine infections (SI), vascular graft infections (VGI), large vessel vasculitis (LVV), retroperitoneal fibrosis (RF) and COVID-19 infections. Methods In September 2020, the inflammatory and infectious diseases focus group (IIFG) of the Italian Association of Nuclear Medicine (AIMN) proposed to realize a procedural paper about the clinical applications of [18F]FDG PET/CT or PET/MRI in inflammatory and infectious diseases. The project was carried out thanks to the collaboration of 13 Italian nuclear medicine centers, with a consolidate experience in this field. With the endorsement of AIMN, IIFG contacted each center, and the pediatric diseases focus group (PDFC). IIFG provided for each team involved, a draft with essential information regarding the execution of [18F]FDG PET/CT or PET/MRI scan (i.e., indications, patient preparation, standard or specific acquisition modalities, interpretation criteria, reporting methods, pitfalls and artifacts), by limiting the literature research to the last 20 years. Moreover, some clinical cases were required from each center, to underline the teaching points. Time for the collection of each report was from October to December 2020. Results Overall, we summarized 291 scientific papers and guidelines published between 1998 and 2021. Papers were divided in several sub-topics and summarized in the following paragraphs: clinical indications, image interpretation criteria, future perspectivess and new trends (for each single disease), while patient preparation, image acquisition, possible pitfalls and reporting modalities were described afterwards. Moreover, a specific section was dedicated to pediatric and PET/MRI indications. A collection of images was described for each indication. Conclusions Currently, [18F]FDG PET/CT in oncology is globally accepted and standardized in main diagnostic algorithms for neoplasms. In recent years, the ever-closer collaboration among different European associations has tried to overcome the absence of a standardization also in the field of inflammation and infections. The collaboration of several nuclear medicine centers with a long experience in this field, as well as among different AIMN focus groups represents a further attempt in this direction. We hope that this document will be the basis for a “common nuclear physicians’ language” throughout all the country. Supplementary Information The online version contains supplementary material available at 10.1007/s40336-021-00445-w.
Published: 2021

44. A Comparison among Different Machine Learning Pretest Approaches to Predict Stress-Induced Ischemia at PET/CT Myocardial Perfusion Imaging

Author: Alberto Cuocolo, Valeria Gaudieri, Adriana D'Antonio, Carmela Nappi, Parthiban Arumugam, Roberta Green, Rosario Megna, Roberta Assante, Teresa Mannarino, Emilia Zampella, Wanda Acampa, Mario Petretta, Valeria Cantoni, Megna, Rosario, Petretta, Mario, Assante, Roberta, Zampella, Emilia, Nappi, Carmela, Gaudieri, Valeria, Mannarino, Teresa, D’Antonio, Adriana, Green, Roberta, Cantoni, Valeria, Arumugam, Parthiban, Acampa, Wanda, and Cuocolo, Alberto
Subjects: Male, Support Vector Machine, Article Subject, Computer applications to medicine. Medical informatics, R858-859.7, Myocardial Ischemia, Coronary Artery Disease, Machine learning, computer.software_genre, General Biochemistry, Genetics and Molecular Biology, Cohort Studies, Machine Learning, Myocardial perfusion imaging, Naive Bayes classifier, Predictive Value of Tests, Positron Emission Tomography Computed Tomography, medicine, Humans, AdaBoost, Aged, PET-CT, General Immunology and Microbiology, medicine.diagnostic_test, business.industry, Applied Mathematics, Decision Trees, Myocardial Perfusion Imaging, Computational Biology, Bayes Theorem, General Medicine, Gold standard (test), Middle Aged, Random forest, Pre- and post-test probability, Logistic Models, Positron emission tomography, Modeling and Simulation, Exercise Test, Female, Artificial intelligence, business, computer, Algorithms, Research Article
Abstract: Traditional approach for predicting coronary artery disease (CAD) is based on demographic data, symptoms such as chest pain and dyspnea, and comorbidity related to cardiovascular diseases. Usually, these variables are analyzed by logistic regression to quantifying their relationship with the outcome; nevertheless, their predictive value is limited. In the present study, we aimed to investigate the value of different machine learning (ML) techniques for the evaluation of suspected CAD; having as gold standard, the presence of stress-induced ischemia by 82Rb positron emission tomography/computed tomography (PET/CT) myocardial perfusion imaging (MPI) ML was chosen on their clinical use and on the fact that they are representative of different classes of algorithms, such as deterministic (Support vector machine and Naïve Bayes), adaptive (ADA and AdaBoost), and decision tree (Random Forest, rpart, and XGBoost). The study population included 2503 consecutive patients, who underwent MPI for suspected CAD. To testing ML performances, data were split randomly into two parts: training/test (80%) and validation (20%). For training/test, we applied a 5-fold cross-validation, repeated 2 times. With this subset, we performed the tuning of free parameters for each algorithm. For all metrics, the best performance in training/test was observed for AdaBoost. The Naïve Bayes ML resulted to be more efficient in validation approach. The logistic and rpart algorithms showed similar metric values for the training/test and validation approaches. These results are encouraging and indicate that the ML algorithms can improve the evaluation of pretest probability of stress-induced myocardial ischemia.
Published: 2021

45. Risk of primary breast cancer in patients with differentiated thyroid cancer undergoing radioactive iodine therapy: a systematic review and meta-analysis

Author: Mario Petretta, Fabio Volpe, Simone Maurea, Michele Klain, Roberta Green, Leandra Piscopo, Alberto Cuocolo, Carmela Nappi, Valeria Cantoni, Nappi, Carmela, Klain, Michele, Cantoni, Valeria, Green, Roberta, Piscopo, Leandra, Volpe, Fabio, Maurea, Simone, Petretta, Mario, and Cuocolo, Alberto
Subjects: Oncology, medicine.medical_specialty, business.industry, Breast Neoplasms, Neoplasms, Second Primary, General Medicine, Adenocarcinoma, medicine.disease, Malignancy, Confidence interval, Iodine Radioisotopes, Breast cancer, hemic and lymphatic diseases, Relative risk, Internal medicine, Meta-analysis, Medicine, Humans, Radiology, Nuclear Medicine and imaging, In patient, Female, Thyroid Neoplasms, business, Primary breast cancer, Thyroid cancer
Abstract: Purpose: Although it has been proven that radioactive iodine (RAI) treatment is an effective and well-tolerated procedure in patients with differentiated thyroid cancer (DTC), there is still some concern regarding the risk of developing a second primary malignancy after RAI administration. We performed a systematic review and meta-analysis to investigate the risk of primary breast cancer in patients with DTC undergoing RAI therapy. Methods: A comprehensive literature search of the PubMed, Scopus, and Web of Science databases was conducted according to the PRISMA statement. Results: The final analysis included 14 studies accounting for a total of 200,247 patients with DTC (98,368 treated with RAI and 101,879 not treated with RAI). The relative risk of primary breast cancer in patients with DTC treated with RAI to those not treated with RAI among studies ranged from 0.45 to 2.55, the pooled relative risk was 0.83 (95% confidence interval, 0.70–0.99), and the heterogeneity was 71.5%. Conclusion: The present meta-analysis indicates that patients with DTC treated with RAI do not have a higher risk of primary breast cancer compared to those not treated with RAI. These findings suggest that RAI therapy does not increase the risk of breast cancer.
