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Purpose We evaluated brain metabolic dysfunctions and associations with neurological and biological parameters in acute, subacute and chronic COVID-19 phases to provide deeper insights into the pathophysiology of the disease.Methods Twenty-six patients with neurological symptoms (neuro-COVID-19) and [F-18]FDG-PET were included. Seven patients were acute (< 1 month (m) after onset), 12 subacute (4 >= 1-m, 4 >= 2-m and 4 >= 3-m) and 7 with neuro-post-COVID-19 (3 >= 5-m and 4 >= 7-9-m). One patient was evaluated longitudinally (acute and 5-m). Brain hypo- and hypermetabolism were analysed at single-subject and group levels. Correlations between severity/extent of brain hypo- and hypermetabolism and biological (oxygen saturation and C-reactive protein) and clinical variables (global cognition and Body Mass Index) were assessed.Results The "fronto-insular cortex" emerged as the hypometabolic hallmark of neuro-COVID-19. Acute patients showed the most severe hypometabolism affecting several cortical regions. Three-m and 5-m patients showed a progressive reduction of hypometabolism, with limited frontal clusters. After 7-9 months, no brain hypometabolism was detected. The patient evaluated longitudinally showed a diffuse brain hypometabolism in the acute phase, almost recovered after 5 months. Brain hypometabolism correlated with cognitive dysfunction, low blood saturation and high inflammatory status. Hypermetabolism in the brainstem, cerebellum, hippocampus and amygdala persisted over time and correlated with inflammation status.Conclusion Synergistic effects of systemic virus-mediated inflammation and transient hypoxia yield a dysfunction of the fronto-insular cortex, a signature of CNS involvement in neuro-COVID-19. This brain dysfunction is likely to be transient and almost reversible. The long-lasting brain hypermetabolism seems to reflect persistent inflammation processes.

Background The current management of lung cancer patients has reached a high level of complexity. Indeed, besides the traditional clinical variables (e.g., age, sex, TNM stage), new omics data have recently been introduced in clinical practice, thereby making more complex the decision-making process. With the advent of Artificial intelligence (AI) techniques, various omics datasets may be used to create more accurate predictive models paving the way for a better care in lung cancer patients. Methods The LANTERN study is a multi-center observational clinical trial involving a multidisciplinary consortium of five institutions from different European countries. The aim of this trial is to develop accurate several predictive models for lung cancer patients, through the creation of Digital Human Avatars (DHA), defined as digital representations of patients using various omics-based variables and integrating well-established clinical factors with genomic data, quantitative imaging data etc. A total of 600 lung cancer patients will be prospectively enrolled by the recruiting centers and multi-omics data will be collected. Data will then be modelled and parameterized in an experimental context of cutting-edge big data analysis. All data variables will be recorded according to a shared common ontology based on variable-specific domains in order to enhance their direct actionability. An exploratory analysis will then initiate the biomarker identification process. The second phase of the project will focus on creating multiple multivariate models trained though advanced machine learning (ML) and AI techniques for the specific areas of interest. Finally, the developed models will be validated in order to test their robustness, transferability and generalizability, leading to the development of the DHA. All the potential clinical and scientific stakeholders will be involved in the DHA development process. The main goals aim of LANTERN project are: i) To develop predictive models

Background: The current management of lung cancer patients has reached a high level of complexity. Indeed, besides the traditional clinical variables (e.g., age, sex, TNM stage), new omics data have recently been introduced in clinical practice, thereby making more complex the decision-making process. With the advent of Artificial intelligence (AI) techniques, various omics datasets may be used to create more accurate predictive models paving the way for a better care in lung cancer patients. Methods: The LANTERN study is a multi-center observational clinical trial involving a multidisciplinary consortium of five institutions from different European countries. The aim of this trial is to develop accurate several predictive models for lung cancer patients, through the creation of Digital Human Avatars (DHA), defined as digital representations of patients using various omics-based variables and integrating well-established clinical factors with genomic data, quantitative imaging data etc. A total of 600 lung cancer patients will be prospectively enrolled by the recruiting centers and multi-omics data will be collected. Data will then be modelled and parameterized in an experimental context of cutting-edge big data analysis. All data variables will be recorded according to a shared common ontology based on variable-specific domains in order to enhance their direct actionability. An exploratory analysis will then initiate the biomarker identification process. The second phase of the project will focus on creating multiple multivariate models trained though advanced machine learning (ML) and AI techniques for the specific areas of interest. Finally, the developed models will be validated in order to test their robustness, transferability and generalizability, leading to the development of the DHA. All the potential clinical and scientific stakeholders will be involved in the DHA development process. The main goals aim of LANTERN project are: i) To develop predictive mode

