Ultrashort Oncologic Whole-Body [18F]FDG Patlak Imaging Using LAFOV PET.

Methods to shorten [18F]FDG Patlak PET imaging procedures ranging from 65-90 to 20-30 min after injection, using a population-averaged input function (PIF) scaled to patient-specific image-derived input function (IDIF) values, were recently evaluated. The aim of the present study was to explore the feasibility of ultrashort 10-min [18F]FDG Patlak imaging at 55-65 min after injection using a PIF combined with direct Patlak reconstructions to provide reliable quantitative accuracy of lung tumor uptake, compared with a full-duration 65-min acquisition using an IDIF. Methods: Patients underwent a 65-min dynamic PET acquisition on a long-axial-field-of-view (LAFOV) Biograph Vision Quadra PET/CT scanner. Subsequently, direct Patlak reconstructions and image-based (with reconstructed dynamic images) Patlak analyses were performed using both the IDIF (time to relative kinetic equilibrium between blood and tissue concentration (t*) = 30 min) and a scaled PIF at 30-60 min after injection. Next, direct Patlak reconstructions were performed on the system console using only the last 10 min of the acquisition, that is, from 55 to 65 min after injection, and a scaled PIF using maximum crystal ring difference settings of both 85 and 322. Tumor lesion and healthy-tissue uptake was quantified and compared between the differently obtained parametric images to assess quantitative accuracy. Results: Good agreement was obtained between direct- and image-based Patlak analyses using the IDIF (t* = 30 min) and scaled PIF at 30-60 min after injection, performed using the different approaches, with no more than 8.8% deviation in tumor influx rate value (Ki ) (mean difference ranging from -0.0022 to 0.0018 mL/[min × g]). When direct Patlak reconstruction was performed on the system console, excellent agreement was found between the use of a scaled PIF at 30-60 min after injection versus 55-65 min after injection, with 2.4% deviation in tumor Ki (median difference, -0.0018 mL/[min × g]; range, -0.0047 to 0.0036 mL/[min × g]). For different maximum crystal ring difference settings using the scan time interval of 55-65 min after injection, only a 0.5% difference (median difference, 0.0000 mL/[min × g]; range, -0.0004 to 0.0013 mL/[min × g]) in tumor Ki was found. Conclusion: Ultrashort whole-body [18F]FDG Patlak imaging is feasible on an LAFOV Biograph Vision Quadra PET/CT system without loss of quantitative accuracy to assess lung tumor uptake compared with a full-duration 65-min acquisition. The ultrashort 10-min direct Patlak reconstruction with PIF allows for its implementation in clinical practice.

MRI-based Zero Echo Time and Black Bone Pseudo-CT Compared with Whole-Body CT to Detect Osteolytic Lesions in Multiple Myeloma.

Background MRI is highly sensitive for assessing bone marrow involvement in multiple myeloma (MM) but does not enable detection of osteolysis. Purpose To assess the diagnostic accuracy, repeatability, and reproducibility of pseudo-CT MRI sequences (zero echo time [ZTE], gradient-echo black bone [BB]) in detecting osteolytic lesions in MM using whole-body CT as the reference standard. Materials and Methods In this prospective study, consecutive patients were enrolled in our academic hospital between June 2021 and December 2022. Inclusion criteria were newly diagnosed MM, monoclonal gammopathy of undetermined significance at high risk for MM, or suspicion of progressive MM. Participants underwent ZTE and BB sequences covering the lumbar spine, pelvis, and proximal femurs as part of 3-T whole-body MRI examinations, as well as clinically indicated fluorine 18 fluorodeoxyglucose PET/CT examination within 1 month that included optimized whole-body CT. Ten bone regions and two scores (categorical score = presence/absence of osteolytic lesion; semiquantitative score = osteolytic lesion count) were assessed by three radiologists (two experienced and one unfamiliar with pseudo-CT reading) on the ZTE, BB, and whole-body CT images. The accuracy, repeatability, and reproducibility of categorical scores (according to Gwet agreement coefficients AC1 and AC2) and differences in semiquantitative scores were assessed at the per-sequence, per-region, and per-patient levels. Results A total of 47 participants (mean age, 67 years ± 11 [SD]; 27 male) were included. In experienced readers, BB and ZTE had the same high accuracy (98%) in the per-patient analysis, while BB accuracy ranged 83%-100% and ZTE accuracy ranged 74%-94% in the per-region analysis. An increase of false-negative (FN) findings in the spine ranging from +17% up to +23%, according to the lumbar vertebra, was observed using ZTE (P < .013). Regardless of the region (except coxal bones), differences in the BB score minus the ZTE score were positively skewed (P < .021). Regardless of the sequence or region, repeatability was very good (AC1 ≥0.87 for all), while reproducibility was at least good (AC2 ≥0.63 for all). Conclusion Both MRI-based ZTE and BB pseudo-CT sequences of the lumbar spine, pelvis, and femurs demonstrated high diagnostic accuracy in detecting osteolytic lesions in MM. Compared with BB, the ZTE sequence yielded more FN findings in the spine. ClinicalTrials.gov Identifier: NCT05381077 Published under a CC BY 4.0 license. Supplemental material is available for this article.