Published: 2021

46. Whole-Body Radioiodine Effective Half-Life in Patients with Differentiated Thyroid Cancer

Author: D. Bianco, Mariarosaria Manganelli, Michele Klain, Martin Schlumberger, Elisa Caiazzo, Alberto Cuocolo, Marina De Risi, Carmela Nappi, Leandra Piscopo, Fabio Volpe, Klain, Michele, Nappi, Carmela, De Risi, Marina, Piscopo, Leandra, Volpe, Fabio, Manganelli, Mariarosaria, Caiazzo, Elisa, Bianco, Davide, Schlumberger, Martin, and Cuocolo, Alberto
Subjects: Total thyroidectomy, medicine.medical_specialty, Medicine (General), business.industry, iodine, medicine.medical_treatment, Clinical Biochemistry, radionuclide therapy, Disease, medicine.disease, Article, R5-920, Internal medicine, Radionuclide therapy, medicine, thyroid cancer, In patient, Whole body, business, Effective half-life, Adjuvant, Thyroid cancer
Abstract: Background: Radioactive 131I (RAI) therapy is used in patients with differentiated thyroid cancer (DTC) after total thyroidectomy for remnant ablation, adjuvant treatment or treatment of persistent disease. 131I retention data, which are used to indicate the time at which a 131I treated DTC patient can be released from the hospital, may bring some insights regarding clinical factors that prolong the length of hospitalization. The aim of this study was to investigate the 131I whole-body retention in DTC patients during 131I therapy. Methods: We monitored 166 DTC patients to follow the 131I whole-body retention during 131I therapy with a radioactivity detector fixed on the ceiling of each protected room. A linear regression fit permitted us to estimate the whole-body 131I effective half-life in each patient, and a relationship was sought between patients’ clinical characteristics and whole-body effective 131I half-life. Results: The effective 131I half-life ranged from 4.08 to 56.4 h. At multivariable analysis, longer effective 131I half-life was related to older age and extensive extra-thyroid disease. Conclusions: 131I effective half-life during 131I treatment in DTC patients is highly variable among patients and is significantly longer in older and in patients with RAI uptake in large thyroid remnants or in extrathyroidal disease that significantly prolongs the whole-body retention of 131I.
Published: 2021
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47. Impact of COVID-19 on Cardiovascular Testing in the United States Versus the Rest of the World

Author: Hirschfeld, Cole B., Shaw, Leslee J., Williams, Michelle C., Lahey, Ryan, Villines, Todd C., Dorbala, Sharmila, Choi, Andrew D., Shah, Nishant R., Bluemke, David A., Berman, Daniel S., Blankstein, Ron, Ferencik, Maros, Narula, Jagat, Winchester, David, Malkovskiy, Eli, Goebel, Benjamin, Randazzo, Michael J., Lopez-Mattei, Juan, Parwani, Purvi, Vitola, Joao V., Cerci, Rodrigo J., Better, Nathan, Raggi, Paolo, Lu, Bin, Sergienko, Vladimir, Sinitsyn, Valentin, Kudo, Takashi, Nørgaard, Bjarne Linde, Maurovich-Horvat, Pál, Cohen, Yosef A., Pascual, Thomas N. B., Pynda, Yaroslav, Dondi, Maurizio, Paez, Diana, Einstein, Andrew J., Cerci, Rodrigo, Hinterleitner, Gerd, Lu, Yao, Morozova, Olga, Xu, Zhuoran, Cohen, Yosef, Randazzo, Michael, Choi, Andrew, Nasery, Mohammad Nawaz, Goda, Artan, Shirka, Ervina, Benlabgaa, Rabie, Bouyoucef, Salah, Medjahedi, Abdelkader, Nailli, Qais, Agolti, Mariela, Aguero, Roberto Nicolas, Alak, Maria del Carmen, Alberguina, Lucia Graciela, Arroñada, Guillermo, Astesiano, Andrea, Astesiano, Alfredo, Norton, Carolina Bas, Benteo, Pablo, Blanco, Juan, Bonelli, Juan Manuel, Bustos, Jose Javier, Cabrejas, Raul, Cachero, Jorge, Campisi, Roxana, Canderoli, Alejandro, Carames, Silvia, Carrascosa, Patrícia, Castro, Ricardo, Cendoya, Oscar, Cognigni, Luciano Martin, Collaud, Carlos, Cortes, Claudia, Courtis, Javier, Cragnolino, Daniel, Daicz, Mariana, De La Vega, Alejandro, De Maria, Silvia Teresa, Del Riego, Horacio, Dettori, Fernando, Deviggiano, Alejandro, Dragonetti, Laura, Embon, Mario, Enriquez, Ruben Emilio, Ensinas, Jorge, Faccio, Fernando, Facello, Adolfo, Garofalo, Diego, Geronazzo, Ricardo, Gonza, Natalia, Gutierrez, Lucas, Guzzo, Miguel Angel, Hasbani, Victor, Huerin, Melina, Jäger, Victor, Lewkowicz, Julio Manuel, Nieves A López De Munaín, Maria, Lotti, Jose Maria, Marquez, Alejandra, Masoli, Osvaldo, Masoli, Osvaldo Horacio, Mastrovito, Edgardo, Mayoraz, Matias, Melado, Graciela Eva, Mele, Anibal, Merani, Maria Fernanda, Meretta, Alejandro Horacio, Molteni, Susana, Montecinos, Marcos, Noguera, Eduardo, Novoa, Carlos, Sueldo, Claudio Pereyra, Ascani, Sebastian Perez, Pollono, Pablo, Pujol, Maria Paula, Radzinschi, Alejandro, Raimondi, Gustavo, Redruello, Marcela, Rodríguez, Marina, Rodríguez, Matías, Romero, Romina Lorena, Acuña, Arturo Romero, Rovaletti, Federico, San Miguel, Lucas, Solari, Lucrecia, Strada, Bruno, Traverso, Sonia, Traverzo, Sonia Simona, Espeche, Maria del Huerto Velazquez, Weihmuller, Juan Sebastian, Wolcan, Juan, Zeffiro, Susana, Sakanyan, Mari, Beuzeville, Scott, Boktor, Raef, Butler, Patrick, Calcott, Jennifer, Carr, Loretta, Chan, Virgil, Chao, Charles, Chong, Woon, Dobson, Mark, Downie, D'Arne, Dwivedi, Girish, Elison, Barry, Engela, Jean, Francis, Roslyn, Gaikwad, Anand, Basavaraj, Ashok