Simple Summary The fibroblast activation protein (FAP) is highly expressed on cancer-associated fibroblasts in many tumors. Radiolabeled FAP inhibitors (FAPIs) have been recently developed as new promising radiotracers in an oncological setting, both as diagnostic imaging by Positron Emission Tomography/Computed Tomography (PET/CT) and as new anti-cancer treatment, in a theranostic perspective. This narrative review aimed to summarize the current evidence on the role of FAPI radiotracers in the diagnostic and therapeutic management of patients with breast cancer (BC). Despite some clinical and methodological heterogeneity among the evaluated studies, Ga-68-FAPI PET/CT emerges as a valuable diagnostic tool in BC patients, demonstrating a general high tumor uptake across all histological and molecular BC subtypes, along with technical advantages and an overall better performance than the standard-of-care F-18-FDG. Moreover, although with still limited clinical evidence, treatment with radiolabeled FAPIs seems a promising approach in BC patients, increasing the possibility of more personalized treatments. Growing studies have recently reported on the promising application of radiolabeled-fibroblast activation protein inhibitors (FAPIs) as diagnostic and therapeutic agents in various oncological populations. To exclusively evaluate the current evidence on the diagnostic and therapeutic role of FAPI radiotracers in patients with breast cancer (BC), a narrative review of the available literature was performed. A search algorithm from PubMed/MEDLINE, based on the combination of "PET" OR "positron emission tomography" and "FAPI" and "cancer", with a last update in February 2022, was applied. From 233 identified articles, 33 studies conducted in BC patients and with available data on PET imaging or radiolabeled-FAPI therapy were finally considered, for a total of 191 patients. Despite some clinical and methodological heterogeneity among the reviewed articles, Ga-68-FAPI PET

With the aim of providing evidence about doctor-managers' resilience during the Covid-19 pandemic, this study analyzes the characteristics of 114 doctor-managers operating within the Italian National Health Service (NHS). During the emergency, doctor-managers had to show adaptive capacities to deal with unexpected situations and develop new paradigms, procedures, and quick responses to patients' needs. This is in line with resilience, and in this perspective, it is crucial to investigate resilience determinants. The paper, therefore, provides an identikit of the resilient doctor-manager. The research was conducted between November and December 2020. Primary data were collected through an online questionnaire consisting of six sections. Participation was voluntary and anonymous. Data were analyzed using quantitative techniques and employing Stata 16. Confirmatory Factor Analysis was employed to test construct validity and scale reliability. Results show that increasing levels of individual resilience are related to increasing levels of managerial identity. Moreover, physicians' individual resilience has a positive association with commitment, knowledge diffusion, and Evidence-Based Medicine adoption. Finally, physicians' individual resilience has a negative association with their role in the university, their specialty, and their gender. The study suggests some practical implications for healtcare organizations. In general, career paths are decided primarily on competency assessment, while an important role should be devoted to behavioral characteristics. Furthermore, organizations should take care of the levels of individual commitment and encourage professional networking because both help doctor-managers cope with uncertainty. The originality of the study relies on a fresh look at all previous work. There are currently few contributions in the literature to explore and investigate resilience elements in doctor-managers during t

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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 < 0.001). Instead, no significant difference among pre-COVID and control periods was present. The prevalence of interstitial pneumonia detected at PET/CT was directly associated with geographic virus diffusion, with the higher rate in Northern Italy. Among 284 interstitial pneumonia detected during COVID period, 169 (59%) were FDG-avid (average SUVmax of 4.1). 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.

Purpose: An appropriate healthy control dataset is mandatory to achieve good performance in voxel-wise analyses. We aimed at evaluating [18F]FDG PET brain datasets of healthy controls (HC), based on publicly available data, for the extraction of voxel-based brain metabolism maps at the single-subject level. Methods: Selection of HC images was based on visual rating, after Cook’s distance and jack-knife analyses, to exclude artefacts and/or outliers. The performance of these HC datasets (ADNI-HC and AIMN-HC) to extract hypometabolism patterns in single patients was tested in comparison with the standard reference HC dataset (HSR-HC) by means of Dice score analysis. We evaluated the performance and comparability of the different HC datasets in the assessment of single-subject SPM-based hypometabolism in three independent cohorts of patients, namely, ADD, bvFTD and DLB. Results: Two-step Cook’s distance analysis and the subsequent jack-knife analysis resulted in the selection of n = 125 subjects from the AIMN-HC dataset and n = 75 subjects from the ADNI-HC dataset. The average concordance between SPM hypometabolism t-maps in the three patient cohorts, as obtained with the new datasets and compared to the HSR-HC standard reference dataset, was 0.87 for the AIMN-HC dataset and 0.83 for the ADNI-HC dataset. Pattern expression analysis revealed high overall accuracy (> 80%) of the SPM t-map classification according to different statistical thresholds and sample sizes. Conclusions: The applied procedures ensure validity of these HC datasets for the single-subject estimation of brain metabolism using voxel-wise comparisons. These well-selected HC datasets are ready-to-use in research and clinical settings.

