Cloud-based serverless computing enables accelerated monte carlo simulations for nuclear medicine imaging.

Objective.This study investigates the potential of cloud-based serverless computing to accelerate Monte Carlo (MC) simulations for nuclear medicine imaging tasks. MC simulations can pose a high computational burden-even when executed on modern multi-core computing servers. Cloud computing allows simulation tasks to be highly parallelized and considerably accelerated.Approach.We investigate the computational performance of a cloud-based serverless MC simulation of radioactive decays for positron emission tomography imaging using Amazon Web Service (AWS) Lambda serverless computing platform for the first time in scientific literature. We provide a comparison of the computational performance of AWS to a modern on-premises multi-thread reconstruction server by measuring the execution times of the processes using between105and2·1010simulated decays. We deployed two popular MC simulation frameworks-SimSET and GATE-within the AWS computing environment. Containerized application images were used as a basis for an AWS Lambda function, and local (non-cloud) scripts were used to orchestrate the deployment of simulations. The task was broken down into smaller parallel runs, and launched on concurrently running AWS Lambda instances, and the results were postprocessed and downloaded via the Simple Storage Service.Main results.Our implementation of cloud-based MC simulations with SimSET outperforms local server-based computations by more than an order of magnitude. However, the GATE implementation creates more and larger output file sizes and reveals that the internet connection speed can become the primary bottleneck for data transfers. Simulating 109decays using SimSET is possible within 5 min and accrues computation costs of about $10 on AWS, whereas GATE would have to run in batches for more than 100 min at considerably higher costs.Significance.Adopting cloud-based serverless computing architecture in medical imaging research facilities can considerably improve processing times and overall workflow efficiency, with future research exploring additional enhancements through optimized configurations and computational methods.

Evaluation of responses to cardiac imaging questions by the artificial intelligence large language model ChatGPT.

PURPOSE: To assess ChatGPT's ability as a resource for educating patients on various aspects of cardiac imaging, including diagnosis, imaging modalities, indications, interpretation of radiology reports, and management. METHODS: 30 questions were posed to ChatGPT-3.5 and ChatGPT-4 three times in three separate chat sessions. Responses were scored as correct, incorrect, or clinically misleading categories by three observers-two board certified cardiologists and one board certified radiologist with cardiac imaging subspecialization. Consistency of responses across the three sessions was also evaluated. Final categorization was based on majority vote between at least two of the three observers. RESULTS: ChatGPT-3.5 answered seventeen of twenty eight questions correctly (61 %) by majority vote. Twenty one of twenty eight questions were answered correctly (75 %) by ChatGPT-4 by majority vote. Majority vote for correctness was not achieved for two questions. Twenty six of thirty questions were answered consistently by ChatGPT-3.5 (87 %). Twenty nine of thirty questions were answered consistently by ChatGPT-4 (97 %). ChatGPT-3.5 had both consistent and correct responses to seventeen of twenty eight questions (61 %). ChatGPT-4 had both consistent and correct responses to twenty of twenty eight questions (71 %). CONCLUSION: ChatGPT-4 had overall better performance than ChatGTP-3.5 when answering cardiac imaging questions with regard to correctness and consistency of responses. While both ChatGPT-3.5 and ChatGPT-4 answers over half of cardiac imaging questions correctly, inaccurate, clinically misleading and inconsistent responses suggest the need for further refinement before its application for educating patients about cardiac imaging.

Dose Reduction in Pediatric Oncology Patients with Delayed Total-Body [18F]FDG PET/CT.

