Search

Purpose Studies based on machine learning-based quantitative imaging techniques have gained much interest in cancer research. The aim of this review is to critically appraise the existing machine learning-based quantitative imaging analysis studies predicting outcomes of esophageal cancer after concurrent chemoradiotherapy in accordance with PRISMA guidelines. Methods A systematic review was conducted in accordance with PRISMA guidelines. The citation search was performed via PubMed and Embase Ovid databases for literature published before April 2021. From each full-text article, study characteristics and model information were summarized. We proposed an appraisal matrix with 13 items to assess the methodological quality of each study based on recommended best-practices pertaining to quality. Results Out of 244 identified records, 37 studies met the inclusion criteria. Study endpoints included prognosis, treatment response, and toxicity after concurrent chemoradiotherapy with reported discrimination metrics in validation datasets between 0.6 and 0.9, with wide variation in quality. A total of 30 studies published within the last 5 years were evaluated for methodological quality and we found 11 studies with at least 6 "good" item ratings. Conclusion A substantial number of studies lacked prospective registration, external validation, model calibration, and support for use in clinic. To further improve the predictive power of machine learning-based models and translate into real clinical applications in cancer research, appropriate methodologies, prospective registration, and multi-institution validation are recommended.

Purpose Studies based on machine learning-based quantitative imaging techniques have gained much interest in cancer research. The aim of this review is to critically appraise the existing machine learning-based quantitative imaging analysis studies predicting outcomes of esophageal cancer after concurrent chemoradiotherapy in accordance with PRISMA guidelines. Methods A systematic review was conducted in accordance with PRISMA guidelines. The citation search was performed via PubMed and Embase Ovid databases for literature published before April 2021. From each full-text article, study characteristics and model information were summarized. We proposed an appraisal matrix with 13 items to assess the methodological quality of each study based on recommended best-practices pertaining to quality. Results Out of 244 identified records, 37 studies met the inclusion criteria. Study endpoints included prognosis, treatment response, and toxicity after concurrent chemoradiotherapy with reported discrimination metrics in validation datasets between 0.6 and 0.9, with wide variation in quality. A total of 30 studies published within the last 5 years were evaluated for methodological quality and we found 11 studies with at least 6 “good” item ratings. Conclusion A substantial number of studies lacked prospective registration, external validation, model calibration, and support for use in clinic. To further improve the predictive power of machine learning-based models and translate into real clinical applications in cancer research, appropriate methodologies, prospective registration, and multi-institution validation are recommended.

Cancer treatment is heading towards precision medicine driven by genetic and biochemical markers. Various genetic and biochemical markers are utilized to render personalized treatment in cancer. In the last decade, noninvasive imaging biomarkers have also been developed to assist personalized decision support systems in oncology. The imaging biomarkers i.e., radiomics is being researched to develop specific digital phenotype of tumor in cancer. Radiomics is a process to extract high throughput data from medical images by using advanced mathematical and statistical algorithms. The radiomics process involves various steps i.e., image generation, segmentation of region of interest (e.g. a tumor), image preprocessing, radiomic feature extraction, feature analysis and selection and finally prediction model development. Radiomics process explores the heterogeneity, irregularity and size parameters of the tumor to calculate thousands of advanced features. Our study investigates the role of radiomics in precision oncology. Radiomics research has witnessed a rapid growth in the last decade with several studies published that show the potential of radiomics in diagnosis and treatment outcome prediction in oncology. Several radiomics based prediction models have been developed and reported in the literature to predict various prediction endpoints i.e., overall survival, progression-free survival and recurrence in various cancer i.e., brain tumor, head and neck cancer, lung cancer and several other cancer types. Radiomics based digital phenotypes have shown promising results in diagnosis and treatment outcome prediction in oncology. In the coming years, radiomics is going to play a significant role in precision oncology.

This information statement from the Society of Nuclear Medicine and Molecular Imaging, American Society of Nuclear Cardiology, and European Association of Nuclear Medicine describes the performance, interpretation, and reporting of hot spot imaging in nuclear cardiology. The field of nuclear cardiology has historically focused on cold spot imaging for the interpretation of myocardial ischemia and infarction. Hot spot imaging has been an important part of nuclear medicine, particularly for oncology or infection indications, and the use of hot spot imaging in nuclear cardiology continues to expand. This document focuses on image acquisition and processing, methods of quantification, indications, protocols, and reporting of hot spot imaging. Indications discussed include myocardial viability, myocardial inflammation, device or valve infection, large vessel vasculitis, valve calcification and vulnerable plaques, and cardiac amyloidosis. This document contextualizes the foundations of image quantification and highlights reporting in each indication for the cardiac nuclear imager.

Background Machine learning studies require a large number of images often obtained on different PET scanners. When merging these images, the use of harmonized images following EARL-standards is essential. However, when including retrospective images, EARL accreditation might not have been in place. The aim of this study was to develop a convolutional neural network (CNN) that can identify retrospectively if an image is EARL compliant and if it is meeting older or newer EARL-standards. Materials and methods 96 PET images acquired on three PET/CT systems were included in the study. All images were reconstructed with the locally clinically preferred, EARL1, and EARL2 compliant reconstruction protocols. After image pre-processing, one CNN was trained to separate clinical and EARL compliant reconstructions. A second CNN was optimized to identify EARL1 and EARL2 compliant images. The accuracy of both CNNs was assessed using fivefold cross-validation. The CNNs were validated on 24 images acquired on a PET scanner not included in the training data. To assess the impact of image noise on the CNN decision, the 24 images were reconstructed with different scan durations. Results In the cross-validation, the first CNN classified all images correctly. When identifying EARL1 and EARL2 compliant images, the second CNN identified 100% EARL1 compliant and 85% EARL2 compliant images correctly. The accuracy in the independent dataset was comparable to the cross-validation accuracy. The scan duration had almost no impact on the results. Conclusion The two CNNs trained in this study can be used to retrospectively include images in a multi-center setting by, e.g., adding additional smoothing. This method is especially important for machine learning studies where the harmonization of images from different PET systems is essential.

Purpose The aim of this study was to assess and compare the arterial uptake of the inflammatory macrophage targeting PET tracer [64Cu]Cu-DOTATATE in patients with no or known cardiovascular disease (CVD) to investigate potential differences in uptake. Methods Seventy-nine patients who had undergone [64Cu]Cu-DOTATATE PET/CT imaging for neuroendocrine neoplasm disease were retrospectively allocated to three groups: controls with no known CVD risk factors (n = 22), patients with CVD risk factors (n = 24), or patients with known ischemic CVD (n = 33). Both maximum, mean of max and most-diseased segment (mds) standardized uptake value (SUV) and target-to-background ratio (TBR) uptake metrics were measured and reported for the carotid arteries and the aorta. To assess reproducibility between different reviewers, Bland–Altman plots were made. Results For the carotid arteries, SUVmax (P = .03), SUVmds (0.05), TBRmax (P mds (P P = .01) were overall shown to provide a group-wise difference in uptake. When measuring uptake values in the aorta, a group-wise difference was only observed with TBRmds (P = .04). Overall, reproducibility of the reported uptake metrics was excellent for SUVs and good to excellent for TBRs for both the carotid arteries and the aorta. Conclusion Using [64Cu]Cu-DOTATATE PET imaging as a marker of atherosclerotic inflammation, we were able to demonstrate differences in some of the most frequently reported uptake metrics in patients with different degrees of CVD. Measurements of the carotid artery as either maximum uptake values or most-diseased segment analysis showed the best ability to discriminate between the groups.