Deep learning model using planar whole-body bone scintigraphy for diagnosis of skull base invasion in patients with nasopharyngeal carcinoma.

PURPOSE: This study assesses the reliability of deep learning models based on planar whole-body bone scintigraphy for diagnosing Skull base invasion (SBI) in nasopharyngeal carcinoma (NPC) patients. METHODS: In this multicenter study, a deep learning model was developed using data from one center with a 7:3 allocation to training and internal test sets, to diagnose SBI in patients newly diagnosed with NPC using planar whole-body bone scintigraphy. Patients were diagnosed based on a composite reference standard incorporating radiologic and follow-up data. Ten different convolutional neural network (CNN) models were applied to both whole-image and partial-image input modes to determine the optimal model for each analysis. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), calibration, decision curve analysis (DCA), and compared with expert assessments by two nuclear medicine physicians. RESULTS: The best-performing model using partial-body input achieved AUCs of 0.80 (95% CI: 0.73, 0.86) in the internal test set, 0.84 (95% CI: 0.77, 0.91) in the external cohort, and 0.78 (95% CI: 0.73, 0.83) in the treatment test cohort. Calibration curves and DCA confirmed the models' excellent discrimination, calibration, and potential clinical utility across internal and external datasets. The AUCs of both nuclear medicine physicians were lower than those of the best-performing deep learning model in external test set (AUC: 0.75 vs. 0.77 vs. 0.84). CONCLUSION: Deep learning models utilizing partial-body input from planar whole-body bone scintigraphy demonstrate high discriminatory power for diagnosing SBI in NPC patients, surpassing experienced nuclear medicine physicians.

Trauma and 'Whole' Body Computed Tomography: Role, Protocols, Appropriateness, and Evidence to Support its Use and When.

Imaging plays a crucial role in the immediate evaluation of the trauma patient, particularly using multi-detector computed tomography (CT), and especially in moderately to severely injured trauma patients. There are specific areas of relative consensus, while other aspects of whole-body computed tomography (WB-CT) use remain controversial and are subject to opinion/debate based on the current literature. Even a few hours of a delayed diagnosis may result in a detrimental outcome for the patient. One must utilize all the tools available to enhance the interpretation of images. It is also important to recognize imaging pitfalls and artifacts to avoid unnecessary intervention.

Diagnostic Value of Whole-Body MRI in Pediatric Patients with Suspected Rheumatic Diseases.

Background and Objectives: The diagnosis of rheumatic diseases in children is challenging and requires the use of advanced imaging examinations such as whole-body magnetic resonance imaging (MRI). Whole-body MRI allows visualization of bone marrow edema (BME), muscle edema, joint effusion and changes in the soft tissues surrounding the joints. The aim of this study was to collect and compare whole-body MRI findings, laboratory results and clinical manifestations of pediatric patients with suspected rheumatic disease. Materials and methods: In this retrospective single-center study, 33 patients who underwent whole-body MRI were included. Their age ranged from 9 to 17 years, and 24 (72.73%) of the patients were female. Patients were diagnosed as follows: juvenile idiopathic arthritis (27.27%), juvenile idiopathic inflammatory myopathies (21.21%), chronic nonbacterial osteomyelitis (21.21%) and other medical conditions (30.30%), such as arthritis associated with infection, scleroderma, Takayasu arteritis, polyarteritis nodosa and joint damage. Results: The most common symptom reported by 26 (79.79%) patients was pain. On physical examination, the limitation of joint mobility was examined in 17 (51.51%), swelling of the joints was observed in 12 (36.36%) patients and decreased muscle strength was noticed in 11 (33.33%) patients. An increase in the C-reactive protein (12%), erythrocyte sedimentation rate (9%), leukocyte count (9%) and creatine kinase (CK) (18%) was observed. Whole-body MRI revealed myositis (30%), joint effusion (27%) and BME (24%). The statistical analysis showed a significant relationship between myositis and the elevated CK level (p < 0.05). Conclusions: The most common symptom in the studied population was pain, while the limitation of joint mobility was found in more than half of patients. Myositis was the most commonly imaged lesion on the whole-body MRI and it was related to an increase in the CK level.