Our aim was to define a lower limit of reduced injected activity in delayed [18F]FDG total-body (TB) PET/CT in pediatric oncology patients. Methods: In this single-center prospective study, children were scanned for 20 min with TB PET/CT, 120 min after intravenous administration of a 4.07 ± 0.49 MBq/kg dose of [18F]FDG. Five randomly subsampled low-count reconstructions were generated using », ⅛, [Formula: see text], and [Formula: see text] of the counts in the full-dose list-mode reference standard acquisition (20 min), to simulate dose reduction. For the 2 lowest-count reconstructions, smoothing was applied. Background uptake was measured with volumes of interest placed on the ascending aorta, right liver lobe, and third lumbar vertebra body (L3). Tumor lesions were segmented using a 40% isocontour volume-of-interest approach. Signal-to-noise ratio, tumor-to-background ratio, and contrast-to-noise ratio were calculated. Three physicians identified malignant lesions independently and assessed the image quality using a 5-point Likert scale. Results: In total, 113 malignant lesions were identified in 18 patients, who met the inclusion criteria. Of these lesions, 87.6% were quantifiable. Liver SUVmean did not change significantly, whereas a lower signal-to-noise ratio was observed in all low-count reconstructions compared with the reference standard (P < 0.0001) because of higher noise rates. Tumor uptake (SUVmax), tumor-to-background ratio, and total lesion count were significantly lower in the reconstructions with [Formula: see text] and [Formula: see text] of the counts of the reference standard (P < 0.001). Contrast-to-noise ratio and clinical image quality were significantly lower in all low-count reconstructions than with the reference standard. Conclusion: Dose reduction for delayed [18F]FDG TB PET/CT imaging in children is possible without loss of image quality or lesion conspicuity. However, our results indicate that to maintain comparable tumor uptake and lesion conspicuity, PET centers should not reduce the injected [18F]FDG activity below 0.5 MBq/kg when using TB PET/CT in pediatric imaging at 120 min after injection.

High-Temporal-Resolution Kinetic Modeling of Lung Tumors with Dual-Blood Input Function Using Total-Body Dynamic PET.

The lungs are supplied by both the pulmonary arteries carrying deoxygenated blood originating from the right ventricle and the bronchial arteries carrying oxygenated blood downstream from the left ventricle. However, this effect of dual blood supply has never been investigated using PET, partially because the temporal resolution of conventional dynamic PET scans is limited. The advent of PET scanners with a long axial field of view, such as the uEXPLORER total-body PET/CT system, permits dynamic imaging with high temporal resolution (HTR). In this work, we modeled the dual-blood input function (DBIF) and studied its impact on the kinetic quantification of normal lung tissue and lung tumors using HTR dynamic PET imaging. Methods: Thirteen healthy subjects and 6 cancer subjects with lung tumors underwent a dynamic 18F-FDG scan with the uEXPLORER for 1 h. Data were reconstructed into dynamic frames of 1 s in the early phase. Regional time-activity curves of lung tissue and tumors were analyzed using a 2-tissue compartmental model with 3 different input functions: the right ventricle input function, left ventricle input function, and proposed DBIF, all with time delay and dispersion corrections. These models were compared for time-activity curve fitting quality using the corrected Akaike information criterion and for differentiating lung tumors from lung tissue using the Mann-Whitney U test. Voxelwise multiparametric images by the DBIF model were further generated to verify the regional kinetic analysis. Results: The effect of dual blood supply was pronounced in the high-temporal-resolution time-activity curves of lung tumors. The DBIF model achieved better time-activity curve fitting than the other 2 single-input models according to the corrected Akaike information criterion. The estimated fraction of left ventricle input was low in normal lung tissue of healthy subjects but much higher in lung tumors (∼0.04 vs. ∼0.3, P < 0.0003). The DBIF model also showed better robustness in the difference in 18F-FDG net influx rate [Formula: see text] and delivery rate [Formula: see text] between lung tumors and normal lung tissue. Multiparametric imaging with the DBIF model further confirmed the differences in tracer kinetics between normal lung tissue and lung tumors. Conclusion: The effect of dual blood supply in the lungs was demonstrated using HTR dynamic imaging and compartmental modeling with the proposed DBIF model. The effect was small in lung tissue but nonnegligible in lung tumors. HTR dynamic imaging with total-body PET can offer a sensitive tool for investigating lung diseases.