Lung cancer is the most common cancer, worldwide, and a major health issue with a remarkable mortality rate. 2-[F-18]fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (2-[F-18]FDG PET/CT) plays an indispensable role in the management of lung cancer patients. Long-established quantitative parameters such as size, density, and metabolic activity have been and are being employed in the current practice to enhance interpretation and improve diagnostic and prognostic value. The introduction of radiomics analysis revolutionized the quantitative evaluation of medical imaging, revealing data within images beyond visual interpretation. The "big data" are extracted from high-quality images and are converted into information that correlates to relevant genetic, pathologic, clinical, or prognostic features. Technically advanced, diverse methods have been implemented in different studies. The standardization of image acquisition, segmentation and features analysis is still a debated issue. Importantly, a body of features has been extracted and employed for diagnosis, staging, risk stratification, prognostication, and therapeutic response. 2-[F-18]FDG PET/CT-derived features show promising value in non-invasively diagnosing the malignant nature of pulmonary nodules, differentiating lung cancer subtypes, and predicting response to different therapies as well as survival. In this review article, we aimed to provide an overview of the technical aspects used in radiomics analysis in non-small cell lung cancer (NSCLC) and elucidate the role of 2-[F-18]FDG PET/CT-derived radiomics in the diagnosis, prognostication, and therapeutic response.

This study investigated the predictive role of baseline 18F-FDG PET/CT (bPET/CT) radiomics from two distinct target lesions in patients with classical Hodgkin’s lymphoma (cHL). cHL patients examined with bPET/CT and interim PET/CT between 2010 and 2019 were retrospectively included. Two bPET/CT target lesions were selected for radiomic feature extraction: Lesion_A, with the largest axial diameter, and Lesion_B, with the highest SUVmax. Deauville score at interim PET/CT (DS) and 24-month progression-free-survival (PFS) were recorded. Mann–Whitney test identified the most promising image features (p < 0.05) from both lesions with regards to DS and PFS; all possible radiomic bivariate models were then built through a logistic regression analysis and trained/tested with a cross-fold validation test. The best bivariate models were selected based on their mean area under curve (mAUC). A total of 227 cHL patients were included. The best models for DS prediction had 0.78 ± 0.05 maximum mAUC, with a predominant contribution of Lesion_A features to the combinations. The best models for 24-month PFS prediction reached 0.74 ± 0.12 mAUC and mainly depended on Lesion_B features. bFDG-PET/CT radiomic features from the largest and hottest lesions in patients with cHL may provide relevant information in terms of early response-to-treatment and prognosis, thus representing an earlier and stronger decision-making support for therapeutic strategies. External validations of the proposed model are planned.

Rationale: Whether assessment of potential bone lesions in metastatic breast cancer (MBC) by means of 18F-fluorodeoxyglucose (FDG)-PET instead of 99mTechnetium (99mTc) bone scintigraphy (BS) supports clinically relevant changes in MBC management, is currently unknown. Therefore, we retrospectively compared the management recommendations based on bone lesion assessment by FDG-PET plus contrast enhanced computed tomography (ceCT) or BS plus ceCT, for patients with newly diagnosed MBC. Methods: Baseline ceCT, BS and FDG-PET of all patients included in the IMPACT-MBC study (NCT01957332) at location University Medical Center Groningen (UMCG), were reviewed for bone lesions. In case of bone lesions on any imaging modality, virtual MBC management recommendations per patient were made by a multidisciplinary expert panel, based on either FDG-PET plus ceCT, or BS plus ceCT. The panel had access to standard clinicopathological information and baseline imaging findings outside the skeleton. Clinically relevant management differences between the two recommendations were defined as 1) different treatment intent, (curative, non-curative or unable to determine and/or 2) different systemic or local treatment. In case of absence of bone lesions with any imaging modality, patients were included in the analyses without expert review. Results: A total of 3,473 unequivocal bone lesions was identified in 102 evaluated patients (39% by ceCT, 26% by BS, 87% by FDG-PET). Additional bone lesions on FDG-PET plus ceCT compared to BS plus ceCT led to change of MBC management recommendations in 16% of all patients (95% confidence interval (CI) 10-24%). BS also changed management compared to FDG-PET in one patient (1%; 95%CI 0-5%). In 26% (95%CI 19-36%) of patients, an additional FDG-PET was requested, because BS provided insufficient information. Conclusion: In this exploratory analysis of newly diagnosed MBC patients, FDG-PET versus BS to assess bone lesions, resulted in clinically relevant management differences in 16% of all patients. BS delivered insufficient information in over one fourth of patients, resulting in additional request for FDG-PET. Based on this data, FDG-PET should be considered as primary imaging modality for assessment of bone lesions in newly diagnosed MBC.

Background 2-Deoxy-2-[18F]fluoroglucose (FDG) PET is an important tool for the identification of Alzheimer’s disease (AD) patients through the characteristic neurodegeneration pattern that these patients present. Regional cerebral blood flow (rCBF) images derived from dynamic 11C-labelled Pittsburgh Compound B (PIB) have been shown to present a similar pattern as FDG. Moreover, multivariate analysis techniques, such as scaled subprofile modelling using principal component analysis (SSM/PCA), can be used to generate disease-specific patterns (DP) that may aid in the classification of subjects. Therefore, the aim of this study was to compare rCBF AD-DPs with FDG AD-DP and their respective performances. Therefore, 52 subjects were included in this study. Fifteen AD and 16 healthy control subjects were used to generate four AD-DP: one based on relative cerebral trace blood (R1), two based on time-weighted average of initial frame intervals (ePIB), and one based on FDG images. Furthermore, 21 subjects diagnosed with mild cognitive impairment were tested against these AD-DPs. Results In general, the rCBF and FDG AD-DPs were characterized by a reduction in cortical frontal, temporal, and parietal lobes. FDG and rCBF methods presented similar score distribution. Conclusion rCBF images may provide an alternative for FDG PET scans for the identification of AD patients through SSM/PCA.