Clinical performance of deep learning-enhanced ultrafast whole-body scintigraphy in patients with suspected malignancy.

BACKGROUND: To evaluate the clinical performance of two deep learning methods, one utilizing real clinical pairs and the other utilizing simulated datasets, in enhancing image quality for two-dimensional (2D) fast whole-body scintigraphy (WBS). METHODS: A total of 83 patients with suspected bone metastasis were retrospectively enrolled. All patients underwent single-photon emission computed tomography (SPECT) WBS at speeds of 20 cm/min (1x), 40 cm/min (2x), and 60 cm/min (3x). Two deep learning models were developed to generate high-quality images from real and simulated fast scans, designated 2x-real and 3x-real (images from real fast data) and 2x-simu and 3x-simu (images from simulated fast data), respectively. A 5-point Likert scale was used to evaluate the image quality of each acquisition. Accuracy, sensitivity, specificity, and the area under the curve (AUC) were used to evaluate diagnostic efficacy. Learned perceptual image patch similarity (LPIPS) and the Fréchet inception distance (FID) were used to assess image quality. Additionally, the count-level consistency of WBS was compared between the two models. RESULTS: Subjective assessments revealed that the 1x images had the highest general image quality (Likert score: 4.40 ± 0.45). The 2x-real, 2x-simu and 3x-real, 3x-simu images demonstrated significantly better quality than the 2x and 3x images (Likert scores: 3.46 ± 0.47, 3.79 ± 0.55 vs. 2.92 ± 0.41, P < 0.0001; 2.69 ± 0.40, 2.61 ± 0.41 vs. 1.36 ± 0.51, P < 0.0001), respectively. Notably, the quality of the 2x-real images was inferior to that of the 2x-simu images (Likert scores: 3.46 ± 0.47 vs. 3.79 ± 0.55, P = 0.001). The diagnostic efficacy for the 2x-real and 2x-simu images was indistinguishable from that of the 1x images (accuracy: 81.2%, 80.7% vs. 84.3%; sensitivity: 77.27%, 77.27% vs. 87.18%; specificity: 87.18%, 84.63% vs. 87.18%. All P > 0.05), whereas the diagnostic efficacy for the 3x-real and 3x-simu was better than that for the 3x images (accuracy: 65.1%, 66.35% vs. 59.0%; sensitivity: 63.64%, 63.64% vs. 64.71%; specificity: 66.67%, 69.23% vs. 55.1%. All P < 0.05). Objectively, both the real and simulated models achieved significantly enhanced image quality from the accelerated scans in the 2x and 3x groups (FID: 0.15 ± 0.18, 0.18 ± 0.18 vs. 0.47 ± 0.34; 0.19 ± 0.23, 0.20 ± 0.22 vs. 0.98 ± 0.59. LPIPS: 0.17 ± 0.05, 0.16 ± 0.04 vs. 0.19 ± 0.05; 0.18 ± 0.05, 0.19 ± 0.05 vs. 0.23 ± 0.04. All P < 0.05). The count-level consistency with the 1x images was excellent for all four sets of model-generated images (P < 0.0001). CONCLUSIONS: Ultrafast 2x speed (real and simulated) images achieved comparable diagnostic value to that of standardly acquired images, but the simulation algorithm does not necessarily reflect real data.

Early treatment response assessment with [177Lu]PSMA whole-body-scintigraphy compared to interim PSMA-PET.