FDG imaging with long-axial field-of-view PET/CT in patients with high blood glucose-a matched pair analysis.

PURPOSE: High blood glucose (hBG) in patients undergoing [18F]FDG PET/CT scans often results in rescheduling the examination, which may lead to clinical delay for the patient and decrease productivity for the department. The aim of this study was to evaluate whether long-axial field-of-view (LAFOV) PET/CT can minimize the effect of altered bio-distribution in hBG patients and is able to provide diagnostic image quality in hBG situations. MATERIALS AND METHODS: Oncologic patients with elevated blood glucose (≥ 8.0 mmol/l) and normal blood glucose (< 8.0 mmol/l, nBG) levels were matched for tumor entity, gender, age, and BMI. hBG patients were further subdivided into two groups (BG 8-11 mmol/l and BG > 11 mmol/l). Tracer uptake in the liver, muscle, and tumor was evaluated. Furthermore, image quality was compared between long acquisitions (ultra-high sensitivity mode, 360 s) on a LAFOV PET/CT and routine acquisitions equivalent to a short-axial field-of-view scanner (simulated (sSAFOV), obtained with high sensitivity mode, 120 s). Tumor-to-background ratio (TBR) and contrast-to-noise ratio (CNR) were used as the main image quality criteria. RESULTS: Thirty-one hBG patients met the inclusion criteria and were matched with 31 nBG patients. Overall, liver uptake was significantly higher in hBG patients (SUVmean, 3.07 ± 0.41 vs. 2.37 ± 0.33; p = 0.03), and brain uptake was significantly lower (SUVmax, 7.58 ± 0.74 vs. 13.38 ± 3.94; p < 0.001), whereas muscle (shoulder/gluteal) uptake showed no statistically significant difference. Tumor uptake was lower in hBG patients, resulting in a significantly lower TBR in the hBG cohort (3.48 ± 0.74 vs. 5.29 ± 1.48, p < 0.001). CNR was higher in nBG compared to hBG patients (12.17 ± 4.86 vs. 23.31 ± 12.22, p < 0.001). However, subgroup analysis of nBG 8-11 mmol/l on sSAFOV PET/CT compared to hBG (> 11 mmol/l) patients examined with LAFOV PET/CT showed no statistical significant difference in CNR (19.84 ± 8.40 vs. 17.79 ± 9.3, p = 0.08). CONCLUSION: While elevated blood glucose (> 11 mmol) negatively affected TBR and CNR in our cohort, the images from a LAFOV PET-scanner had comparable CNR to PET-images acquired from nBG patients using sSAFOV PET/CT. Therefore, we argue that oncologic patients with increased blood sugar levels might be imaged safely with LAFOV PET/CT when rescheduling is not feasible.

Development of a Monte Carlo-based scatter correction method for total-body PET using the uEXPLORER PET/CT scanner.

Objective.This study presents and evaluates a robust Monte Carlo-based scatter correction (SC) method for long axial field of view (FOV) and total-body positron emission tomography (PET) using the uEXPLORER total-body PET/CT scanner.Approach.Our algorithm utilizes the Monte Carlo (MC) tool SimSET to compute SC factors in between individual image reconstruction iterations within our in-house list-mode and time-of-flight-based image reconstruction framework. We also introduced a unique scatter scaling technique at the detector block-level for optimal estimation of the scatter contribution in each line of response. First image evaluations were derived from phantom data spanning the entire axial FOV along with image data from a human subject with a large body mass index. Data was evaluated based on qualitative inspections, and contrast recovery, background variability, residual scatter removal from cold regions, biases and axial uniformity were quantified and compared to non-scatter-corrected images.Main results.All reconstructed images demonstrated qualitative and quantitative improvements compared to non-scatter-corrected images: contrast recovery coefficients improved by up to 17.2% and background variability was reduced by up to 34.3%, and the residual lung error was between 1.26% and 2.08%. Low biases throughout the axial FOV indicate high quantitative accuracy and axial uniformity of the corrections. Up to 99% of residual activity in cold areas in the human subject was removed, and the reliability of the method was demonstrated in challenging body regions like in the proximity of a highly attenuating knee prosthesis.Significance.The MC SC method employed was demonstrated to be accurate and robust in TB-PET. The results of this study can serve as a benchmark for optimizing the quantitative performance of future SC techniques.