Gangasandra, Goodwin, Bruce, Greenough, Robert, Hamilton-Craig, Christian, Hsieh, Victar, Joshi, Subodh, Lederer, Karin, Lee, Kenneth, Lee, Joseph, Magnussen, John, Mai, Nghi, Mander, Gordon, Murton, Fiona, Nandurkar, Dee, Neill, Johanne, O'Rourke, Edward, O'Sullivan, Patricia, Pandos, George, Pathmaraj, Kunthi, Pitman, Alexander, Poulter, Rohan, Premaratne, Manuja, Prior, David, Ridley, Lloyd, Rutherford, Natalie, Salehi, Hamid, Saunders, Connor, Scarlett, Luke, Seneviratne, Sujith, Shetty, Deepa, Shrestha, Ganesh, Shulman, Jonathan, Solanki, Vijay, Stanton, Tony, Stuart, Murch, Stubbs, Michael, Swainson, Ian, Taubman, Kim, Taylor, Andrew, Thomas, Paul, Unger, Steven, Upton, Anthony, Vamadevan, Shankar, Van Gaal, William, Verjans, Johan, Voutnis, Demetrius, Wayne, Victor, Wilson, Peter, Wong, David, Wong, Kirby, Younger, John, Feuchtner, Gudrun, Mirzaei, Siroos, Weiss, Konrad, Maroz-Vadalazhskaya, Natallia, Gheysens, Olivier, Homans, Filip, Moreno-Reyes, Rodrigo, Pasquet, Agnès, Roelants, Veronique, Van De Heyning, Caroline M., Ríos, Raúl Araujo, Soldat-Stankovic, Valentina, Stankovic, Sinisa, Albernaz Siqueira, Maria Helena, Almeida, Augusto, Alves Togni, Paulo Henrique, Andrade, Jose Henrique, Andrade, Luciana, Anselmi, Carlos, Araújo, Roberta, Azevedo, Guilherme, Bezerra, Sabbrina, Biancardi, Rodrigo, Grossman, Gabriel Blacher, Brandão, Simone, Pianta, Diego Bromfman, Carreira, Lara, Castro, Bruno, Chang, Tien, Cunali, Fernando, Cury, Roberto, Dantas, Roberto, de Amorim Fernandes, Fernando, De Lorenzo, Andrea, De Macedo Filho, Robson, Erthal, Fernanda, Fernandes, Fabio, Fernandes, Juliano, De Souza, Thiago Ferreira, Alves, Wilson Furlan, Ghini, Bruno, Goncalves, Luiz, Gottlieb, Ilan, Hadlich, Marcelo, Kameoka, Vinícius, Lima, Ronaldo, Lima, 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Schoepf, U. Joseph, Shah, Samir, Shah, Nishant, Shanbhag, Sujata, Sharma, Gaurav, Shayani, Steven, Shirani, Jamshid, Shivaram, Pushpa, Sigman, Steven, Simon, Mitch, Slim, Ahmad, Smith, David, Smith, Alexandra, Soman, Prem, Sood, Aditya, Srichai-Parsia, Monvadi Barbara, Streeter, James, T, Albert, Tawakol, Ahmed, Thomas, Dustin, Thompson, Randall, Torbet, Tara, Trinidad, Desiree, Ullery, Shawn, Unzek, Samuel, Uretsky, Seth, Vallurupalli, Srikanth, Verma, Vikas, Waller, Alfonso, Wang, Ellen, Ward, Parker, Weissman, Gaby, Wesbey, George, White, Kelly, Wolinsky, David, Yost, Sandra, Zgaljardic, Michael, Alonso, Omar, Beretta, Mario, Ferrando, Rodolfo, Kapitan, Miguel, Mut, Fernando, Djuraev, Omoa, Rozikhodjaeva, Gulnora, Le Ngoc, Ha, Mai, Son Hong, Nguyen, Xuan Canh, Hirschfeld, Cole B., Shaw, Leslee J., Williams, Michelle C., Lahey, Ryan, Villines, Todd C., Dorbala, Sharmila, Choi, Andrew D., Shah, Nishant R., Bluemke, David A., Berman, Daniel S., Blankstein, Ron, Ferencik, Maro, Narula, Jagat, Winchester, David, Malkovskiy, Eli, Goebel, Benjamin, Randazzo, Michael J., Lopez-Mattei, Juan, Parwani, Purvi, Vitola, Joao V., Cerci, Rodrigo J., Better, Nathan, Raggi, Paolo, Lu, Bin, Sergienko, Vladimir, Sinitsyn, Valentin, Kudo, Takashi, Nørgaard, Bjarne Linde, Maurovich-Horvat, Pál, Cohen, Yosef A., Pascual, Thomas N. B., Pynda, Yaroslav, Dondi, Maurizio, Paez, Diana, Einstein, Andrew J., Cerci, Rodrigo, Hinterleitner, Gerd, Lu, Yao, Morozova, Olga, Xu, Zhuoran, Cohen, Yosef, Randazzo, Michael, Choi, Andrew, Nasery, Mohammad Nawaz, Goda, Artan, Shirka, Ervina, Benlabgaa, Rabie, Bouyoucef, Salah, Medjahedi, Abdelkader, Nailli, Qai, Agolti, Mariela, Aguero, Roberto Nicola, Alak, Maria del Carmen, Alberguina, Lucia Graciela, Arroñada, Guillermo, Astesiano, Andrea, Astesiano, Alfredo, Norton, Carolina Ba, Benteo, Pablo, Blanco, Juan, Bonelli, Juan Manuel, Bustos, Jose Javier, Cabrejas, Raul, Cachero, Jorge, Campisi, Roxana, Canderoli, Alejandro, Carames, Silvia, Carrascosa, Patrícia, Castro, Ricardo, Cendoya, Oscar, Cognigni, Luciano Martin, Collaud, Carlo, Cortes, Claudia, Courtis, Javier, Cragnolino, Daniel, Daicz, Mariana, De La Vega, Alejandro, De Maria, Silvia Teresa, Del Riego, Horacio, Dettori, Fernando, Deviggiano, Alejandro, Dragonetti, Laura, Embon, Mario, Enriquez, Ruben Emilio, Ensinas, Jorge, Faccio, Fernando, Facello, Adolfo, Garofalo, Diego, Geronazzo, Ricardo, Gonza, Natalia, Gutierrez, Luca, Guzzo, Miguel Angel, Hasbani, Victor, Huerin, Melina, Jäger, Victor, Lewkowicz, Julio Manuel, Nieves A López De Munaín, Maria, Lotti, Jose Maria, Marquez, Alejandra, Masoli, Osvaldo, Masoli, Osvaldo Horacio, Mastrovito, Edgardo, Mayoraz, Matia, Melado, Graciela Eva, Mele, Anibal, Merani, Maria Fernanda, Meretta, Alejandro Horacio, Molteni, Susana, Montecinos, Marco, Noguera, Eduardo, Novoa, Carlo, Sueldo, Claudio Pereyra, Ascani, Sebastian Perez, Pollono, Pablo, Pujol, Maria Paula, Radzinschi, Alejandro, Raimondi, Gustavo, Redruello, Marcela, Rodríguez, Marina, Rodríguez, Matía, Romero, Romina Lorena, Acuña, Arturo Romero, Rovaletti, Federico, San Miguel, Luca, Solari, Lucrecia, Strada, Bruno, Traverso, Sonia, Traverzo, Sonia