I-131-meta-iodobenzylguanidine (I-131-MIBG) radiotherapy has shown some survival benefits in metastatic neuroendocrine tumors (NETs). European Association of Nuclear Medicine clinical guidelines for I-131-MIBG radiotherapy suggest a repeated treatment protocol, although none currently exists. The existing single-high-dose I-131-MIBG radiotherapy (444 MBq/kg) has been shown to have some benefits for patients with metastatic NETs. However, this protocol increases adverse effects and requires alternative therapeutic approaches. Therefore, the aim of this study was to evaluate the effects of repeated I-131-MIBG therapy on tumor size and tumor metabolic response in patients with metastatic NETs. Methods: Eleven patients with metastatic NETs (aged 49.2 +/- 16.3 y) prospectively received repeated 5,550-MBq doses of I-131-MIBG therapy at 6-mo intervals. In total, 31 treatments were performed. The mean number of treatments was 2.8 0.4, and the cumulative I-131-MIBG dose was 15,640.9 + 2,245.1 MBq (286.01 MBq/kg). Tumor response was observed by CT and 18F-FDG PET or by F-18-FDG PET/CT before and 3-6 mo after the final I-131-MIBG treatment. Results: On the basis of the CT findings with RECIST, 3 pa tients showed a partial response and 6 patients showed stable disease. The remaining 2 patients showed progressive disease. Al though there were 2 progressive-disease patients, analysis of all patients showed no increase in summed length diameter (median, 228.7 mm [interquartile range (10R), 37.0-336.0 mm] to 171.0 mm [IQR, 38.0-270.0 mm]; P = 0.563). In tumor region-based analysis with par tial-response and stable-disease patients (n = 9), I-131-MIBG therapy significantly reduced tumor diameter (79 lesions; median, 16 mm [IQR, 12-22 mm] to 11 mm [10R, 6-16 mm]; P < 0.001). Among 5 patients with hypertension, there was a strong trend toward systolic blood pressure reduction (P = 0.058), and diastolic blood pressure was significantly reduced (P = 0.006). Conclusion: Eighty-two percent of metastatic NET patients effectively achieved inhibition of disease progression, with reduced tumor size and reduced metabolic activity, through repeated I-131-MIBG therapy. Therefore, this relatively short-term repeated I-131-MIBG treatment may have potential as one option in the therapeutic protocol for metastatic NETs. Larger prospective studies with control groups are warranted.

A retrospective, single-center analysis of 14 cases of Candida endocarditis (from 355 candidemia cases during the years 2012–2019) revealed a high in-hospital mortality (57.1%), a high proportion of healthcare-associated infections (13/14) and a high treatment preference for echinocandins. Transthoracic echocardiography and 18F-FDG PET/CT had a sensitivity of 54.5% and 57.1%, respectively. Patients were older than previously described and most patients with Candida endocarditis had persistent candidemia for ≥ 3 days despite antifungal therapy. Electronic supplementary material The online version of this article (10.1007/s11046-020-00492-3) contains supplementary material, which is available to authorized users.

Objective In this retrospective, single-center observational study, we investigated whether discontinuing metformin for at least 48 h prevents metformin-induced [18F]fluorodeoxyglucose (FDG) uptake in all segments of the colon. Methods Patients with type 2 diabetes who were using metformin before undergoing an FDG PET/CT scan were included. Two groups were created: patients who discontinued metformin for less than 48 h ( Results Colonic FDG uptake in the ≥ 48 h group (n = 23) was higher than uptake in the control group (n = 96) in the colon descendens [odds ratio (OR) 14.0; 95% confidence interval (CI) 4.8–40.9; p value: 0.001] and rectosigmoid (OR 11.3; 95% CI 4.0–31.9; p value: 0.001), and there was no difference in the colon ascendens and transversum. Colonic FDG uptake in the n = 25) was higher than uptake in the ≥ 48 h group (n = 23) in the colon transversum (OR 4.8; 95% CI 1.3–18.5; p value: 0.022) and rectosigmoid (p value: 0.023), and there was no difference in the colon ascendens and descendens. Conclusions Discontinuing metformin for 48 h before undergoing an FDG PET/CT still gives a high uptake in the distal parts of the colon when compared with non-diabetic patients who are not using metformin. Discontinuing metformin for 48 h seems to be useful for scanning the more proximal segments of the colon.

Several factors that influence physiologic 18F-fluorodeoxyglucose (FDG) uptake and general FDG distribution may affect PET/CT imaging in infection and inflammation. The general impact of hyperglycemia on the diagnostic performance of FDG-PET/CT is probably less in infection/inflammation than in malignancy. Patient preparation may reduce physiologic FDG uptake, but recommendations are less established than in malignancy. Local implementation of various patient preparatory measures should reflect the specific patient population and indications. This article outlines some of the challenges with physiologic FDG distribution, focusing on infectious and inflammatory diseases, and potential countermeasures and patient preparation to limit physiologic uptake before scan.

Periprosthetic joint infection (PJI) is a severe complication, associated with substantial morbidity and high costs. PJI can occur in the early postoperative period but also many years after joint replacement. Timely and accurate diagnosis is important for treatment planning. Diagnosis of PJI can be a challenge, especially for chronic and low-grade infections. The diagnostic performance of fludeoxyglucose F 18 (18F-FDG) positron emission tomography (PET) in detecting PJI seems sufficiently high for routine clinical application and has additional value to conventional tests. Further research is needed to determine the exact place of 18F-FDG PET in the diagnostic work-up of suspected PJI.

Purpose: The aim was to perform a systematic review on the value of diffusion-weighted MRI (DW-MRI) with apparent diffusion coefficient (ADC) mapping in the prediction and assessment of response to chemo- and/or radiotherapy in oesophageal cancer.Materials and methods: A systematic search was performed on Pubmed, Embase, Medline and Cochrane databases. Studies that evaluated the ADC for response evaluation before, during or after chemo- and/or radiotherapy were included. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) was used to assess the quality of the included studies.Results: Fourteen studies, comprising 516 patients, in which the response to treatment in oesophageal cancer was evaluated on ADC maps were included. Acquisition parameter settings for DW-MRI and ROI placement varied substantially. The reference standard was RECIST or endoscopic assessment in eight non-surgery studies and histopathology after surgery in six studies. A high pre-treatment ADC significantly correlated with good response in three out of 12 studies; conversely, one study reported a significantly higher pre-treatment ADC in poor responders. In five out of eight studies good responders showed a significantly larger relative increase in ADC two weeks after the onset of treatment (range 23-59%) than poor responders (range 1.5-17%). After chemo- and/or radiotherapy ADC results varied considerably, amongst others due to large variation in the interval between completion of therapy and DW-MRI.Conclusion: DW-MRI for response evaluation to chemo- and/or radiotherapy in oesophageal cancer shows variable methods and results. A large relative ADC increase after two weeks of treatment seems most predictive for good response. (C) 2019 Elsevier B.V. All rights reserved.