Long-axial field-of-view PET/CT for the assessment of inflammation in calcified coronary artery plaques with [68 Ga]Ga-DOTA-TOC.

PURPOSE: Inflamed, prone-to-rupture coronary plaques are an important cause of myocardial infarction and their early identification is crucial. Atherosclerotic plaques are characterized by overexpression of the type-2 somatostatin receptor (SST2) in activated macrophages. SST2 ligand imaging (e.g. with [68 Ga]Ga-DOTA-TOC) has shown promise in detecting and quantifying the inflammatory activity within atherosclerotic plaques. However, the sensitivity of standard axial field of view (SAFOV) PET scanners may be suboptimal for imaging coronary arteries. Long-axial field of view (LAFOV) PET/CT scanners may help overcome this limitation. We aim to assess the ability of [68 Ga]Ga-DOTA-TOC LAFOV-PET/CT in detecting calcified, SST2 overexpressing coronary artery plaques. METHODS: In this retrospective study, 108 oncological patients underwent [68 Ga]Ga-DOTA-TOC PET/CT on a LAFOV system. [68 Ga]Ga-DOTA-TOC uptake and calcifications in the coronary arteries were evaluated visually and semi-quantitatively. Data on patients' cardiac risk factors and coronary artery calcium score were also collected. Patients were followed up for 21.5 ± 3.4 months. RESULTS: A total of 66 patients (61.1%) presented with calcified coronary artery plaques. Of these, 32 patients had increased [68 Ga]Ga-DOTA-TOC uptake in at least one coronary vessel (TBR: 1.65 ± 0.53). Patients with single-vessel calcifications showed statistically significantly lower uptake (SUVmax 1.10 ± 0.28) compared to patients with two- (SUVmax 1.31 ± 0.29, p < 0.01) or three-vessel calcifications (SUVmax 1.24 ± 0.33, p < 0.01). There was a correlation between coronary artery calcium score (CACS) and [68 Ga]Ga-DOTA-TOC uptake, especially in the LAD (p = 0.02). Stroke and all-cause death occurred more frequently in patients with increased [68 Ga]Ga-DOTA-TOC uptake (15.63% vs. 0%; p:0.001 and 21.88% vs. 6.58%; p: 0.04, respectively) during the follow-up period. CONCLUSION: [68 Ga]Ga-DOTA-TOC as a marker for the macrophage activity can reveal unknown cases of inflamed calcified coronary artery plaques using a LAFOV PET system. [68 Ga]Ga-DOTA-TOC uptake increased with the degree of calcification and correlated with higher risk of stroke and all-cause death. [68 Ga]Ga-DOTA-TOC LAFOV PET/CT may be useful to assess patients' cardiovascular risk.

EXPLORing Arthritis with Total-body Positron Emission Tomography.

Arthritis has significant adverse consequences on musculoskeletal tissues and often other organs of the body. Current methods for clinical evaluation of arthritis are suboptimal, and biomarkers that are objective and measurable indicators for monitoring of arthritis disease activity are in critical demand. Recently, total-body positron emission tomography (PET) has been developed that can collect imaging signals synchronously from the entire body at ultra-low doses and reduced scan times. These scanners have increased signal collection efficiency that overcomes several limitations of standard PET scanners in the evaluation of arthritis, and they may potentially provide biomarkers to assess local and systemic impact of the arthritis disease process. This article reviews current results from using total-body PET in the assessment of common arthritic conditions, and it outlines future opportunities and challenges.

Total-body Dynamic Imaging and Kinetic Modeling of 18F-AraG in Healthy Individuals and a Non-Small Cell Lung Cancer Patient Undergoing Anti-PD-1 Immunotherapy.