Simona, Espeche, Maria del Huerto Velazquez, Weihmuller, Juan Sebastian, Wolcan, Juan, Zeffiro, Susana, Sakanyan, Mari, Beuzeville, Scott, Boktor, Raef, Butler, Patrick, Calcott, Jennifer, Carr, Loretta, Chan, Virgil, Chao, Charle, Chong, Woon, Dobson, Mark, Downie, D'Arne, Dwivedi, Girish, Elison, Barry, Engela, Jean, Francis, Roslyn, Gaikwad, Anand, Basavaraj, Ashok Gangasandra, Goodwin, Bruce, Greenough, Robert, Hamilton-Craig, Christian, Hsieh, Victar, Joshi, Subodh, Lederer, Karin, Lee, Kenneth, Lee, Joseph, Magnussen, John, Mai, Nghi, Mander, Gordon, Murton, Fiona, Nandurkar, Dee, Neill, Johanne, O'Rourke, Edward, O'Sullivan, Patricia, Pandos, George, Pathmaraj, Kunthi, Pitman, Alexander, Poulter, Rohan, Premaratne, Manuja, Prior, David, Ridley, Lloyd, Rutherford, Natalie, Salehi, Hamid, Saunders, Connor, Scarlett, Luke, Seneviratne, Sujith, Shetty, Deepa, Shrestha, Ganesh, Shulman, Jonathan, Solanki, Vijay, Stanton, Tony, Stuart, Murch, Stubbs, Michael, Swainson, Ian, Taubman, Kim, Taylor, Andrew, Thomas, Paul, Unger, Steven, Upton, Anthony, Vamadevan, Shankar, Van Gaal, William, Verjans, Johan, Voutnis, Demetriu, Wayne, Victor, Wilson, Peter, Wong, David, Wong, Kirby, Younger, John, Feuchtner, Gudrun, Mirzaei, Siroo, Weiss, Konrad, Maroz-Vadalazhskaya, Natallia, Gheysens, Olivier, Homans, Filip, Moreno-Reyes, Rodrigo, Pasquet, Agnè, Roelants, Veronique, Van De Heyning, Caroline M., Ríos, Raúl Araujo, Soldat-Stankovic, Valentina, Stankovic, Sinisa, Albernaz Siqueira, Maria Helena, Almeida, Augusto, Alves Togni, Paulo Henrique, Andrade, Jose Henrique, Andrade, Luciana, Anselmi, Carlo, Araújo, Roberta, Azevedo, Guilherme, Bezerra, Sabbrina, Biancardi, Rodrigo, Grossman, Gabriel Blacher, Brandão, Simone, Pianta, Diego Bromfman, Carreira, Lara, Castro, Bruno, Chang, Tien, Cunali, Fernando, Cury, Roberto, Dantas, Roberto, de Amorim Fernandes, Fernando, De Lorenzo, Andrea, De Macedo Filho, Robson, Erthal, Fernanda, Fernandes, Fabio, Fernandes, Juliano, De Souza, Thiago Ferreira, Alves, Wilson Furlan, Ghini, Bruno, Goncalves, Luiz, Gottlieb, Ilan, Hadlich, Marcelo, Kameoka, Viníciu, Lima, Ronaldo, Lima, Adna, Lopes, Rafael Willain, Machado e Silva, Ricardo, Magalhães, Tiago, Silva, Fábio Martin, Mastrocola, Luiz Eduardo, Medeiros, Fábio, Meneghetti, José Claudio, Naue, Vania, Naves, Danilo, Nolasco, Roberto, Nomura, Cesar, Oliveira, Joao Bruno, Paixao, Eduardo, De Carvalho, Filipe Penna, Pinto, Ibraim, Possetti, Priscila, Quinta, Mayra, Nogueira Ramos, Rodrigo Rizzo, Rocha, Ricardo, Rodrigues, Alfredo, Rodrigues, Carlo, Romantini, Leila, Sanches, Adelina, Santana, Sara, Sara da Silva, Leonardo, Schvartzman, Paulo, Matushita, Cristina Sebastião, Senra, Tiago, Shiozaki, Afonso, Menezes de Siqueira, Maria Eduarda, Siqueira, Cristiano, Smanio, Paola, Soares, Carlos Eduardo, Junior, José Soare, Bittencourt, Marcio Sommer, Spiro, Bernardo, Mesquita, Cláudio Tinoco, Torreao, Jorge, Torres, Rafael, Uellendahl, Marly, Monte, Guilherme Urpia, Veríssimo, Otávia, Cabeda, Estevan Vieira, Pedras, Felipe Villela, Waltrick, Roberto, Zapparoli, Marcello, Naseer, Hamid, Garcheva-Tsacheva, Marina, Kostadinova, Irena, Theng, Youdaline, Abikhzer, Gad, Barette, Rene, Chow, Benjamin, Dabreo, Dominique, Friedrich, Matthia, Garg, Ria, Hafez, Mohammed Nassoh, Johnson, Chri, Kiess, Marla, Leipsic, Jonathon, Leung, Eugene, Miller, Robert, Oikonomou, Anastasia, Probst, Stephan, Roifman, Idan, Small, Gary, Tandon, Vika, Trivedi, Adwait, White, Jame, Zukotynski, Katherine, Canessa, Jose, Muñoz, Gabriel Castro, Concha, Carmen, Hidalgo, Pablo, Lovera, Cesar, Massardo, Teresa, Vargas, Luis Salazar, Abad, Pedro, Arturo, Harold, Ayala, Sandra, Benitez, Lui, Cadena, Alberto, Caicedo, Carlo, Moncayo, Antonio Calderón, Gomez, Sharon, Gutierrez Villamil, Claudia T., Jaimes, Claudia, Londoño, Juan, Londoño Blair, Juan Lui, Pabon, Luz, Pineda, Mauricio, Rojas, Juan Carlo, Ruiz, Diego, Escobar, Manuel Valencia, Vasquez, Andre, Vergel, Damiana, Zuluaga, Alejandro, Gamboa, Isabel Berrocal, Castro, Gabriel, González, Ulise, Baric, Ana, Batinic, Tonci, Franceschi, Maja, Paar, Maja Hrabak, Jukic, Mladen, Medakovic, Petar, Persic, Viktor, Prpic, Marina, Punda, Ante, Batista, Juan Felipe, Gómez Lauchy, Juan Manuel, Gutierrez, Yamile Marco, Menéndez, Rayner, Peix, Amalia, Rochela, Lui, Panagidis, Christoforo, Petrou, Ioanni, Engelmann, Vaclav, Kaminek, Milan, Kincl, Vladimír, Lang, Otto, Simanek, Milan, Abdulla, Jawdat, Bøttcher, Morten, Christensen, Mette, Gormsen, Lars Christian, Hasbak, Philip, Hess, Søren, Holdgaard, Paw, Johansen, Allan, Kyhl, Kasper, Norgaard, Bjarne Linde, Øvrehus, Kristian Altern, Rønnow Sand, Niels Peter, Steffensen, Rolf, Thomassen, Ander, Zerahn, Bo, Perez, Alfredo, Escorza Velez, Giovanni Alejandro, Velez, Mayra Sanchez, Abdel Aziz, Islam Shawky, Abougabal, Mahasen, Ahmed, Taghreed, Allam, Adel, Asfour, Ahmed, Hassan, Mona, Hassan, Alia, Ibrahim, Ahmed, Kaffas, Sameh, Kandeel, Ahmed, Ali, Mohamed Mandour, Mansy, Ahmad, Maurice, Hany, Nabil, Sherif, Shaaban, Mahmoud, Flores, Ana