Background The aim of this study was to explore the feasibility of assisted diagnosis of active (peri-)aortitis using radiomic imaging biomarkers derived from [18F]-Fluorodeoxyglucose Positron Emission Tomography–Computed Tomography (FDG PET–CT) images. Methods The aorta was manually segmented on FDG PET–CT in 50 patients with aortitis and 25 controls. Radiomic features (RF) (n = 107), including SUV (Standardized Uptake Value) metrics, were extracted from the segmented data and harmonized using the ComBat technique. Individual RFs and groups of RFs (i.e., signatures) were used as input in Machine Learning classifiers. The diagnostic utility of these classifiers was evaluated with area under the receiver operating characteristic curve (AUC) and accuracy using the clinical diagnosis as the ground truth. Results Several RFs had high accuracy, 84% to 86%, and AUC scores 0.83 to 0.97 when used individually. Radiomic signatures performed similarly, AUC 0.80 to 1.00. Conclusion A methodological framework for a radiomic-based approach to support diagnosis of aortitis was outlined. Selected RFs, individually or in combination, showed similar performance to the current standard of qualitative assessment in terms of AUC for identifying active aortitis. This framework could support development of a clinical decision-making tool for a more objective and standardized assessment of aortitis.

18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) identifies carotid plaque inflammation and predicts stroke recurrence in patients with atherothrombotic stroke. The aim of the study was to identify plasma inflammatory biomarkers associated with plaque inflammation according to 18F-FDG uptake. We conducted a prospective study of consecutive adult patients with a recent (18F-FDG PET, and a blood sample was obtained at days 7 ± 1 from the stroke. The plasma concentration of 16 inflammation-related molecules was analyzed in a Luminex using xMAP technology. Multivariable linear regression was used to assess the association between plasma biomarkers and the standardized uptake value (SUV) of 18F-FDG uptake. Soluble intercellular adhesion molecule-1 (sICAM-1), soluble vascular adhesion molecule-1 (sVCAM-1), and fractalkine (FKN) were independently associated with plaque inflammation (β = 0.121, 95% CI 0.061–0.181, p β = 0.144, 95% CI 0.012–0.276, p = 0.033; β = 0.136, 95% CI 0.037–0.235, p = 0.008). In a multivariable logistic regression analysis, sICAM-1 was associated with SUVmax ≥ 2.85 (OR = 1.02, 95% CI 1.00–1.03, p = 0.020). Multivariable Cox regression was used to assess the association between biomarkers and stroke recurrence. sICAM-1 was associated with stroke recurrence (HR = 1.03, 95% CI 1.00–1.05, p = 0.002). In summary, elevated concentrations of sICAM-1 were associated with carotid plaque inflammation and an increased risk of stroke recurrence in patients with recent ischemic stroke and carotid atherosclerosis.

To confirm the diagnosis of large vessel vasculitis (LVV) with high accuracy, one of the recommended imaging techniques is [18F]Fluoro-2-deoxy-d-glucose positron emission tomography with computed tomography ([18F]FDG-PET/CT). Visual assessment of [18F]FDG uptake in the arterial wall compared to liver uptake is the mainstay for diagnosing LVV in routine clinical practice. To date, there is no consensus on the preferred semi-quantitative or quantitative parameter for diagnosing LVV. The aim of this review is to critically update the knowledge on the available evidence of semi-quantitative and quantitative [18F]FDG uptake parameters for diagnosing LVV and to provide future directions for methodological standardization and research.

Parkinson's disease (PD) commences several years before the onset of motor features. Pathophysiological understanding of the pre-clinical or early prodromal stages of PD are essential for the development of new therapeutic strategies. Two categories of patients are ideal to study the early disease stages. Idiopathic rapid eye movement sleep behavior disorder (iRBD) represents a well-known prodromal stage of PD in which pathology is presumed to have reached the lower brainstem. The majority of patients with iRBD will develop manifest PD within years to decades. Another category encompasses non-manifest mutation carriers, i.e. subjects without symptoms, but with a known mutation or genetic variant which gives an increased risk of developing PD. The speed of progression from preclinical or prodromal to full clinical stages varies among patients and cannot be reliably predicted on the individual level. Clinical trials will require inclusion of patients with a predictable conversion within a limited time window. Biomarkers are necessary that can confirm pre-motor PD status and can provide information regarding lead time and speed of progression. Neuroimaging changes occur early in the disease process and may provide such a biomarker. Studies have focused on radiotracer imaging of the dopaminergic nigrostriatal system, which can be assessed with dopamine transporter (DAT) single photon emission computed tomography (SPECT). Loss of DAT binding represents an effect of irreversible structural damage to the nigrostriatal system. This marker can be used to monitor disease progression and identify individuals at specific risk for phenoconversion. However, it is known that changes in neuronal activity precede structural changes. Functional neuro-imaging techniques, such as F-18-2-fluoro-2-deoxy-D-glucose Positron Emission Tomography (F-18-FDG PET) and functional magnetic resonance imaging (fMRI), can be used to model the effects of disease on brain networks when combined with advanced analytical methods. Because these changes occur early in the disease process, functional imaging studies are of particular interest in prodromal PD diagnosis. In addition, fMRI and F-18-FDG PET may be able to predict a specific future phenotype in prodromal cohorts, which is not possible with DAT SPECT. The goal of the current review is to discuss the network-level brain changes in pre-motor PD.

To confirm the diagnosis of large vessel vasculitis (LVV) with high accuracy, one of the recommended imaging techniques is [F-18]Fluoro-2-deoxy-d-glucose positron emission tomography with computed tomography ([F-18]FDG-PET/CT). Visual assessment of [F-18]FDG uptake in the arterial wall compared to liver uptake is the mainstay for diagnosing LVV in routine clinical practice. To date, there is no consensus on the preferred semi-quantitative or quantitative parameter for diagnosing LVV. The aim of this review is to critically update the knowledge on the available evidence of semi-quantitative and quantitative [F-18]FDG uptake parameters for diagnosing LVV and to provide future directions for methodological standardization and research.

Parkinson’s disease (PD) commences several years before the onset of motor features. Pathophysiological understanding of the pre-clinical or early prodromal stages of PD are essential for the development of new therapeutic strategies. Two categories of patients are ideal to study the early disease stages. Idiopathic rapid eye movement sleep behavior disorder (iRBD) represents a well-known prodromal stage of PD in which pathology is presumed to have reached the lower brainstem. The majority of patients with iRBD will develop manifest PD within years to decades. Another category encompasses non-manifest mutation carriers, i.e. subjects without symptoms, but with a known mutation or genetic variant which gives an increased risk of developing PD. The speed of progression from preclinical or prodromal to full clinical stages varies among patients and cannot be reliably predicted on the individual level. Clinical trials will require inclusion of patients with a predictable conversion within a limited time window. Biomarkers are necessary that can confirm pre-motor PD status and can provide information regarding lead time and speed of progression. Neuroimaging changes occur early in the disease process and may provide such a biomarker. Studies have focused on radiotracer imaging of the dopaminergic nigrostriatal system, which can be assessed with dopamine transporter (DAT) single photon emission computed tomography (SPECT). Loss of DAT binding represents an effect of irreversible structural damage to the nigrostriatal system. This marker can be used to monitor disease progression and identify individuals at specific risk for phenoconversion. However, it is known that changes in neuronal activity precede structural changes. Functional neuro-imaging techniques, such as 18F-2-fluoro-2-deoxy-D-glucose Positron Emission Tomography (18F-FDG PET) and functional magnetic resonance imaging (fMRI), can be used to model the effects of disease on brain networks when combined with advanced analytical methods. Because these changes occur early in the disease process, functional imaging studies are of particular interest in prodromal PD diagnosis. In addition, fMRI and 18F-FDG PET may be able to predict a specific future phenotype in prodromal cohorts, which is not possible with DAT SPECT. The goal of the current review is to discuss the network-level brain changes in pre-motor PD.