Purpose: An appropriate healthy control dataset is mandatory to achieve good performance in voxel-wise analyses. We aimed at evaluating [18F]FDG PET brain datasets of healthy controls (HC), based on publicly available data, for the extraction of voxel-based brain metabolism maps at the single-subject level. Methods: Selection of HC images was based on visual rating, after Cook’s distance and jack-knife analyses, to exclude artefacts and/or outliers. The performance of these HC datasets (ADNI-HC and AIMN-HC) to extract hypometabolism patterns in single patients was tested in comparison with the standard reference HC dataset (HSR-HC) by means of Dice score analysis. We evaluated the performance and comparability of the different HC datasets in the assessment of single-subject SPM-based hypometabolism in three independent cohorts of patients, namely, ADD, bvFTD and DLB. Results: Two-step Cook’s distance analysis and the subsequent jack-knife analysis resulted in the selection of n = 125 subjects from the AIMN-HC dataset and n = 75 subjects from the ADNI-HC dataset. The average concordance between SPM hypometabolism t-maps in the three patient cohorts, as obtained with the new datasets and compared to the HSR-HC standard reference dataset, was 0.87 for the AIMN-HC dataset and 0.83 for the ADNI-HC dataset. Pattern expression analysis revealed high overall accuracy (> 80%) of the SPM t-map classification according to different statistical thresholds and sample sizes. Conclusions: The applied procedures ensure validity of these HC datasets for the single-subject estimation of brain metabolism using voxel-wise comparisons. These well-selected HC datasets are ready-to-use in research and clinical settings.

Purpose: In the present review, we aimed to underline the importance of a clinically oriented PET reporting through the discussion of critical aspects that affect the impact of PET in NSCLC patients. Methods: Cornerstones for PET reporting related to staging of NSCLC after the publication of the new 8th edition of TNM and emerging issues related to locally advanced disease, to restaging and to response evaluation to innovative therapies are listed and specifically commented. Results: 18F-FDG PET/CT imaging has a prominent role in NSCLC patients both prior to surgery and when evaluating for metastatic disease. The benefit is even most marked in patients at greater risk of distant metastases. In this framework, for patients with stage III, PET imaging has the potential to result in a stage-shift through the identification of asymptomatic occult distant metastases, thus highlighting unexpected stage IV patients. The final PET report is influenced by factors that lie outside the acquired images, from the clinical information available at the time of reporting to the capability of linking these clinical details to further decision-making especially in the settings of response to new therapies. Conclusion: A multidisciplinary approach to cancer patients has a significant impact in their management and outcome. A clinically-oriented report is needed to transfer the relevant information to the clinician to fully exploit PET potential in NSCLC.

Purpose: To investigate whether the COVID-19 pandemic and national lockdown had an impact on the extent of cancer disease at FDG PET/CT staging as surrogate marker. Methods: Retrospective observational study including cancer patients submitted to FDG PET/CT staging from June 1 to October 31, 2020, and June 1 to October 31, 2019, respectively. Data regarding primary tumour, nodal (N) status and number of involved nodal stations, and presence and number of distant metastases (M) were collected. Each scan was classified in limited vs advanced status. Data were aggregated across the study population and tumour type. Bi-weekly frequencies of the observed events were analysed. Results: Six hundred eleven patients were included (240 in 2019 vs 371 in 2020, respectively). A significant increase of advanced disease patients (rate 1.56, P < 0.001), N + or M + patients (rate 1.84 and 2.09, respectively, P < 0.001), and patients with a greater number of involved N stations or M (rate 2.01 and 2.06, respectively, P < 0.001) were found in 2020 compared with data of 2019. Analysis by tumour type showed a significant increase of advanced disease in lymphoma and lung cancer in 2020 compared with 2019 (P < 0.001). In addition, a significant increase of nodal involvement was found in lung, gastro-intestinal, and breast cancers, as well as in lymphoma patients (P < 0.02). A significant increase of distant metastases was found in lung cancers (P = 0.002). Conclusion: Cancer patients with advanced disease at FDG PET/CT staging increased in 2020 compared with 2019, following the national lockdown due to the COVID-19 pandemic, 1.5-fold with a significant increase of patients with N or M involvement. Targeted health interventions are needed to mitigate the effects of the pandemic on patient outcome.