Camila, Poksi, Anne, Knuuti, Juhani, Kokkonen, Velipekka, Larikka, Martti, Uusitalo, Valtteri, Bailly, Matthieu, Burg, Samuel, Deux, Jean-Françoi, Habouzit, Vincent, Hyafil, Fabien, Lairez, Olivier, Proffit, Franck, Regaieg, Hamza, Sarda-Mantel, Laure, Tacher, Vania, Schneider, Roman P., Ayetey, Harold, Angelidis, George, Archontaki, Aikaterini, Chatziioannou, Sofia, Datseris, Ioanni, Fragkaki, Christina, Georgoulias, Panagioti, Koukouraki, Sophia, Koutelou, Maria, Kyrozi, Eleni, Repasos, Evangelo, Stavrou, Petro, Valsamaki, Pipitsa, Gonzalez, Carla, Gutierrez, Goleat, Maldonado, Alejandro, Buga, Klara, Garai, Ildiko, Schmidt, Erzsébet, Szilveszter, Balint, Várady, Edit, Banthia, Nilesh, Bhagat, Jinendra Kumar, Bhargava, Rishi, Bhat, Vivek, Bhatia, Mona, Choudhury, Partha, Chowdekar, Vijay Sai, Irodi, Aparna, Jain, Shashank, Joseph, Elizabeth, Kumar, Sukriti, Girijanandan Mahapatra, Prof Dr, Mitra, Deepanjan, Mittal, Bhagwant Rai, Ozair, Ahmad, Patel, Chetan, Patel, Tapan, Patel, Ravi, Patel, Shivani, Saxena, Sudhir, Sengupta, Shantanu, Singh, Santosh, Singh, Bhanupriya, Sood, Ashwani, Verma, Atul, Affandi, Erwin, Alam, Edison, Padma, Savenadia, Gunawan, Gani, Hapkido, Habusari, Hidayat, Basuki, Huda, Aulia, Mukti, Anggoro Praja, Prawiro, Djoko, Soeriadi, Erwin Affandi, Syawaluddin, Hilman, Albadr, Amjed, Assadi, Majid, Emami, Farshad, Houshmand, Golnaz, Maleki, Majid, Rostami, Maryam Tajik, Zakavi, Seyed Rasoul, Zaid, Eed Abu, Agranovich, Svetlana, Arnson, Yoav, Bar-Shalom, Rachel, Frenkel, Alex, Knafo, Galit, Lugassi, Rachel, Maor Moalem, Israel Shlomo, Mor, Maya, Muskal, Noam, Ranser, Sara, Shalev, Aryeh, Albano, Domenico, Alongi, Pierpaolo, Arnone, Gaspare, Bagatin, Elisa, Baldari, Sergio, Bauckneht, Matteo, Bertelli, Paolo, Bianco, Francesco, Bonfiglioli, Rachele, Boni, Roberto, Bruno, Andrea, Bruno, Isabella, Busnardo, Elena, Califaretti, Elena, Camoni, Luca, Carnevale, Aldo, Casoni, Roberta, Cavallo, Armando Ugo, Cavenaghi, Giorgio, Chierichetti, Franca, Chiocchi, Marcello, Cittanti, Corrado, Colletta, Mauro, Conti, Umberto, Cossu, Alberto, Cuocolo, Alberto, Cuzzocrea, Marco, De Rimini, Maria Luisa, De Vincentis, Giuseppe, Del Giudice, Eleonora, Del Torto, Alberico, Della Tommasina, Veronica, Durmo, Rexhep, Erba, Paola Anna, Evangelista, Laura, Faletti, Riccardo, Faragasso, Evelina, Farsad, Mohsen, Ferro, Paola, Florimonte, Luigia, Frantellizzi, Viviana, Fringuelli, Fabio Massimo, Gatti, Marco, Gaudiano, Angela, Gimelli, Alessia, Giubbini, Raffaele, Giuffrida, Francesca, Ialuna, Salvatore, Laudicella, Riccardo, Leccisotti, Lucia, Leva, Lucia, Liga, Riccardo, Liguori, Carlo, Longo, Giampiero, Maffione, Margherita, Mancini, Maria Elisabetta, Marcassa, Claudio, Milan, Elisa, Nardi, Barbara, Pacella, Sara, Pepe, Giovanna, Pontone, Gianluca, Pulizzi, Sabina, Quartuccio, Natale, Rampin, Lucia, Ricci, Fabrizio, Rossini, Pierluigi, Rubini, Giuseppe, Russo, Vincenzo, Sacchetti, Gian Mauro, Sambuceti, Gianmario, Scarano, Massimo, Sciagrà, Roberto, Sperandio, Massimiliano, Stefanelli, Antonella, Ventroni, Guido, Zoboli, Stefania, Baugh, Dainia, Chambers, Duane, Madu, Ernest, Nunura, Felix, Asano, Hiroshi, Chimura, Chimura Misato, Fujimoto, Shinichiro, Fujisue, Koichiro, Fukunaga, Tomohisa, Fukushima, Yoshimitsu, Fukuyama, Kae, Hashimoto, Jun, Ichikawa, Yasutaka, Iguchi, Nobuo, Imai, Masamichi, Inaki, Anri, Ishimura, Hayato, Isobe, Satoshi, Kadokami, Toshiaki, Kato, Takao, Kumita, Shinichiro, Maruno, Hirotaka, Mataki, Hiroyuki, Miyagawa, Masao, Morimoto, Ryota, Moroi, Masao, Nagamachi, Shigeki, Nakajima, Kenichi, Nakata, Tomoaki, Nakazato, Ryo, Nanasato, Mamoru, Naya, Masanao, Norikane, Takashi, Ohta, Yasutoshi, Okayama, Satoshi, Okizaki, Atsutaka, Otomi, Yoichi, Otsuka, Hideki, Saito, Masaki, Sakata, Sakata Yasushi, Sarai, Masayoshi, Sato, Daisuke, Shiraishi, Shinya, Suwa, Yoshinobu, Takanami, Kentaro, Takehana, Kazuya, Taki, Junichi, Tamaki, Nagara, Taniguchi, Yasuyo, Teragawa, Hiroki, Tomizawa, Nobuo, Tsujita, Kenichi, Umeji, Kyoko, Wakabayashi, Yasushi, Yamada, Shinichiro, Yamazaki, Shinya, Yoneyama, Tatsuya, Rawashdeh, Mohammad, Batyrkhanov, Daultai, Dautov, Tairkhan, Makhdomi, Khalid, Ombati, Kevin, Alkandari, Faridah, Garashi, Masoud, Coie, Tchoyoson Lim, Rajvong, Sonexay, Kalinin, Artem, Kalnina, Marika, Haidar, Mohamad, Komiagiene, Renata, Kviecinskiene, Giedre, Mataciunas, Mindauga, Vajauskas, Donata, Picard, Christian, Karim, Noor Khairiah A., Reichmuth, Luise, Samuel, Anthony, Allarakha, Mohammad Aaftaab, Naojee, Ambedhkar Shantaram, Alexanderson-Rosas, Erick, Barragan, Erika, González-Montecinos, Alejandro Becerril, Cabada, Manuel, Rodriguez, Daniel Calderon, Carvajal-Juarez, Isabel, Cortés, Violeta, Cortés, Filiberto, De La Peña, Erasmo, Gama-Moreno, Manlio, González, Lui, Ramírez, Nelsy Gonzalez, Jiménez-Santos, Moisé, Matos, Lui, Monroy, Edgar, Morelos, Martha, Ornelas, Mario, Ortga Ramirez, Jose Alberto, Preciado-Anaya, André, Preciado-Gutiérrez, Óscar Ulise, Barragan, Adriana Puente, Rosales Uvera, Sandra Graciela, Sandoval, Sigelinda, Tomas, Miguel Santaularia, Sierra-Galan, Lilia