Immunotherapies, especially the checkpoint inhibitors such as anti-PD-1 antibodies, have transformed cancer treatment by enhancing immune system's capability to target and kill cancer cells. However, predicting immunotherapy response remains challenging. 18F-AraG is a molecular imaging tracer targeting activated T cells, which may facilitate therapy response assessment by non-invasive quantification of immune cell activity within tumor microenvironment and elsewhere in the body. The aim of this study was to obtain preliminary data on total-body pharmacokinetics of 18F-AraG, as a potential quantitative biomarker for immune response evaluation. Methods: The study consisted of 90-min total-body dynamic scans of four healthy subjects and one non-small cell lung cancer (NSCLC) patient, scanned before and after anti-PD-1 immunotherapy. Compartmental modeling with Akaike information criterion model selection were employed to analyze tracer kinetics in various organs. Additionally, seven sub-regions of the primary lung tumor and four mediastinal lymph nodes were analyzed. Practical identifiability analysis was performed to assess reliability of kinetic parameter estimation. Correlations of SUVmean, SUVR (tissue-to-blood ratio), and Logan plot slope KLogan with total volume-of-distribution VT were calculated to identify potential surrogates for kinetic modeling. Results: Strong correlations were observed between KLogan and SUVR values with VT, suggesting that they can be used as promising surrogates for VT, especially in organs with low blood-volume fraction. Moreover, the practical identifiability analysis suggests that the dynamic 18F-AraG PET scans could potentially be shortened to 60 minutes, while maintaining quantification accuracy for all organs-of-interest. The study suggests that although 18F-AraG SUV images can provide insights on immune cell distribution, kinetic modeling or graphical analysis methods may be required for accurate quantification of immune response post-therapy. While SUVmean showed variable changes in different sub-regions of the tumor post-therapy, the SUVR, KLogan, and VT showed consistent increasing trends in all analyzed sub-regions of the tumor with high practical identifiability. Conclusion: Our findings highlight the promise of 18F-AraG dynamic imaging as a non-invasive biomarker for quantifying the immune response to immunotherapy in cancer patients. The promising total-body kinetic modeling results also suggest potentially wider applications of the tracer in investigating the role of T cells in the immunopathogenesis of diseases.

Natural History of Lung Hernias.

BACKGROUND: Lung herniation has been described in case reports or series. There are scare data in the form of original research studies to systematically evaluate this condition. OBJECTIVE: Our aim was to evaluate lung hernias with a focus on their natural history. METHODS: This is a retrospective study at our institution of patients who were found to have lung herniation on imaging between September 2010 and November 2022. Electronic medical record review was performed to extract clinical information regarding patients. Computed tomographic imaging was used to evaluate hernia size and size progression over time with a median follow-up time of 3.8 years. RESULTS: Thirty-eight patients were eligible for analysis. Majority of patients were overweight or obese (31/38), smokers (31/38), had prior thoracic surgery (30/38), and were asymptomatic (33/38). Twenty of 38 patients had stability in hernia size, 12 of 38 patients had hernia size progression, and 6 of 38 patients showed hernia size regression. Younger age was found to be predictive of hernia size progression with age of 60 years being the cut-off for its prediction. CONCLUSION: Lung hernias typically either remain stable in size or show size progression. Younger age (60 years cut-off) was found to be predictive of size progression. This is the largest systematic investigation at a medical institution to the best of our knowledge of lung hernias which used computed tomographic imaging to follow up lung hernias. Further information could be given to patients with this condition and to clinicians for potential management guidance.

Total-Body Multiparametric PET Quantification of 18F-FDG Delivery and Metabolism in the Study of Coronavirus Disease 2019 Recovery.