2-deoxy-2-fluorine-(18F)fluoro-D-glucose Positron Emission Tomography/Computed Tomography (18F-FDG-PET/CT) is widely used in oncology mainly for diagnosis and staging of various cancer types, including lung cancer, which is the most common cancer worldwide. Since histopathologic subtypes of lung cancer show different degree of 18F-FDG uptake, to date there are some diagnostic limits and uncertainties, hindering an 18F-FDG-PET-driven classification of histologic subtypes of lung cancers. On the other hand, since activated macrophages, neutrophils, fibroblasts and granulation tissues also show an increased 18F-FDG activity, infectious and/or inflammatory processes and post-surgical and post-radiation changes may cause false-positive results, especially for lymph-nodes assessment. Here we propose a model-free, machine-learning based algorithm for the automated classification of adenocarcinoma, the most common type of lung cancer, and other types of tumors. Input for the algorithm are dynamic acquisitions of PET data (dPET), providing for a spatially and temporally resolved characterization of the uptake kinetic. The algorithm consists in a trained Random Forest classifier which, relying contextually on several spatial and temporal features of 18F-FDG uptake, generates as an outcome probability maps allowing to distinguish adenocarcinoma from other lung histotype and to identify metastatic lymph-nodes, ultimately increasing the specificity of the technique. Its performance, evaluated on a dPET dataset of 19 patients affected by primary lung cancer, provides a probability 0.943 ± 0.090 for the detection of adenocarcinoma. The use of this algorithm will guarantee an automatic and more accurate localization and discrimination of tumors, also providing a powerful tool for detecting at which extent tumor has spread beyond a primary tumor into lymphatic system.

Malignant pleural mesothelioma (MPM) is an aggressive malignancy, frequently diagnosed at locally-advanced/metastatic stages. Due to a very poor prognosis and limited treatment options, the need to identify new prognostic markers represents a great clinical challenge. The prognostic role of metabolic information derived from Positron Emission Tomography (PET) with 18F-Fluoro-deoxy-glucose (18F-FDG) has been investigated in different MPM settings, however with no definitive consensus. In this comprehensive review, the prognostic value of FDG-PET imaging exclusively performed at staging in MPM patients was evaluated, conducting a literature search on PubMed/MEDLINE from 2010 to 2020. From the 19 selected studies, despite heterogeneity in several aspects, staging FDG-PET imaging emerges as a valuable prognostic biomarker, with higher tumor uptake predictive of worse prognosis, and with volumetric metabolic parameters like Metabolic Tumor Volume, (MTV) and Total Lesion Glycolisis (TLG) performing better than SUVmax. However, PET uptake parameters were not always confirmed as independent prognostic factors, especially in patients previously treated with pleurodesis and with a non-epithelioid histotype. Future prospective studies in larger and clinically homogeneous populations, and using more standardized methods of PET images analysis, are needed to further validate the value of staging FDG-PET in the prognostic MPM stratification, with a potential impact on better patient-tailored treatment planning, in the perspective of personalized medicine.

Purpose: Tumor response evaluated by 2-deoxy-2-[ 18 F]fluoro-d-glucose ([ 18 F]FDG) positron emission tomography/computed tomography (PET/CT) with standardized uptake value (SUV) is questionable when pre- and post-treatment PET/CT are acquired on different scanners. The aims of our study, performed in oncological patients who underwent pre- and post-treatment [ 18 F]FDG PET/CT on different scanners, were (1) to evaluate whether EQ·PET, a proprietary SUV inter-exams harmonization tool, modifies the EORTC tumor response classification and (2) to assess which classification (harmonized and non-harmonized) better predicts clinical outcome. Procedures: We retrospectively identified 95 PET pairs (pre- and post-treatment) performed on different scanners (Biograph mCT, Siemens; GEMINI GXL, Philips) in 73 oncological patients (52F; 57.8 ± 16.3 years). An 8-mm Gaussian filter was applied for the Biograph protocol to meet the EANM/EARL harmonization standard; no filter was needed for GXL. SUVmax and SUVmaxEQ of the same target lesion in the pre- and post-treatment PET/CT were noted. For each PET pair, the metabolic response classification (responder/non-responder), derived from combining the EORTC response categories, was evaluated twice (with and without harmonization). In discordant cases, the association of each metabolic response classification with final clinical response assessment and survival data (2-year disease-free survival, DFS) was assessed. Results: On Biograph, SUVmaxEQ of all target lesions was significantly lower (p = 0.001) than SUVmax (8.5 ± 6.8 vs 12.5 ± 9.6; − 38.6 %). A discordance between the two metabolic response classifications (harmonized and non-harmonized) was found in 19/95 (20 %) PET pairs. In this subgroup (n = 19; mean follow-up, 33.9 ± 9 months), responders according to harmonized classification (n = 9) had longer DFS (47.5 months, 88.9 %) than responders (n = 10) according to non-harmonized classification (26.3&n