Rationale In Parkinson’s disease (PD), spatial covariance analysis of 18F-FDG PET data has consistently revealed a characteristic PD-related brain pattern (PDRP). By quantifying PDRP expression on a scan-by-scan basis, this technique allows objective assessment of disease activity in individual subjects. We provide a further validation of the PDRP by applying spatial covariance analysis to PD cohorts from the Netherlands (NL), Italy (IT), and Spain (SP). Methods The PDRPNL was previously identified (17 controls, 19 PD) and its expression was determined in 19 healthy controls and 20 PD patients from the Netherlands. The PDRPIT was identified in 20 controls and 20 “de-novo” PD patients from an Italian cohort. A further 24 controls and 18 “de-novo” Italian patients were used for validation. The PDRPSP was identified in 19 controls and 19 PD patients from a Spanish cohort with late-stage PD. Thirty Spanish PD patients were used for validation. Patterns of the three centers were visually compared and then cross-validated. Furthermore, PDRP expression was determined in 8 patients with multiple system atrophy. Results A PDRP could be identified in each cohort. Each PDRP was characterized by relative hypermetabolism in the thalamus, putamen/pallidum, pons, cerebellum, and motor cortex. These changes co-varied with variable degrees of hypometabolism in posterior parietal, occipital, and frontal cortices. Frontal hypometabolism was less pronounced in “de-novo” PD subjects (Italian cohort). Occipital hypometabolism was more pronounced in late-stage PD subjects (Spanish cohort). PDRPIT, PDRPNL, and PDRPSP were significantly expressed in PD patients compared with controls in validation cohorts from the same center (P < 0.0001), and maintained significance on cross-validation (P < 0.005). PDRP expression was absent in MSA. Conclusion The PDRP is a reproducible disease characteristic across PD populations and scanning platforms globally. Further study is needed to identify the topography of specific PD subtypes, and to identify and correct for center-specific effects.

BACKGROUND: Today, the standardized uptake value (SUV) is essentially the only means for quantitative evaluation of static [18F-]fluorodeoxyglucose (FDG) positron emission tomography (PET) investigations. However, the SUV approach has several well-known shortcomings which adversely affect the reliability of the SUV as a surrogate of the metabolic rate of glucose consumption. The standard uptake ratio (SUR), i.e., the uptake time-corrected ratio of tumor SUV to image-derived arterial blood SUV, has been shown in the first clinical studies to overcome most of these shortcomings, to decrease test-retest variability, and to increase the prognostic value in comparison to SUV. However, it is unclear, to what extent the SUR approach is vulnerable to observer variability of the additionally required blood SUV (BSUV) determination. The goal of the present work was the investigation of the interobserver variability of image-derived BSUV. METHODS: FDG PET/CT scans from 83 patients (72 male, 11 female) with non-small cell lung cancer (N = 46) or head and neck cancer (N = 37) were included. BSUV was determined by 8 individuals, each applying a dedicated delineation tool for the BSUV determination in the aorta. Two of the observers applied two further tools. Altogether, five different delineation tools were used. With each used tool, delineation was performed for the whole patient group, resulting in 12 distinct observations per patient. Intersubject variability of BSUV determination was assessed using the fractional deviations for the individual patients from the patient group average and was quantified as standard deviation (SD is), 95% confidence interval, and range. Interobserver variability of BSUV determination was assessed using the fractional deviations of the individual observers from the observer-average for the considered patient and quantified as standard deviations (SD p, SD d) or root mean square (RMS), 95% confidence interval, and range in each patient, each observer, and the pooled data respectively. RESULTS: Interobserver variability in the pooled data amounts to RMS = 2.8% and is much smaller than the intersubject variability of BSUV (SD is= 16%). Averaged over the whole patient group, deviations of individual observers from the observer average are very small and fall in the range [ - 0.96, 1.05]%. However, interobserver variability partly differs distinctly for different patients, covering a range of [0.7, 7.4]% in the investigated patient group. CONCLUSION: The present investigation demonstrates that the image-based manual determination of BSUV in the aorta is sufficiently reproducible across different observers and delineation tools which is a prerequisite for accurate SUR determination. This finding is in line with the already demonstrated superior prognostic value of SUR in comparison to SUV in the first clinical studies. ispartof: EJNMMI RESEARCH vol:9 issue:1 ispartof: location:Germany status: published

Cardiovascular disease is the major cause of morbidity and mortality in developed countries and atherosclerosis is the major cause of cardiovascular disease. Atherosclerotic lesions obstruct blood flow in the arterial vessel wall and can rupture leading to the formation of occlusive thrombi. Conventional diagnostic tools are still of limited value for identifying the vulnerable arterial plaque and for predicting its risk of rupture and of releasing thromboembolic material. Knowledge of the molecular and biological processes implicated in the process of atherosclerosis will advance the development of imaging probes to differentiate the vulnerable plaque. The development of imaging probes with high sensitivity and specificity in identifying high-risk atherosclerotic vessel wall changes and plaques is crucial for improving knowledge-based decisions and tailored individual interventions. Arterial PET imaging with 18F-FDG has shown promising results in identifying inflammatory vessel wall changes in numerous studies and clinical trials. However, due to its limited specificity in general and its intense physiological uptake in the left ventricular myocardium that impair imaging of the coronary arteries, different PET tracers for the molecular imaging of atherosclerosis have been evaluated. This review describes biological, chemical and medical expertise supporting a translational approach that will enable the development of new or the evaluation of existing PET tracers for the identification of vulnerable atherosclerotic plaques for better risk prediction and benefit to patients.

Cardiovascular disease is the major cause of morbidity and mortality in developed countries and atherosclerosis is the major cause of cardiovascular disease. Atherosclerotic lesions obstruct blood flow in the arterial vessel wall and can rupture leading to the formation of occlusive thrombi. Conventional diagnostic tools are still of limited value for identifying the vulnerable arterial plaque and for predicting its risk of rupture and of releasing thromboembolic material. Knowledge of the molecular and biological processes implicated in the process of atherosclerosis will advance the development of imaging probes to differentiate the vulnerable plaque. The development of imaging probes with high sensitivity and specificity in identifying high-risk atherosclerotic vessel wall changes and plaques is crucial for improving knowledge-based decisions and tailored individual interventions. Arterial PET imaging with 18F-FDG has shown promising results in identifying inflammatory vessel wall changes in numerous studies and clinical trials. However, due to its limited specificity in general and its intense physiological uptake in the left ventricular myocardium that impair imaging of the coronary arteries, different PET tracers for the molecular imaging of atherosclerosis have been evaluated. This review describes biological, chemical and medical expertise supporting a translational approach that will enable the development of new or the evaluation of existing PET tracers for the identification of vulnerable atherosclerotic plaques for better risk prediction and benefit to patients.