M., Siu, Silvia, Vallejo, Enrique, Valles, Mario, Faraggi, Marc, Sereegotov, Erdenechimeg, Ilic, Srdja, Ben-Rais, Nozha, Alaoui, Nadia Ismaili, Taleb, Sara, Myo, Khin Pa, Thu, Phyo Si, Ghimire, Ram Kumar, Rajbanshi, Bijoy, Barneveld, Peter, Glaudemans, Andor, Habets, Jesse, Koopmans, Klaas Pieter, Manders, Jeroen, Pool, Stefan, Scholte, Arthur, Scholtens, Asbjørn, Slart, Riemer, Thimister, Paul, Van Asperen, Erik-Jan, Veltman, Niel, Verschure, Derk, Wagenaar, Nil, Edmond, John, Ellis, Chri, Johnson, Kerryanne, Keenan, Ro, Hua, Shaw, Occleshaw, Christopher, Sasse, Alexander, To, Andrew, Van Pelt, Niel, Young, Calum, Cuadra, Teresa, Roque Vanegas, Hector Bladimir, Soli, Idrissa Adamou, Issoufou, Djibrillou Moussa, Ayodele, Tolulope, Madu, Chibuzo, Onimode, Yetunde, Efros-Monsen, Elen, Forsdahl, Signe Helene, Hildre Dimmen, Jenni-Mari, Jørgensen, Arve, Krohn, Isabel, Løvhaugen, Pål, Bråten, Anders Tjellaug, Al Dhuhli, Humoud, Al Kindi, Faiza, Al-Bulushi, Naeema, Jawa, Zabah, Tag, Naima, Afzal, Muhammad Shehzad, Fatima, Shazia, Younis, Muhammad Numair, Riaz, Musab, Saadullah, Mohammad, Herrera, Yariela, Lenturut-Katal, Dora, Vázquez, Manuel Castillo, Ortellado, José, Akhter, Afroza, Cao, Dianbo, Cheung, Stephen, Dai, Xu, Gong, Lianggeng, Han, Dan, Hou, Yang, Li, Caiying, Li, Tao, Li, Dong, Li, Sijin, Liu, Jinkang, Liu, Hui, Ng, Ming Yen, Sun, Kai, Tang, Gongshun, Wang, Jian, Wang, Ximing, Wang, Zhao-Qian, Wang, Yining, Wang, Yifan, Wu, Jiang, Wu, Zhifang, Xia, Liming, Xiao, Jiangxi, Xu, Lei, Yang, Youyou, Yin, Wu, Yu, Jianqun, Yuan, Li, Zhang, Tong, Zhang, Longjiang, Zhang, Yong-Gao, Zhang, Xiaoli, Zhu, Li, Alfaro, Ana, Abrihan, Paz, Barroso, Asela, Cruz, Eric, Gomez, Marie Rhiamar, Magboo, Vincent Peter, Medina, John Michael, Obaldo, Jerry, Pastrana, Davidson, Pawhay, Christian Michael, Quinon, Alvin, Tang, Jeanelle Margareth, Tecson, Bettina, Uson, Kristine Joy, Uy, Mila, Kostkiewicz, Magdalena, Kunikowska, Jolanta, Bettencourt, Nuno, Cantinho, Guilhermina, Ferreira, Antonio, Syed, Ghulam, Arnous, Samer, Atyani, Said, Byrne, Angela, Gleeson, Tadhg, Kerins, David, Meehan, Conor, Murphy, David, Murphy, Mark, Murray, John, O'Brien, Julie, Bang, Ji-In, Bom, Henry, Cho, Sang-Geon, Hong, Chae Moon, Jang, Su Jin, Jeong, Yong Hyu, Kang, Won Jun, Kim, Ji-Young, Lee, Jaetae, Namgung, Chang Kyeong, So, Young, Won, Kyoung Sook, Majstorov, Venjamin, Vavlukis, Marija, Salobir, Barbara Gužic, Štalc, Monika, Benedek, Theodora, Benedek, Imre, Mititelu, Raluca, Stan, Claudiu Adrian, Ansheles, Alexey, Dariy, Olga, Drozdova, Olga, Gagarina, Nina, Gulyaev, Vsevolod Milyevich, Itskovich, Irina, Karalkin, Anatoly, Kokov, Alexander, Migunova, Ekaterina, Pospelov, Viktor, Ryzhkova, Daria, Saifullina, Guzaliya, Sazonova, Svetlana, Shurupova, Irina, Trifonova, Tatjana, Ussov, Wladimir Yurievich, Vakhromeeva, Margarita, Valiullina, Nailya, Zavadovsky, Konstantin, Zhuravlev, Kirill, Alasnag, Mirvat, Okarvi, Subhani, Saranovic, Dragana Sobic, Keng, Felix, Jason See, Jia Hao, Sekar, Ramkumar, Yew, Min Sen, Vondrak, Andrej, Bejai, Shereen, Bennie, George, Bester, Ria, Engelbrecht, Gerrit, Evbuomwan, Osayande, Gongxeka, Harlem, Vuuren, Magritha Jv, Kaplan, Mitchell, Khushica, Purbhoo, Lakhi, Hoosen, Louw, Lizette, Malan, Nico, Milos, Katarina, Modiselle, Moshe, More, Stuart, Naidoo, Mathava, Scholtz, Leonie, Vangu, Mboyo, Aguadé-Bruix, Santiago, Blanco, Isabel, Cabrera, Antonio, Camarero, Alicia, Casáns-Tormo, Irene, Cuellar-Calabria, Hug, Flotats, Albert, Fuentes Cañamero, Maria Eugenia, García, María Elia, Jimenez-Heffernan, Amelia, Leta, Rubén, Diaz, Javier Lopez, Lumbreras, Lui, Marquez-Cabeza, Juan Javier, Martin, Francisco, Martinez de Alegria, Anxo, Medina, Francisco, Canal, Maria Pedrera, Peiro, Virginia, Pubul-Nuñez, Virginia, Rayo Madrid, Juan Ignacio, Rey, Cristina Rodríguez, Perez, Ricardo Ruano, Ruiz, Joaquín, Hernández, Gertrudis Sabatel, Sevilla, Ana, Zeidán, Nahla, Nanayakkara, Damayanthi, Udugama, Chandraguptha, Simonsson, Magnu, Alkadhi, Hatem, Buechel, Ronny Ralf, Burger, Peter, Ceriani, Luca, De Boeck, Bart, Gräni, Christoph, Juillet de Saint Lager Lucas, Alix, Kamani, Christel H., Kawel-Boehm, Nadine, Manka, Robert, Prior, John O., Rominger, Axel, Vallée, Jean-Paul, Khiewvan, Benjapa, Premprabha, Teerapon, Thientunyakit, Tanyaluck, Sellem, Ali, Kir, Kemal Metin, Sayman, Haluk, Sebikali, Mugisha Juliu, Muyinda, Zerida, Kmetyuk, Yaroslav, Korol, Pavlo, Mykhalchenko, Olena, Pliatsek, Volodymyr, Satyr, Maryna, Albalooshi, Batool, Ahmed Hassan, Mohamed Ismail, Anderson, Jill, Bedi, Punit, Biggans, Thoma, Bularga, Anda, Bull, Russell, Burgul, Rajesh, Carpenter, John-Paul, Coles, Duncan, Cusack, David, Deshpande, Aparna, Dougan, John, Fairbairn, Timothy, Farrugia, Alexia, Gopalan, Deepa, Gummow, Alistair, Ramkumar, Prasad Guntur, Hamilton, Mark, Harbinson, Mark, Hartley, Thoma, Hudson, Benjamin, Joshi, Nikhil, Kay, Michael, Kelion, Andrew, Khokhar, Azhar, Kitt, Jamie, Lee, Ken, Low, Chen, Mak, Sze Mun, Marousa, Ntouskou, Martin, Jon, Mcalindon, Elisa, Menezes, Leon, Morgan-Hughes, Gareth, Moss, Alastair, Murray, Anthony, Nicol, Edward, Patel, Dilip, Peebles, Charle, Pugliese, Francesca, Luis