Purpose: To test a short 2-[18F]Fluoro-2-deoxy-D-glucose (2-[18F]FDG) PET dynamic acquisition protocol to calculate Ki using regional Patlak graphical analysis in patients with non-small-cell lung cancer (NSCLC). Methods: 24 patients with NSCLC who underwent standard dynamic 2-[18F]FDG acquisitions (60 min) were randomly divided into two groups. In group 1 (n = 10), a population-based image-derived input function (pIDIF) was built using a monoexponential trend (10–60 min), and a leave-one-out cross-validation (LOOCV) method was performed to validate the pIDIF model. In group 2 (n = 14), Ki was obtained by standard regional Patlak plot analysis using IDIF (0–60 min) and tissue response (10–60 min) curves from the volume of interests (VOIs) placed on descending thoracic aorta and tumor tissue, respectively. Moreover, with our method, the Patlak analysis was performed to obtain Ki,s using IDIFFitted curve obtained from PET counts (0–10 min) followed by monoexponential coefficients of pIDIF (10–60 min) and tissue response curve obtained from PET counts at 10 min and between 40 and 60 min, simulating two short dynamic acquisitions. Both IDIF and IDIFFitted curves were modeled to assume the value of 2-[18F]FDG plasma activity measured in the venous blood sampling performed at 45 min in each patient. Spearman's rank correlation, coefficient of determination, and Passing–Bablok regression were used for the comparison between Ki and Ki,s. Finally, Ki,s was obtained with our method in a separate group of patients (group 3, n = 8) that perform two short dynamic acquisitions. Results: Population-based image-derived input function (10–60 min) was modeled with a monoexponential curve with the following fitted parameters obtained in group 1: a = 9.684, b = 16.410, and c = 0.068 min−1. The LOOCV error was 0.4%. In patients of group 2, the mean values of Ki and Ki,s were 0.0442 ± 0.0302 and 0.33 ± 0.0298, respectively (R2 = 0.9970). The Passing–Bablok regression for comparison betwe

Background: 18F-fluorodeoxyglucose (18F-FDG) positron-emission-tomography (PET) allows detection of cerebral metabolic alterations in neurological diseases vs. normal aging. We assess age-and sex-related brain metabolic changes in healthy subjects, exploring impact of activity normalization methods. Methods: brain scans of Italian Association of Nuclear Medicine normative database (151 subjects, 67 Males, 84 Females, aged 20–84) were selected. Global mean, white matter, and pons activity were explored as normalization reference. We performed voxel-based and ROI analyses using SPM12 and IBM-SPSS software. Results: SPM proved a negative correlation between age and brain glucose metabolism involving frontal lobes, anterior-cingulate and insular cortices bilaterally. Narrower clusters were detected in lateral parietal lobes, precuneus, temporal pole and medial areas bilaterally. Normalizing on pons activity, we found a more significant negative correlation and no positive one. ROIs analysis confirmed SPM results. Moreover, a significant age × sex interaction effect was revealed, with worse metabolic reduction in posterior-cingulate cortices in females than males, especially in post-menopausal age. Conclusions: this study demonstrated an age-related metabolic reduction in frontal lobes and in some parieto-temporal areas more evident in females. Results suggested pons as the most appropriate normalization reference. Knowledge of age-and sex-related cerebral metabolic changes is critical to correctly interpreting brain 18F-FDG PET imaging.