Aim: To estimate the standard uptake values (SUVs) of Tc-99m methylene-diphosphonate (Tc-99m MDP) from normal skeletal sites in breast cancer patients using quantitative single-photon emission computed tomography (SPECT).Materials and Methods: A total of 60 breast cancer patients who underwent Tc-99m MDP SPECT/CT study at different postinjection acquisition times were included in this study. Based on postinjection acquisition time, patients were divided into four study groups (n_15 each), i.e. I st (2 h), II nd (3 h), III rd (4 h), and IV th (5 h). Image quantification (SUVmax and SUVmean) was performed using Q.Metrix software. Delineation of volume of interest was shaped around different bones of the skeletal system. Results: The highest normal SUVmax and SUVmean values were observed in lumber and thoracic vertebra (8.89 ± 2.26 and 2.89 ± 0.58) for Group I and in pelvis and thoracic (9.6 ± 1.32 and 3.04 ± 0.64), (10.93 ± 3.91 and 3.65 ± 0.97), (11.33 ± 2.67 and 3.65 ± 0.22) for Group II, III and IV, respectively. Lowest normal SUVmax and SUVmean values were observed in humerus and ribs (3.22 ± 0.67 and 0.97 ± 0.18), (5.16 ± 1.82 and 1.18 ± 0.16) for Group I, IV, and in humerus (3.17 ± 0.58 and 0.85 ± 0.26), (3.98 ± 1.12 and 1.04 ± 0.28) for Group II and III, respectively. Significant difference ( P < 0.05) noted in SUVmax for sternum, cervical, humerus, ribs, and pelvis with respect to time. However, significant difference ( P < 0.05) noted in SUVmean for all skeletal sites with respect to time. Conclusions: Our study shows variability in normal SUV values for different skeletal sites in breast cancer patients. Vertebral bodies and pelvis contribute highest SUV values. Time dependency of SUVs emphasizes the usefulness of routinely acquired images at the same time after Tc-99m MDP injection, especially in follow-up studies.

Purpose: In about 30% of patients treated with neoadjuvant chemoradiotherapy (nCRT) followed by surgical resection for locally advanced oesophageal cancer no vital tumour is found in the resection specimen. Accurate clinical response assessment is critical if deferral from surgery is considered in complete responders. Our study aimed to compare the performance of MRI and of FDG-PET/CT for the detection of residual disease after nCRT. Methods: Patients with oesophageal cancer eligible for nCRT and oesophagectomy were prospectively included. All patients underwent FDG-PET/CT and MRI before and between 6 and 8 weeks after nCRT. Two radiologists scored the MRI scans, and two nuclear medicine physicians scored the FDG-PET/CT scans using a 5-point score for residual disease. Histopathology after oesophagectomy represented the reference standard. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were calculated for detection of residual tumour (ypT+), residual nodal disease (ypN+), and any residual disease (ypT+Nx/ypT0N+). Results: Seven out of 33 (21%) patients had a pathological complete response. The AUCs for individual readers to detect ypT+ were 0.71/0.70 on diffusion-weighted (DW)-MRI and 0.54/0.57 on FDG-PET/CT, and to detect ypN+ were 0.89/0.81 on DW-MRI and 0.75/0.71 on FDG-PET/CT. The AUCs/sensitivities/specificities for the individual readers to detect any residual disease were 0.74/92%/57% and 0.70/96%/43% on MRI; these were 0.49/69%/29% and 0.60/69%/43% on FDG-PET/CT, respectively. Conclusion: MRI reached higher diagnostic accuracies than FDG-PET/CT for the detection of residual tumour in oesophageal cancer patients at 6 to 8 weeks after nCRT.

Objectives To investigate the potential of automatic lung cancer detection on submillisievert dose 18F-fludeoxyglucose (18F-FDG) scans using different positron emission tomography (PET) parameters, as a primary step towards a potential new indication for 18F-FDG PET in lung cancer screening. Methods We performed a retrospective cohort analysis with 83 patients referred for 18F-FDG PET/CT, including of 34 patients with histology-proven lung cancer and 49 patients without lung disease. Aside clinical standard PET images (PET100%) two additional low-dose PET reconstructions were generated, using only 15 s and 5 s of the 150 s list mode raw data of the full-dose PET, corresponding to 10% and 3.3% of the original 18F-FDG activity. The lungs were subdivided into three segments on each side, and each segment was classified as normal or containing cancer. The following standardized uptake values (SUVs) were extracted from PET per lung segment: SUVmean, SUVhot5, SUVmedian, SUVstd and SUVtotal. A multivariate linear regression model was used and cross-validated. The accuracy for lung cancer detection was tested with receiver operating characteristics analysis and T-statistics was used to calculate the weight of each parameter. Results The T-statistics showed that SUVstd was the most important discriminative factor for lung cancer detection. The multivariate model achieved an area under the curve of 0.97 for full-dose PET, 0.85 for PET10% with PET3.3% reconstructions resulting in a still high sensitivity the PET10% reconstruction of 80%. Conclusion This pilot study indicates that segment-based, quantitative PET parameters of low-dose PET reconstructions could be used to automatically detect lung cancer with high sensitivity. Advances in knowledge Automated assessment of PET parameters in low-dose PET may aid for an early detection of lung cancer.

Contains fulltext : 238088.pdf (Publisher’s version ) (Open Access) BACKGROUND: Central necrosis can be detected on [(18)F]FDG PET/CT as a region with little to no tracer uptake. Currently, there is no consensus regarding the inclusion of regions of central necrosis during volume of interest (VOI) delineation for radiomic analysis. The aim of this study was to assess how central necrosis affects radiomic analysis in PET. METHODS: Forty-three patients, either with non-small cell lung carcinomas (NSCLC, n = 12) or with pheochromocytomas or paragangliomas (PPGL, n = 31), were included retrospectively. VOIs were delineated with and without central necrosis. From all VOIs, 105 radiomic features were extracted. Differences in radiomic features between delineation methods were assessed using a paired t-test with Benjamini-Hochberg multiple testing correction. In the PPGL cohort, performances of the radiomic models to predict the noradrenergic biochemical profile were assessed by comparing the areas under the receiver operating characteristic curve (AUC) for both delineation methods. RESULTS: At least 65% of the features showed significant differences between VOI(vital-tumour) and VOI(gross-tumour) (65%, 79% and 82% for the NSCLC, PPGL and combined cohort, respectively). The AUCs of the radiomic models were not significantly different between delineation methods. CONCLUSION: In both tumour types, almost two-third of the features were affected, demonstrating that the impact of whether or not to include central necrosis in the VOI on the radiomic feature values is significant. Nevertheless, predictive performances of both delineation methods were comparable. We recommend that radiomic studies should report whether or not central necrosis was included during delineation.