Conventional whole-body static 18F-FDG PET imaging provides a semiquantitative evaluation of overall glucose metabolism without insight into the specific transport and metabolic steps. Here we demonstrate the ability of total-body multiparametric 18F-FDG PET to quantitatively evaluate glucose metabolism using macroparametric quantification and assess specific glucose delivery and phosphorylation processes using microparametric quantification for studying recovery from coronavirus disease 2019 (COVID-19). Methods: The study included 13 healthy subjects and 12 recovering COVID-19 subjects within 8 wk of confirmed diagnosis. Each subject had a 1-h dynamic 18F-FDG scan on the uEXPLORER total-body PET/CT system. Semiquantitative SUV and the SUV ratio relative to blood (SUVR) were calculated for different organs to measure glucose utilization. Tracer kinetic modeling was performed to quantify the microparametric blood-to-tissue 18F-FDG delivery rate [Formula: see text] and the phosphorylation rate k 3, as well as the macroparametric 18F-FDG net influx rate ([Formula: see text]). Statistical tests were performed to examine differences between healthy subjects and recovering COVID-19 subjects. The effect of COVID-19 vaccination was also investigated. Results: We detected no significant difference in lung SUV but significantly higher lung SUVR and [Formula: see text] in COVID-19 recovery, indicating improved sensitivity of kinetic quantification for detecting the difference in glucose metabolism. A significant difference was also observed in the lungs with the phosphorylation rate k 3 but not with [Formula: see text], which suggests that glucose phosphorylation, rather than glucose delivery, drives the observed difference of glucose metabolism. Meanwhile, there was no or little difference in bone marrow 18F-FDG metabolism measured with SUV, SUVR, and [Formula: see text] but a significantly higher bone marrow [Formula: see text] in the COVID-19 group, suggesting a difference in glucose delivery. Vaccinated COVID-19 subjects had a lower lung [Formula: see text] and a higher spleen [Formula: see text] than unvaccinated COVID-19 subjects. Conclusion: Higher lung glucose metabolism and bone marrow glucose delivery were observed with total-body multiparametric 18F-FDG PET in recovering COVID-19 subjects than in healthy subjects, implying continued inflammation during recovery. Vaccination demonstrated potential protection effects. Total-body multiparametric PET of 18F-FDG can provide a more sensitive tool and more insights than conventional whole-body static 18F-FDG imaging to evaluate metabolic changes in systemic diseases such as COVID-19.

Ampullary Adenocarcinoma, Version 1.2023, NCCN Clinical Practice Guidelines in Oncology.

Ampullary cancers refer to tumors originating from the ampulla of Vater (the ampulla, the intraduodenal portion of the bile duct, and the intraduodenal portion of the pancreatic duct), while periampullary cancers may arise from locations encompassing the head of the pancreas, distal bile duct, duodenum, or ampulla of Vater. Ampullary cancers are rare gastrointestinal malignancies, and prognosis varies greatly based on factors such as patient age, TNM classification, differentiation grade, and treatment modality received. Systemic therapy is used in all stages of ampullary cancer, including neoadjuvant therapy, adjuvant therapy, and first-line or subsequent-line therapy for locally advanced, metastatic, and recurrent disease. Radiation therapy may be used in localized ampullary cancer, sometimes in combination with chemotherapy, but there is no high-level evidence to support its utility. Select tumors may be treated surgically. This article describes NCCN recommendations regarding management of ampullary adenocarcinoma.

Fully Automated, Fast Motion Correction of Dynamic Whole-Body and Total-Body PET/CT Imaging Studies.