Purpose: The prognostic evaluation of glioma recurrence patients is important in the therapeutic management. We investigated the prognostic value of11 C-methionine PET-CT (MET-PET) dynamic and semiquantitative parameters in patients with suspected glioma recurrence. Methods: Sixty-seven consecutive patients who underwent MET-PET for suspected glioma recurrence at MR were retrospectively included. Twenty-one patients underwent static MET-PET; 46/67 underwent dynamic MET-PET. In all patients, SUVmax, SUVmean and tumour-to-background ratio (T/B) were calculated. From dynamic acquisition, the shape and slope of time-activity curves, time-to-peak and its SUVmax (SUVmaxTTP ) were extrapolated. The prognostic value of PET parameters on progression-free (PFS) and overall survival (OS) was evaluated using Kaplan–Meier survival estimates and Cox regression. Results: The overall median follow-up was 19 months from MET-PET. Recurrence patients (38/67) had higher SUVmax (p = 0.001), SUVmean (p = 0.002) and T/B (p < 0.001); deceased patients (16/67) showed higher SUVmax (p = 0.03), SUVmean (p = 0.03) and T/B (p = 0.006). All static parameters were associated with PFS (all p < 0.001); T/B was associated with OS (p = 0.031). Regarding kinetic analyses, recurrence (27/46) and deceased (14/46) patients had higher SUVmaxTTP (p = 0.02, p = 0.01, respectively). SUVmaxTTP was the only dynamic parameter associated with PFS (p = 0.02) and OS (p = 0.006). At univariate analysis, SUVmax, SUVmean, T/B and SUVmaxTTP were predictive for PFS (all p < 0.05); SUVmaxTTP was predictive for OS (p = 0.02). At multivariate analysis, SUVmaxTTP remained significant for PFS (p = 0.03). Conclusion: Semiquantitative parameters and SUVmaxTTP were associated with clinical outcomes in patients with suspected glioma recurrence. Dynamic PET-CT acquisition, with static and kinetic parameters, can be a valuable non-invasive prognostic marker, identifying patients with worse prognosis who require personali

In patients with plasma cell malignancy (multiple myeloma and plasmacytoma), whole-body low-dose computed tomography, magnetic resonance imaging, and 18F-FDG PET/CT are widely applied and suggested by international guidelines to assess the disease extension. Recently, 11C-methionine PET/CT has proven to be promising in those patients compared to other diagnostic techniques. We aimed to review current literature on the state of the art of 11C-methionine PET/CT in patients with plasma cell malignancy. PubMed/MEDLINE database was screened to find articles regarding the role of 11C-methionine PET/CT in plasma cell malignancy. Terms (PET OR positron emission tomography) AND methionine AND myeloma were used. Among 23 studies initially retrieved, 7 (overall 258 patients) were included. In all except two studies, 11C-methionine PET/CT was related to 18F-FDG PET/CT (of whom one also with 11C-4′-thiothymidine PET/CT), one study to 11C-choline PET/CT and one compared multiple myeloma and control patients, both having 11C-methionine scan. Overall, 11C-methionine PET/CT resulted able to detect a higher number of positive patients as well as more bone lesions than 18F-FDG and 11C-choline (detection rate: 75.6–90.7%, 55.0–76.7%, and 73.7%, respectively). A stronger correlation with bone marrow histological results was found for 11C-methionine than for 18F-FDG and 11C-choline PET/CT scans. Although additional studies are needed to validate the role of 11C-methionine PET/CT, it seems to be a safety and effective tool in identification of medullary and extramedullary disease in patients with plasma cell malignancy.

We report the case of a 58-year-old man with mesenteric nodule at CT performed for abdominal pain. In the suspicion of neoplastic disease, he underwent 18F-FDG PET/CT that did not show abnormal uptake. The nodule was monitored alternating CT and MRI. Two years after the first detection, MRI revealed an increase in size, and 18F-FDG PET/CT was repeated for metabolic evaluation, showing increased metabolic activity. In suspicion of neuroendocrine tumor, for anatomical site, slow growth, and clinical symptoms, 68Ga-DOTATOC PET/CT was performed showing focal uptake, indicating high expression of somatostatin receptors. The final pathology report was consistent with high-grade leiomyosarcoma.

Objective: 11C-Methionine PET/CT (C-MET) is a promising method in detecting abnormal parathyroid glands in patients with primary hyperparathyroidism (PHPT). The first aim of the study was to evaluate which is the diagnostic role of C-MET in patients with PHPT and inconclusive pre-operative imaging. Second, we aimed to investigate whether C-MET semi-quantitative parameters may reflect biochemical and histological characteristics of involved glands. Methods: Patients with PHPT, undergoing C-MET after an inconclusive pre-operative imaging and having a parathyroid surgery, were retrospectively included. C-MET visual and semi-quantitative assessment was performed. Parameters, as SUVmax, SUVpeak, SUVmean, functional lesion volume (FLV) and total lesion activity (TLA), were measured for each detected lesion; SUVmean, FLV and TLA were calculated on 40–90% thresholds of SUVmax to define SUVmean40-90, FLV40-90 and TLA40-90, respectively. Results were correlated with patients’ clinical-laboratory (calcium and PTH values) and histological data (size and weight of excised glands). Mann–Whitney test was used and P value < 0.05 was considered significant. Results: Thirty-eight patients (36 female, age: 57.69 ± 15.13 years) were included. Pre-operative median calcium and PTH values were 11.1 mg/dl [interquartile range (IQR) 10.6–11.5] and 154.6 pg/ml (IQR 101.8–227.0), respectively. C-MET showed a parathyroid uptake in 30 out of thirty-eight patients (78.9%). Among 42 nodules excised, C-MET correctly detected the side of the neck (right/left) in 30/42 with sensitivity, specificity and accuracy of 79, 75 and 79%, respectively. C-MET correctly identified the exact position (superior/inferior) in 27/42 with sensitivity, specificity and accuracy of 75, 50 and 71%, respectively. SUVpeak, FLV50-70 and TLA40-70 were significantly (P < 0.05) higher in patients with higher PTH results. The histological size resulted significantly (P < 0.05) higher in abnormal glands