BACKGROUND: Prostate-specific membrane antigen positron emission tomography (PSMA-PET) is an essential tool for patient selection before radioligand therapy (RLT). Interim-staging with PSMA-PET during RLT allows for therapy monitoring. However, its added value over post-treatment imaging is poorly elucidated. The aim of this study was to compare early treatment response assessed by post-therapeutic whole-body scans (WBS) with interim-staging by PSMA-PET after 2 cycles in order to prognosticate OS. METHODS: Men with metastasized castration-resistant PC (mCRPC) who had received at least two cycles of RLT, and interim PSMA-PET were evaluated retrospectively. PROMISE V2 framework was used to categorize PSMA expression and assess response to treatment. Response was defined as either disease control rate (DCR) for responders or progression for non-responders. RESULTS: A total of 188 men with mCRPC who underwent RLT between February 2015 and December 2021 were included. The comparison of different imaging modalities revealed a strong and significant correlation with Cramer V test: e.g. response on WBS during second cycle compared to interim PET after two cycles of RLT (cφ = 0.888, P < 0.001, n = 188). The median follow-up time was 14.7 months (range: 3-63 months; 125 deaths occurred). Median overall survival (OS) time was 14.5 months (95% CI: 11.9-15.9). In terms of OS analysis, early progression during therapy revealed a significantly higher likelihood of death: e.g. second cycle WBS (15 vs. 25 months, P < 0.001) with a HR of 2.81 (P < 0.001) or at PET timepoint after 2 cycles of RLT (11 vs. 24 months, P < 0.001) with a HR of 3.5 (P < 0.001). For early biochemical response, a PSA decline of at least 50% after two cycles of RLT indicates a significantly lower likelihood of death (26 vs. 17 months, P < 0.001) with a HR of 0.5 (P < 0.001). CONCLUSION: Response assessment of RLT by WBS and interim PET after two cycles of RLT have high congruence and can identify patients at risk of poor outcome. This indicates that interim PET might be omitted for response assessment, but future trials corroborating these findings are warranted.

Refining penalty parameter selection in whole-body PET image reconstruction for lung cancer patients using the cross-validation log-likelihood method.

Objective.Penalty parameters in penalized likelihood positron emission tomography (PET) reconstruction are typically determined empirically. The cross-validation log-likelihood (CVLL) method has been introduced to optimize these parameters by maximizing a CVLL function, which assesses the likelihood of reconstructed images using one subset of a list-mode dataset based on another subset. This study aims to validate the efficacy of the CVLL method in whole-body imaging for cancer patients using a conventional clinical PET scanner.Approach.Fifteen lung cancer patients were injected with 243.7 ± 23.8 MBq of [18F]FDG and underwent a 22 min PET scan on a Biograph mCT PET/CT scanner, starting at 60 ± 5 min post-injection. The PET list-mode data were partitioned by subsampling without replacement, with 20 minutes of data for image reconstruction using an in-house ordered subset expectation maximization algorithm and the remaining 2 minutes of data for cross-validation. Two penalty parameters, penalty strengthßand Fair penalty function parameterδ, were subjected to optimization. Whole-body images were reconstructed, and CVLL values were computed across various penalty parameter combinations. The optimal image corresponding to the maximum CVLL value was selected by a grid search for each patient.Main results.Theδvalue required to maximize the CVLL value was notably small (⩽10-6in this study). The influences of voxel size and scan duration on image optimization were investigated. A correlation analysis revealed a significant inverse relationship between optimalßand scan count level, with a correlation coefficient of -0.68 (p-value = 3.5 × 10-5). The optimal images selected by the CVLL method were compared with those chosen by two radiologists based on their diagnostic preferences. Differences were observed in the selection of optimal images.Significance.This study demonstrates the feasibility of incorporating the CVLL method into routine imaging protocols, potentially allowing for a wide range of combinations of injected radioactivity amounts and scan durations in modern PET imaging.

RF coil that minimizes electronic components while enhancing performance for rodent MRI at 7 Tesla.