We introduce the Fast Algorithm for Motion Correction (FALCON) software, which allows correction of both rigid and nonlinear motion artifacts in dynamic whole-body (WB) images, irrespective of the PET/CT system or the tracer. Methods: Motion was corrected using affine alignment followed by a diffeomorphic approach to account for nonrigid deformations. In both steps, images were registered using multiscale image alignment. Moreover, the frames suited to successful motion correction were automatically estimated by calculating the initial normalized cross-correlation metric between the reference frame and the other moving frames. To evaluate motion correction performance, WB dynamic image sequences from 3 different PET/CT systems (Biograph mCT, Biograph Vision 600, and uEXPLORER) using 6 different tracers (18F-FDG, 18F-fluciclovine, 68Ga-PSMA, 68Ga-DOTATATE, 11C-Pittsburgh compound B, and 82Rb) were considered. Motion correction accuracy was assessed using 4 different measures: change in volume mismatch between individual WB image volumes to assess gross body motion, change in displacement of a large organ (liver dome) within the torso due to respiration, change in intensity in small tumor nodules due to motion blur, and constancy of activity concentration levels. Results: Motion correction decreased gross body motion artifacts and reduced volume mismatch across dynamic frames by about 50%. Moreover, large-organ motion correction was assessed on the basis of correction of liver dome motion, which was removed entirely in about 70% of all cases. Motion correction also improved tumor intensity, resulting in an average increase in tumor SUVs by 15%. Large deformations seen in gated cardiac 82Rb images were managed without leading to anomalous distortions or substantial intensity changes in the resulting images. Finally, the constancy of activity concentration levels was reasonably preserved (<2% change) in large organs before and after motion correction. Conclusion: FALCON allows fast and accurate correction of rigid and nonrigid WB motion artifacts while being insensitive to scanner hardware or tracer distribution, making it applicable to a wide range of PET imaging scenarios.

Baseline 18F-FDG PET/CT Radiomics in Classical Hodgkin's Lymphoma: The Predictive Role of the Largest and the Hottest Lesions.

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.

Ferumoxytol-enhanced MR venography for diagnosis of venous thoracic outlet syndrome.

Venous thoracic outlet syndrome commonly results in arm swelling and pain as the subclavian vein is obstructed within the thoracic inlet. We report the use of ferumoxytol-enhanced contrast MRI in the diagnosis of venous thoracic outlet syndrome in a male adolescent. In this patient who presented with right upper extremity thrombosis, ferumoxytol-enhanced MRI of the chest was able to show both chronic subclavian vein thromboses and dynamic occlusion of the subclavian veins with arm abduction consistent with Paget-Schroetter syndrome.

Long Axial Field-of-View PET/CT Could Answer Unmet Needs in Gynecological Cancers.

Gynecological malignancies currently affect about 3.5 million women all over the world. Imaging of uterine, cervical, vaginal, ovarian, and vulvar cancer still presents several unmet needs when using conventional modalities such as ultrasound, computed tomography (CT), magnetic resonance, and standard positron emission tomography (PET)/CT. Some of the current diagnostic limitations are represented by differential diagnosis between inflammatory and cancerous findings, detection of peritoneal carcinomatosis and metastases <1 cm, detection of cancer-associated vascular complications, effective assessment of post-therapy changes, as well as bone metabolism and osteoporosis assessment. As a result of recent advances in PET/CT instrumentation, new systems now offer a long-axial field-of-view (LAFOV) to image between 106 cm and 194 cm (i.e., total-body PET) of the patient's body simultaneously and feature higher physical sensitivity and spatial resolution compared to standard PET/CT systems. LAFOV PET could overcome the forementioned limitations of conventional imaging and provide valuable global disease assessment, allowing for improved patient-tailored care. This article provides a comprehensive overview of these and other potential applications of LAFOV PET/CT imaging for patients with gynecological malignancies.

Total-Body Multiparametric PET Quantification of 18 F-FDG Delivery and Metabolism in the Study of COVID-19 Recovery.