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 < 0.001). Instead, no significant difference among pre-COVID and control periods was present. The prevalence of interstitial pneumonia detected at PET/CT was directly associated with geographic virus diffusion, with the higher rate in Northern Italy. Among 284 interstitial pneumonia detected during COVID period, 169 (59%) were FDG-avid (average SUVmax of 4.1). 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.

Neurotrophins are a family of proteins that support neuronal proliferation, survival, and differentiation in the central and peripheral nervous systems, and are regulators of neuronal plasticity. Nerve growth factor is one of the best-described neurotrophins and has advanced to clinical trials for treatment of ocular and brain diseases due to its trophic and regenerative properties. Prior trials over the past few decades have produced conflicting results, which have principally been ascribed to adverse effects of systemic nerve growth factor administration, together with poor penetrance of the blood-brain barrier that impairs drug delivery. Contrastingly, recent studies have revealed that topical ocular and intranasal nerve growth factor administration are safe and effective, suggesting that topical nerve growth factor delivery is a potential alternative to both systemic and invasive intracerebral delivery. The therapeutic effects of local nerve growth factor delivery have been extensively investigated for different ophthalmic diseases, including neurotrophic keratitis, glaucoma, retinitis pigmentosa, and dry eye disease. Further, promising pharmacologic effects were reported in an optic glioma model, which indicated that topically administered nerve growth factor diffused far beyond where it was topically applied. These findings support the therapeutic potential of delivering topical nerve growth factor preparations intranasally for acquired and degenerative brain disorders. Preliminary clinical findings in both traumatic and non-traumatic acquired brain injuries are encouraging, especially in pediatric patients, and clinical trials are ongoing. The present review will focus on the therapeutic effects of both ocular and intranasal nerve growth factor delivery for diseases of the brain and eye.

Purpose: To evaluate the predictive value of18F-FDG PET/CT semiquantitative parameters of the primary tumour and CA 19-9 levels assessed before treatment in patients with locally advanced pancreatic cancer (LAPC). Methods: Among one-hundred twenty patients with LAPC treated at our institution with initial chemotherapy followed by curative chemoradiotherapy (CRT) from July 2013 to January 2019, a secondary analysis with baseline18F-FDG PET/CT was conducted in fifty-eight patients. Pre-treatment CA 19-9 level and the maximum standardized uptake value (SUVmax), metabolic tumour volume (MTV) and total lesion glycolysis (TLG) of primary tumour were measured. The receiving operating characteristics (ROC) analysis was performed to define the cut-off point of SUVmax, MTV, TLG and CA 19-9 values to use in prediction of early progression (EP), local progression (LP) and overall survival (OS). Areas under the curve (AUCs) were assessed for all variables. Post-test probability was calculated to evaluate the advantage for parameters combination. Results: For EP, CA 19-9 level > 698 U/mL resulted the best marker to identify patient at higher risk with OR of 5.96 (95% CI, 1.66–19.47; p = 0.005) and a Positive Predictive Value (PPV) of 61%. For LP, the most significant parameter was TLG (OR 9.75, 95% CI, 1.64–57.87, p = 0.012), with PPV of 83%. For OS, the most significant parameter was MTV (OR 3.12, 95% CI, 0.9–10.83, p = 0.07) with PPV of 88%. Adding consecutively each of the other parameters, PPV to identify patients at risk resulted further increased (>90%). Conclusions: Pre-treatment CA 19-9 level, as well as MTV and TLG values of primary tumour at baseline18F-FDG PET/CT and their combination, may represent significant predictors of EP, LP and OS in LAPC patients.