Rodrigues, Jonathan Carl, Rofe, Christopher, Sabharwal, Nikant, Schofield, Rebecca, Semple, Thoma, Sharma, Naveen, Strouhal, Peter, Subedi, Deepak, Topping, William, Tweed, Katharine, Weir-Mccall, Jonathan, Abbara, Suhny, Abbasi, Taimur, Abbott, Brian, Abohashem, Shady, Abramson, Sandra, Al-Abboud, Tarek, Al-Mallah, Mouaz, Almousalli, Omar, Ananthasubramaniam, Karthikeyan, Kumar, Mohan Ashok, Askew, Jeffrey, Attanasio, Lea, Balmer-Swain, Mallory, Bayer, Richard R., Bernheim, Adam, Bhatti, Sabha, Bieging, Erik, Bloom, Stephen, Blue, Sean, Bluemke, David, Borges, Andressa, Branch, Kelley, Bravo, Paco, Brothers, Jessica, Budoff, Matthew, Bullock-Palmer, Renée, Burandt, Angela, Burke, Floyd W., Bush, Kelvin, Candela, Candace, Capasso, Elizabeth, Cavalcante, Joao, Chang, Donald, Chatterjee, Saurav, Chatzizisis, Yianni, Cheezum, Michael, Chen, Tiffany, Chen, Jennifer, Chen, Marcu, Clarcq, Jame, Cordero, Ayreen, Crim, Matthew, Danciu, Sorin, Decter, Bruce, Dhruva, Nimish, Doherty, Neil, Doukky, Rami, Dunbar, Anjori, Duvall, William, Edwards, Rachael, Esquitin, Kerry, Farah, Husam, Fentanes, Emilio, Fisher, Daniel, Fitzpatrick, Daniel, Foster, Cameron, Fuisz, Tony, Gannon, Michael, Gastner, Lori, Gerson, Myron, Ghoshhajra, Brian, Goldberg, Alan, Goldner, Brian, Gonzalez, Jorge, Gore, Rosco, Gracia-López, Sandra, Hage, Fadi, Haider, Agha, Haider, Sofia, Hamirani, Yasmin, Hassen, Karen, Hatfield, Mallory, Hawkins, Carolyn, Hawthorne, Katie, Heath, Nichola, Hendel, Robert, Hernandez, Phillip, Hill, Gregory, Horgan, Stephen, Huffman, Jeff, Hurwitz, Lynne, Iskandrian, Ami, Janardhanan, Rajesh, Jellis, Christine, Jerome, Scott, Kalra, Dinesh, Kaviratne, Summanther, Kay, Fernando, Kelly, Faith, Khalique, Omar, Kinkhabwala, Mona, Iii, George Kinzfogl, Kircher, Jacqueline, Kirkbride, Rachael, Kontos, Michael, Kottam, Anupama, Krepp, Joseph, Layer, Jay, Lee, Steven H., Leppo, Jeffrey, Lesser, John, Leung, Steve, Lewin, Howard, Litmanovich, Diana, Liu, Yiyan, Magurany, Kathleen, Markowitz, Jeremy, Marn, Amanda, Matis, Stephen E., Mckenna, Michael, Mcrae, Tony, Mendoza, Fernando, Merhige, Michael, Min, David, Moffitt, Chanan, Moncher, Karen, Moore, Warren, Morayati, Shamil, Morris, Michael, Mossa-Basha, Mahmud, Mrsic, Zorana, Murthy, Venkatesh, Nagpal, Prashant, Napier, Kyle, Nelson, Katarina, Nijjar, Prabhjot, Osman, Medhat, Passen, Edward, Patel, Amit, Patil, Pravin, Paul, Ryan, Phillips, Lawrence, Polsani, Venkateshwar, Poludasu, Rajaram, Pomerantz, Brian, Porter, Thoma, Prentice, Ryan, Pursnani, Amit, Rabbat, Mark, Ramamurti, Suresh, Rich, Florence, Luna, Hiram Rivera, Robinson, Austin, Robles, Kim, Rodríguez, Cesar, Rorie, Mark, Rumberger, John, Russell, Raymond, Sabra, Philip, Sadler, Diego, Schemmer, Mary, Schoepf, U. Joseph, Shah, Samir, Shah, Nishant, Shanbhag, Sujata, Sharma, Gaurav, Shayani, Steven, Shirani, Jamshid, Shivaram, Pushpa, Sigman, Steven, Simon, Mitch, Slim, Ahmad, Smith, David, Smith, Alexandra, Soman, Prem, Sood, Aditya, Srichai-Parsia, Monvadi Barbara, Streeter, Jame, T, Albert, Tawakol, Ahmed, Thomas, Dustin, Thompson, Randall, Torbet, Tara, Trinidad, Desiree, Ullery, Shawn, Unzek, Samuel, Uretsky, Seth, Vallurupalli, Srikanth, Verma, Vika, Waller, Alfonso, Wang, Ellen, Ward, Parker, Weissman, Gaby, Wesbey, George, White, Kelly, Wolinsky, David, Yost, Sandra, Zgaljardic, Michael, Alonso, Omar, Beretta, Mario, Ferrando, Rodolfo, Kapitan, Miguel, Mut, Fernando, Djuraev, Omoa, Rozikhodjaeva, Gulnora, Le Ngoc, Ha, Mai, Son Hong, Nguyen, Xuan Canh, Hirschfeld, C, Shaw, L, Williams, M, Lahey, R, Villines, T, Dorbala, S, Choi, A, Shah, N, Bluemke, D, Berman, D, Blankstein, R, Ferencik, M, Narula, J, Winchester, D, Malkovskiy, E, Goebel, B, Randazzo, M, Lopez-Mattei, J, Parwani, P, Vitola, J, Cerci, R, Better, N, Raggi, P, Lu, B, Sergienko, V, Sinitsyn, V, Kudo, T, Nørgaard, B, Maurovich-Horvat, P, Cohen, Y, Pascual, T, Pynda, Y, Dondi, M, Paez, D, Einstein, A, and Erba, P
Subjects: Aging, Coronavirus disease 2019 (COVID-19), Clinical Sciences, coronavirus, Disease, 030204 cardiovascular system & hematology, Cardiorespiratory Medicine and Haematology, Cardiovascular, 030218 nuclear medicine & medical imaging, NO, 03 medical and health sciences, 0302 clinical medicine, COVID-19 Testing, Cardiovascular procedures, Predictive Value of Tests, cardiovascular disease, Clinical Research, Environmental health, INCAPS-COVID Investigators Group, Pandemic, Volume reduction, Medicine, Humans, Radiology, Nuclear Medicine and imaging, cardiovascular imaging, diagnostic cardiovascular procedure, Pandemics, business.industry, SARS-CoV-2, Prevention, COVID-19, Health Services, United States/epidemiology, United States, Invasive coronary angiography, coronaviru, Heart Disease, Good Health and Well Being, MYOCARDIAL-INFARCTION, Cardiovascular System & Hematology, Predictive value of tests, HOSPITAL ADMISSIONS, Cardiology and Cardiovascular Medicine, Early phase, business
Abstract: Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-U.S. institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection.