Supplemental Digital Content is available in the text., Background: The mechanism behind the cardiovascular protection observed with human GLP-1 RA (glucagon-like peptide-1 receptor agonists) in type 2 diabetes is unknown. We hypothesized that treatment with the GLP-1 RA liraglutide had a positive effect on vascular inflammation. Methods: LIRAFLAME (Effect of liraglutide on vascular inflammation in type-2 diabetes: A randomized, placebocontrolled, double-blind, parallel clinical PET/CT trial) was a double-blind, randomized controlled trial performed at a single university hospital clinic in Denmark. Patients with type 2 diabetes were via computer-generated randomization list assigned (1:1) liraglutide up to 1.8 mg or placebo once daily for 26 weeks. The primary end point was change in vascular inflammation over 26 weeks assessed by [18F]-fluorodeoxyglucose positron emission tomography/computed tomography. Analyses were based on intention-to-treat. Key secondary outcomes included change in other indices of atherosclerosis. Results: Between October 26, 2017, and August 16, 2019, 147 patients were screened and 102 were randomly assigned to liraglutide (n=51) or placebo (n=51) and 99 (97%) completed the trial. Change in the [18F]-fluorodeoxyglucose positron emission tomography measure of vascular inflammation (active-segment target-to-background ratio) did not differ between treatment groups: change from baseline to 26 weeks was −0.04 (95% CI, −0.17 to 0.08) in the liraglutide group compared with −0.09 (−0.19 to 0.01) in the placebo group (mean difference, 0.05 [95% CI, −0.11 to 0.21], P=0.53). Secondary analyses restricted to [18F]-fluorodeoxyglucose positron emission tomography of the carotid arteries as well as other indices of atherosclerosis confirmed the primary result. We performed an explorative analysis of interaction between treatment group and history of cardiovascular disease (P=0.052). Conclusions: In this low to moderate risk population with type 2 diabetes, liraglutide did not change vascular inflammation assessed as [18F]-fluorodeoxyglucose uptake compared with placebo. An explorative analysis indicated a possible effect in persons with history of cardiovascular disease, in line with current guidelines where liraglutide is recommended to patients with history of cardiovascular disease. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03449654.

Aim The aims of this study were to determine the role of 18F-FDG PET/CT in vulvar cancer patients and to extract summary estimates of its diagnostic performance for preoperative lymph node staging. Patients and methods PubMed/Medline and Embase databases were searched to identify studies evaluating 18F-FDG PET/CT in vulvar cancer patients. The assessment of methodological quality of the included articles was performed. Per-patient and per-groin pooled estimates, with 95% confidence intervals (CIs), of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic odds ratio (DOR) were calculated. Results Ten articles were included in the systematic review, 7 among which evaluated the diagnostic performance of preoperative 18F-FDG PET/CT for lymph node staging. Qualitative per-patient analysis (72 patients from 4 studies) resulted in estimated pooled sensitivity, specificity, PPV, NPV, and DOR of 0.70 (95% CI, 0.44-0.95), 0.90 (95% CI, 0.76-1.04), 0.86 (95% CI, 0.66-1.06), 0.77 (95% CI, 0.56-0.97), and 10.49 (95% CI, 1.68-65.50), respectively. Qualitative per-groin analysis (245 groins from 5 studies) resulted in estimated pooled sensitivity, specificity, PPV, NPV, and DOR of 0.76 (95% CI, 0.57-0.94), 0.88 (95% CI, 0.82-0.94), 0.70 (95% CI, 0.55-0.85), 0.92 (95% CI, 0.86-0.97), and 19.43 (95% CI, 6.40-58.95), respectively. Conclusions Despite limited literature data, this systematic review and meta-analysis revealed that a negative preoperative PET/CT scan may exclude groin metastases in at least early-stage vulvar cancer patients currently unfit for sentinel node biopsy and select those eligible for a less invasive surgical treatment. A positive PET/CT result should otherwise be interpreted with caution. Larger prospective studies are needed to confirm these results and to evaluate the diagnostic value of standardized semiquantitative analysis compared with the qualitative one.

BACKGROUND: Transvenous 3 permanent pacemaker-related infection is a severe condition associated with significant morbidity and mortality. Leadless pacemakers may be more resistant to bacterial seeding during bloodstream infection because of its small surface area and encapsulation in the right ventricle. This study reports the incidence and outcomes of bacteraemia in patients implanted with a Micra leadless pacemaker. We present 18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) findings obtained in a subgroup of patients. METHODS: We report a retrospective cohort study of 155 patients who underwent a Micra TPS implant procedure at the University Hospitals of Leuven between July 2015 and July 2019. We identified the patients who developed an episode of bacteraemia, proved by ≥2 positive blood cultures. RESULTS: Of the 155 patients, 15 patients presented an episode of bacteraemia at a median of 226 days (range: 3-1129) days after the implant procedure. Gram-positive species accounted for 73.3% (n = 11) of the bacteraemia including Staphylococcus (n = 5), Enterococcus (n = 3), and Streptococcus (n = 3). The source of infection was identified in nine patients (60%) including endocarditis in four patients, urinary tract in three patients, and skin in two patients. 18 F-FDG PET/CT imaging performed in six patients did not show sign of infection around the leadless pacemaker. Bacteraemia was resolved in all patients after adequate antibiotherapy. Four patients died early during follow up. For all other patients, there were no recurrence of systemic infection during a median follow up of 263 days (range: 15-1134). CONCLUSION: In our small cohort, no leadless pacemaker endocarditis was observed among patients with bacteraemia. ispartof: JOURNAL OF CARDIOVASCULAR ELECTROPHYSIOLOGY vol:31 issue:9 pages:2440-2447 ispartof: location:United States status: published

PURPOSE: 18F-Fluorodeoxyglucose positron emission tomography (18F-FDG PET/CT) is frequently used to diagnose fracture-related infections (FRIs), but its diagnostic performance in this field is still unknown. The aims of this study were: (1) to assess the diagnostic performance of qualitative assessment of 18F-FDG PET/CT scans in diagnosing FRI, (2) to establish the diagnostic performance of standardized uptake values (SUVs) extracted from 18F-FDG PET/CT scans and to determine their associated optimal cut-off values, and (3) to identify variables that predict a false-positive (FP) or false-negative (FN) 18F-FDG PET/CT result.METHODS: This retrospective cohort study included all patients with suspected FRI undergoing 18F-FDG PET/CT between 2011 and 2017 in two level-1 trauma centres. Two nuclear medicine physicians independently reassessed all 18F-FDG PET/CT scans. The reference standard consisted of the result of at least two deep, representative microbiological cultures or the presence/absence of clinical confirmatory signs of FRI (AO/EBJIS consensus definition) during a follow-up of at least 6 months. Diagnostic performance in terms of sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) was calculated. Additionally, SUVs were measured on 18F-FDG PET/CT scans. Volumes of interest were drawn around the suspected and corresponding contralateral areas to obtain absolute values and ratios between suspected and contralateral areas. A multivariable logistic regression analysis was also performed to identify the most important predictor(s) of FP or FN 18F-FDG PET/CT results.RESULTS: The study included 156 18F-FDG PET/CT scans in 135 patients. Qualitative assessment of 18F-FDG PET/CT scans showed a sensitivity of 0.89, specificity of 0.80, PPV of 0.74, NPV of 0.91 and diagnostic accuracy of 0.83. SUVs on their own resulted in lower diagnostic performance, but combining them with qualitative assessments yielded an AUC of 0.89 compared to an AUC of 0.84 when considering only the qualitative assessment results (p = 0.007). 18F-FDG PET/CT performed CONCLUSION: Qualitative assessment of 18F-FDG PET/CT scans had a diagnostic accuracy of 0.83 and an excellent NPV of 0.91 in diagnosing FRI. Adding SUV measurements to qualitative assessment provided additional accuracy in comparison to qualitative assessment alone. An interval between surgery and 18F-FDG PET/CT of