Aim The aim of this study was to evaluate brain glucose metabolism by means of [18F]-fluoro-deoxygluycose (18F-FDG) PET in a group of patients presenting dysautonomic syndrome after human papilloma virus (HPV) immunization. Methods Medical records of patients, referred to the 'Second Opinion Medical Consulting Network' Medical Centre (Modena, Italy) diagnosed with dysautonomic syndrome were searched. Inclusion criteria were presence in the medical history of adverse drug reactions following HPV vaccine; a Montreal Cognitive Assessment score <25 and good quality of a 18F-FDG-PET brain scan performed within 12 months from the diagnosis of dysautonomic syndrome. 18F-FDG-PET images of patients (HPV-group) were compared to a control group, matched for age and sex, using statistical parametric mapping (SPM). Results The 18F-FDG-PET study was available for five female patients. The SPM-group analysis revealed significant hypometabolism (P < 0.05 false discovery rate corrected) in the right superior and medial temporal gyrus (Brodmann areas 22, 21) and insula (Brodmann area 13). At a threshold of P < 0.001 (uncorrected), further hypometabolic regions were revealed in the right superior temporal gyrus (Brodmann area 42) and caudate head and in the left superior temporal gyrus (Brodmann area 22), frontal subcallosal gyrus (Brodmann area 47) and insula (Brodmann area 13). Relative hypermetabolism (P = 0.001) was revealed in the right premotor cortex (Brodmann area 6). Conclusion This study revealed the possibility of altered brain glucose metabolism in subjects with dysautonomic syndrome post-immunization with HPV vaccine. These results could reinforce the hypothesis of a causal relationship between HPV vaccine, or some component included in the vaccine and the development of clinical manifestations.

Idiopathic normal pressure hydrocephalus (iNPH) is the only form of dementia that can be cured by surgery. Its diagnosis relies on clinical and radiological criteria. Identifying patients who can benefit from surgery is challenging, as other neurological diseases can be concomitant or mimic iNPH. We performed a systematic review on the role of positron emission tomography (PET) in iNPH. We retrieved 35 papers evaluating four main functional aspects with different PET radiotracers: (1) PET with amyloid tracers, revealing Alzheimer’s disease (AD) pathology in 20–57% of suspected iNPH patients, could be useful in predictions of surgical outcome. (2) PET with radiolabeled water as perfusion tracer showed a global decreased cerebral blood flow (CBF) and regional reduction of CBF in basal ganglia in iNPH; preoperative perfusion parameters could predict surgical outcome. (3) PET with 2-Deoxy-2-[18F]fluoroglucose ([18F]FDG ) showed a global reduction of glucose metabolism without a specific cortical pattern and a hypometabolism in basal ganglia; [18F]FDG PET may identify a coexisting neurodegenerative disease, helping in patient selection for surgery; postsurgery increase in glucose metabolism was associated with clinical improvement. (4) Dopaminergic PET imaging showed a postsynaptic D2 receptor reduction and striatal upregulation of D2 receptor after treatment, associated with clinical improvement. Overall, PET imaging could be a useful tool in iNPH diagnoses and treatment response.

Purpose: In patient with breast cancer (BC), 18F-FDG PET/CT is widely used for assessing skeletal metastatic involvement. Also 18F-NaF PET imaging is considered an accurate modality for detecting bone metastases. We aimed to review current literature on comparative performances of 18F-FDG and 18F-NaF PET imaging for assessing bone metastases from BC. Methods: A literature search for PET studies published in PubMed/MEDLINE database in the last 10 years (September 2009–September 2019) using both 18F-FDG and 18F-NaF to detect bone involvement in BC patients was conducted, based on the combination of the terms (“PET” OR “positron emission tomography”) AND ((“FDG” OR “fluorodeoxyglucose” AND “fluoride” OR “NaF”)) AND “breast cancer”. Data on clinical and methodological aspects and diagnostic performances between the two tracers were collected and compared. Results: Out of 43 studies initially retrieved, 12 studies (overall 340 patients) were finally considered, 3/12 performing a combined 18F-FDG/18F-NaF (“cocktail”) imaging. Heterogeneity in several aspects has been found among studies. However, 18F-NaF PET demonstrated overall higher sensitivity than 18F-FDG (ranging from 91.7 to 100% and from 41.6 to 75%, respectively), potentially impacting on patients’ management, but with lower specificity due to non-tumor-specific bone uptake (ranging from 46.3 to 76.2% and from 94.3 to 99%, respectively). 18F-FDG only is able to detect early metastases confined to bone marrow. Occurrence of “flare phenomenon” limits the use of 18F-NaF for assessing early treatment response. Cocktail imaging may allow the most comprehensive evaluation of bone involvement, moreover with dosimetry advantages over two single-tracer PET scans, but losing prognostic information carried by 18F-FDG. Conclusion: Both 18F-NaF and 18F-FDG are suitable for assessing skeletal involvement in BC patients. However, inherent different uptake mechanism highlights differences in diagnostic performance between t