Conventional whole-body 18 F-FDG PET imaging provides a semi-quantitative evaluation of overall glucose metabolism without gaining insight into the specific transport and metabolic steps. Here we demonstrate the ability of total-body multiparametric 18 F-FDG PET to quantitatively evaluate glucose metabolism using macroparametric quantification and assess specific glucose delivery and phosphorylation processes using microparametric quantification for studying recovery from coronavirus disease 2019 (COVID-19). Methods: The study included thirteen healthy subjects and twelve recovering COVID-19 subjects within eight weeks of confirmed diagnosis. Each subject had a dynamic 18 F-FDG scan on the uEXPLORER total-body PET/CT system for one hour. Semiquantitative standardized uptake value (SUV) and SUV ratio relative to blood (SUVR) were calculated for regions of interest (ROIs) in different organs to measure glucose utilization. Tracer kinetic modeling was performed to quantify microparametric rate constants K 1 and k 3 that characterize 18 F-FDG blood-to-tissue delivery and intracellular phosphorylation, respectively, and a macroparameter K i that represents 18 F-FDG net influx rate. Statistical tests were performed to examine differences between the healthy controls and recovering COVID-19 subjects. Impact of COVID-19 vaccination was investigated. We further generated parametric images to confirm the ROI-based analysis. Results: We detected no significant difference in lung SUV but significantly higher lung SUVR and K i in the recovering COVID-19 subjects, indicating an improved sensitivity of kinetic quantification for detecting the difference in glucose metabolism. A significant difference was also observed in the lungs with the phosphorylation rate k 3 , but not with the delivery rate K 1 , which suggests it is glucose phosphorylation, not glucose delivery, that drives the observed difference of glucose metabolism in the lungs. Meanwhile, there was no or little difference in bone marrow metabolism measured with SUV, SUVR and K i , but a significant increase in bone-marrow 18 F-FDG delivery rate K 1 in the COVID-19 group ( p < 0.05), revealing a difference of glucose delivery in this immune-related organ. The observed differences were lower or similar in vaccinated COVID-19 subjects as compared to unvaccinated ones. The organ ROI-based findings were further supported by parametric images. Conclusions: Higher lung glucose metabolism and bone-marrow glucose delivery were observed with total-body multiparametric 18 F-FDG PET in recovering COVID-19 subjects as compared to healthy subjects, which suggests continued inflammation due to COVID-19 during the early stages of recovery. Total-body multiparametric PET of 18 F-FDG delivery and metabolism can provide a more sensitive tool and more insights than conventional static whole-body 18 F-FDG imaging to evaluate metabolic changes in systemic diseases such as COVID-19.

AI-Based Automated Lipomatous Tumor Segmentation in MR Images: Ensemble Solution to Heterogeneous Data.

Deep learning (DL) has been proposed to automate image segmentation and provide accuracy, consistency, and efficiency. Accurate segmentation of lipomatous tumors (LTs) is critical for correct tumor radiomics analysis and localization. The major challenge of this task is data heterogeneity, including tumor morphological characteristics and multicenter scanning protocols. To mitigate the issue, we aimed to develop a DL-based Super Learner (SL) ensemble framework with different data correction and normalization methods. Pathologically proven LTs on pre-operative T1-weighted/proton-density MR images of 185 patients were manually segmented. The LTs were categorized by tumor locations as distal upper limb (DUL), distal lower limb (DLL), proximal upper limb (PUL), proximal lower limb (PLL), or Trunk (T) and grouped by 80%/9%/11% for training, validation and testing. Six configurations of correction/normalization were applied to data for fivefold-cross-validation trainings, resulting in 30 base learners (BLs). A SL was obtained from the BLs by optimizing SL weights. The performance was evaluated by dice-similarity-coefficient (DSC), sensitivity, specificity, and Hausdorff distance (HD95). For predictions of the BLs, the average DSC, sensitivity, and specificity from the testing data were 0.72 [Formula: see text] 0.16, 0.73 [Formula: see text] 0.168, and 0.99 [Formula: see text] 0.012, respectively, while for SL predictions were 0.80 [Formula: see text] 0.184, 0.78 [Formula: see text] 0.193, and 1.00 [Formula: see text] 0.010. The average HD95 of the BLs were 11.5 (DUL), 23.2 (DLL), 25.9 (PUL), 32.1 (PLL), and 47.9 (T) mm, whereas of SL were 1.7, 8.4, 15.9, 2.2, and 36.6 mm, respectively. The proposed method could improve the segmentation accuracy and mitigate the performance instability and data heterogeneity aiding the differential diagnosis of LTs in real clinical situations.