Published: 2021

48. Advances in Functional Imaging of Differentiated Thyroid Cancer

Author: Livia Lamartina, Martin Schlumberger, Domenico Salvatore, Emanuele Nicolai, Elena Califaretti, Raffaele Ambrosio, Alberto Cuocolo, Carmela Nappi, Désirée Deandreis, Emilia Zampella, Michele Klain, Klain, Michele, Zampella, Emilia, Nappi, Carmela, Nicolai, Emanuele, Ambrosio, Raffaele, Califaretti, Elena, Lamartina, Livia, Schlumberger, Martin, Deandreis, Désirée, Salvatore, Domenico, and Cuocolo, Alberto
Subjects: Cancer Research, medicine.medical_specialty, Radioiodine uptake, diagnosis, differentiated thyroid cancer, Review, Imaging modalities, medicine, Diagnosis, Differentiated thyroid cancer, Imaging, Radioactive iodine therapy, Theragnostic, Therapeutic intent, Thyroid cancer, RC254-282, business.industry, theragnostic, Fdg uptake, Thyroid, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, imaging, medicine.disease, radioactive iodine therapy, Functional imaging, medicine.anatomical_structure, Oncology, Radiology, Radioactive iodine, business
Abstract: Simple Summary Since the 1940s, radioactive iodine has been used for functional imaging and for treating patients with differentiated thyroid cancer (DTC). During this long-lasting experience, the use of iodine isotopes evolved, especially during the last years due to improved knowledge of thyroid cancer biology and improved performances of imaging tools. The present review summarizes recent advances in the field of functional imaging and theragnostic approach of DTC. Abstract The present review provides a description of recent advances in the field of functional imaging that takes advantage of the functional characteristics of thyroid neoplastic cells (such as radioiodine uptake and FDG uptake) and theragnostic approach of differentiated thyroid cancer (DTC). Physical and biological characteristics of available radiopharmaceuticals and their use with state-of-the-art technologies for diagnosis, treatment, and follow-up of DTC patients are depicted. Radioactive iodine is used mostly with a therapeutic intent, while PET/CT with 18F-FDG emerges as a useful tool in the diagnostic management and complements the use of radioactive iodine. Beyond 18F-FDG PET/CT, other tracers including 124I, 18F-TFB and 68Ga-PSMA, and new methods such as PET/MR, might offer new opportunities in selecting patients with DTC for specific imaging modalities or treatments.
Published: 2021

49. The Endolog technique for moderate to severe hallux valgus treatment: Clinical and radiographic analysis of 194 patients

Author: Daniela Invernizzi, Federico Bertolo, Francesco Atzori, Claudio Cuocolo, and Andrea Pautasso
Subjects: Adult, Male, Moderate to severe, medicine.medical_specialty, Radiography, Severity of Illness Index, 03 medical and health sciences, 0302 clinical medicine, Recurrence, Deformity, medicine, Humans, Orthopedics and Sports Medicine, Hallux Valgus, Aged, Retrospective Studies, Aged, 80 and over, Aofas score, 030222 orthopedics, biology, business.industry, Retrospective cohort study, 030229 sport sciences, Middle Aged, biology.organism_classification, Osteotomy, Surgery, Valgus, Treatment Outcome, Associated procedure, Radiological weapon, Female, medicine.symptom, business
Abstract: Background Endolog is an intra-medullary titanium device used for a minimally-invasive hallux valgus correction. The aim of this study was to evaluate clinical and radiographic outcomes of this device. Methods A retrospective study with a prospective data collection was conducted. Patients underwent to Endolog procedures from September 2009 to April 2017 were enrolled. Mild HV deformity (HVA ≤ 19° and IMA ≤ 13°) or associated procedure to Endolog technique were excluded. The radiological (HVA, IMA and PASA) and clinical (AOFAS score) pre and post-operative data were compared through Wilcoxon Signed-Rank test. Results 194 feet (144 moderate and 50 severe HV) underwent HV correction respecting study’s criteria. AOFAS scores significantly improved from 31.0 ± 12.7 points preoperatively to 88.5 ± 8.0 at 24 months. Even all radiographic measurements significantly improved during 2 years’ follow-up. Only 6 patients experienced complications: 4 cases of HV recurrence and 2 cases of intolerance device-related pain. Conclusions Endolog technique proved to be a valid option in the moderate-to-severe hallux valgus treatment, comparable to other surgical techniques described in literature.
Published: 2021

50. Imaging medullary thyroid cancer patients with detectable serum markers: state of the art and future perspectives

Author: Julien Hadoux, Désirée Deandreis, Domenico Salvatore, Martin Schlumberger, Carmela Nappi, Monica Finessi, Alberto Cuocolo, Michele Klain, Raffaele Ambrosio, Klain, Michele, Hadoux, Julien, Nappi, Carmela, Finessi, Monica, Ambrosio, Raffaele, Schlumberger, Martin, Cuocolo, Alberto, Deandreis, Désirée, and Salvatore, Domenico
Subjects: medicine.medical_specialty, Medullary cavity, PET/CT, Endocrinology, Diabetes and Metabolism, Disease, Medullary Thyroid Carcinoma, Imaging, Thyroid carcinoma, Endocrinology, Positron Emission Tomography Computed Tomography, medicine, Humans, Prospective Studies, Thyroid Neoplasms, Tumor marker, Ultrasonography, PET-CT, business.industry, Thyroid, Medullary thyroid cancer, medicine.disease, Carcinoma, Neuroendocrine, medicine.anatomical_structure, MTC, Radiology, business, Biomarkers, Serum markers
Abstract: Purpose: Medullary thyroid carcinoma (MTC) originates from thyroid parafollicular C-cells and represents
Published: 2021

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