Purpose Positron emission tomography (PET) with Zirconium-89 (Zr-89)-labeled antibodies can be used for in vivo quantification of antibody uptake. Knowledge about measurement variability is required to ensure correct interpretation. However, no clinical studies have been reported on measurement variability of Zr-89 immuno-PET. As variability due to low signal-to-noise is part of the total measurement variability, the aim of this study was to assess noise-induced variability of Zr-89 -immuno-PET using count-reduced clinical images. Procedures Data were acquired from three previously reported clinical studies with [89Zr]antiCD20 (74 MBq, n = 7), [89Zr]antiEGFR (37 MBq, n = 7), and [89Zr]antiCD44 (37 MBq, n = 13), with imaging obtained 1 to 6 days post injection (D0–D6). Volumes of interest (VOIs) were manually delineated for liver, spleen, kidney, lung, brain, and tumor. For blood pool and bone marrow, fixed-size VOIs were used. Original PET list mode data were split and reconstructed, resulting in two count-reduced images at 50 % of the original injected dose (e.g., 37 MBq74inj). Repeatability coefficients (RC) were obtained from Bland-Altman analysis on standardized uptake values (SUV) derived from VOIs applied to these images. Results The RC for the combined manually delineated organs for [89Zr] antiCD20 (37 MBq74inj) increased from D0 to D6 and was less than 6 % at all time points. Blood pool and bone marrow had higher RC, up to 43 % for 37 MBq74inj at D6. For tumor, the RC was up to 42 % for [89Zr]antiCD20 (37 MBq74inj). For [89Zr]antiCD20, (18 MBq74inj), [89Zr]antiEGFR (18 MBq37inj), and [89Zr]antiCD44 (18 MBq37inj), measurement variability was independent of the investigated antibody. Conclusions Based on this study, noise-induced variability results in a RC for Zr-89-immuno-PET (37 MBq) around 6 % for manually delineated organs combined, increasing up to 43 % at D6 for blood pool and bone marrow, assuming similar biodistribution of antibodies. The signal-to-noise ratio leads to tumor RC up to 42 %. Electronic supplementary material The online version of this article (10.1007/s11307-018-1200-4) contains supplementary material, which is available to authorized users.

Purpose: An ever-growing number of predictive models used to inform clinical decision making have included quantitative, computer-extracted imaging biomarkers, or "radiomic features." Broadly generalizable validity of radiomics-assisted models may be impeded by concerns about reproducibility. We offer a qualitative synthesis of 41 studies that specifically investigated the repeatability and reproducibility of radiomic features, derived from a systematic review of published peer-reviewed literature.Methods and Materials: The PubMed electronic database was searched using combinations of the broad Haynes and Ingui filters along with a set of text words specific to cancer, radiomics (including texture analyses), reproducibility, and repeatability. This review has been reported in compliance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. From each full-text article, information was extracted regarding cancer type, class of radiomic feature examined, reporting quality of key processing steps, and statistical metric used to segregate stable features.Results: Among 624 unique records, 41 full-text articles were subjected to review. The studies primarily addressed non-small cell lung cancer and oropharyngeal cancer. Only 7 studies addressed in detail every methodologic aspect related to image acquisition, preprocessing, and feature extraction. The repeatability and reproducibility of radiomic features are sensitive at various degrees to processing details such as image acquisition settings, image reconstruction algorithm, digital image preprocessing, and software used to extract radiomic features. First-order features were overall more reproducible than shape metrics and textural features. Entropy was consistently reported as one of the most stable first-order features. There was no emergent consensus regarding either shape metrics or textural features; however, coarseness and contrast appeared among the least reproducible.Conclusions: Investigations of feature repeatability and reproducibility are currently limited to a small number of cancer types. Reporting quality could be improved regarding details of feature extraction software, digital image manipulation (preprocessing), and the cutoff value used to distinguish stable features. (C) 2018 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Positron emission tomography (PET) and magnetic resonance imaging (MRI) have both been used for decades in cardiovascular imaging. Since 2010, hybrid PET/MRI using sequential and integrated scanner platforms has been available, with hybrid cardiac PET/MR imaging protocols increasingly incorporated into clinical workflows. Given the range of complementary information provided by each method, the use of hybrid PET/MRI may be justified and beneficial in particular clinical settings for the evaluation of different disease entities. In the present joint position statement, we critically review the role and value of integrated PET/MRI in cardiovascular imaging, provide a technical overview of cardiac PET/MRI and practical advice related to the cardiac PET/MRI workflow, identify cardiovascular applications that can potentially benefit from hybrid PET/MRI, and describe the needs for future development and research. In order to encourage its wide dissemination, this article is freely accessible on the European Radiology and European Journal of Hybrid Imaging web sites. • Studies and case-reports indicate that PET/MRI is a feasible and robust technology. • Promising fields of application include a variety of cardiac conditions. • Larger studies are required to demonstrate its incremental and cost-effective value. • The translation of novel radiopharmaceuticals and MR-sequences will provide exciting new opportunities.

PURPOSE: This study aims to investigate whether clinical, laboratory, and fluorine-18-fluorodeoxyglucose (F-FDG) PET/CT findings can discriminate between mediastinal Hodgkin's lymphoma and primary mediastinal B-cell lymphoma (PMBCL).PATIENTS AND METHODS: This retrospective study included 56 patients (42 with mediastinal Hodgkin's lymphoma and 14 with PBMCL). Differences in clinical, laboratory, and F-FDG PET/CT metrics were assessed between Hodgkin's lymphoma and PMBCL.RESULTS: Lactate dehydrogenase (LDH) and F-FDG PET/CT-based maximum tumor diameter, lesion-to-liver ratio maximum standardized uptake value (SUVmax), and lesion-to-liver ratio peak standardized uptake value (SUVpeak) were all significantly higher (PCONCLUSION: LDH levels and several F-FDG PET/CT findings (tumor size, presence of necrosis, and degree of F-FDG uptake) are helpful in discriminating mediastinal Hodgkin's lymphoma from PMBCL.