This study introduces a novel volume coil design that features two slotted end-plates connected by six rungs, resembling the traditional birdcage coil. The end rings are equipped with six evenly distributed circular slots, inspired by Mansfield's cavity resonator theory, which suggests that circular slots can generate a baseline resonant frequency. One notable advantage of this proposed coil design is its reduced reliance on electronic components compared to other volume coils, making it more efficient. Additionally, the dimensions of the coil can be theoretically computed in advance, enhancing its practicality. To evaluate the performance and safety of the coil, electromagnetic field and specific absorption rate simulations were simulated using a cylindrical saline phantom and the finite element method. Furthermore, a transceiver coil prototype optimized for 7 Tesla and driven in quadrature was constructed, enabling whole-body imaging of rats. The resonant frequency of the coil prototype obtained through experimental measurements closely matched the theoretical frequency derived from Mansfield's theory. To validate the coil design, phantom images were acquired to demonstrate its viability and assess its performance. These images also served to validate the magnetic field simulations. The experimental results aligned well with the simulation findings, confirming the reliability of the proposed coil design. Importantly, the prototype coil showcased significant improvements over a similarly-sized birdcage coil, indicating its potential for enhanced performance. The noise figure was lower in the prototype versus the birdcage coil (NFbirdcage-NFslotcage= 0.7). Phantom image data were also used to compute the image SNR, giving SNRslotcage/SNRbirdcage= 34.36/24.34. By proving the feasibility of the coil design through successful rat whole-body imaging, the study provides evidence supporting its potential as a viable option for high-field MRI applications on rodents.

Dose estimation in patients from different protocols of 18F-FDG PET/CT studies and analysis of optimization strategies.

This study aimed to evaluate the dose in different protocols of 18F-2-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (PET/CT) procedure. The retrospective study involves 207 patients with confirmed malignancies who underwent PET/CT. Effective dose (E) from PET was estimated based on injected activity and dose coefficient as per International Commission on Radiation Protection (ICRP) 128. Estimation of E from CT was done utilizing the dose length product (DLP) method and conversion factors as per ICRP 102. There was a significant statistical difference observed in E between different PET/CT protocols (P < .001). E of PET in the whole body (WB) was found to be 4.9 ± 0.9 mSv, whereas mean volume computed tomography dose indexvol, DLP, and E of CT in WB were 7.0 ± 0.2 mGy, 674.3 ± 80.7 mGy.cm, and 10.1 ± 1.2 mSv, respectively. No linear correlation was seen between the size-specific dose estimate and E of CT (r = -0.003; P = .978). The total mean E in WB PET/CT was 17.0 ± 1.7 mSv. CT dose was contributing more than PET dose in all protocols except brain PET/CT. Optimization strategies can be evaluated only if monitored periodically.

[11C]Methionine PET vs. [18F]Fluorodeoxyglucose PET Whole-body Imaging to Determine the Extent of Methionine-addiction Compared to Glucose-addiction of Primary and Metastatic Cancer of the Trunk in Patients.

BACKGROUND/AIM: Positron emission tomography (PET) is an important imaging modality, especially in oncology. [18F]fluorodeoxyglucose PET (FDG-PET) is the most used cancer PET imaging. However, since the elevated glucose use by cancers, termed the Warburg effect, is usually only moderate, FDG often does not provide a strong or well-delineated signal. Malignancies have a stronger addiction to methionine, known as the Hoffman effect, and thus [11C]methionine PET (MET-PET) has demonstrated superiority over FDG-PET in gliomas and other brain tumors. Our team is pioneering the use of MET-PET for tumors of the trunk for both better detection of cancer and to determine candidates for methionine-restriction therapy. The present study provides examples of cancers of organs in the trunk in which MET-PET outperforms FDG-PET in detecting and delineating primary and metastatic cancer. PATIENTS AND METHODS: In all cases, MET-PET and FDG-PET were performed simultaneously. An evaluation of the images was conducted by a nuclear medicine physician. RESULTS: Four cases, including prostate, bladder, esophageal, and breast cancer demonstrated the superiority of MET-PET compared to FDG-PET. CONCLUSION: MET-PET can out-perform FDG PET for accurate detection of primary and metastatic cancer in the trunk and can determine the extent of methionine addiction of cancer, thereby indicating whether cancer patients can benefit from methionine-restriction therapy.

Research Note: A deep learning method segments chicken keel bones from whole-body X-ray images.

Most commercial laying hens suffer from sternum (keel) bone damage including deviations and fractures. X-raying hens, followed by segmenting and assessing the keel bone, is a key to automating the monitoring of keel bone condition. The aim of the current work is to train a deep learning model to segment the keel bone out of whole-body x-ray images. We obtained full-body x-ray images of laying hens (n = 1,051) and manually drew the outline of the keel bone on each image. Using the annotated images, a U-net model was then trained to segment the keel bone. The proposed model was evaluated using 5-fold cross validation. We obtained high segmentation accuracy (Dice coefficients of 0.88-0.90) repeatably over several validation folds. In conclusion, automatic segmentation of the keel bone from full-body x-ray images is possible with good accuracy. Segmentation is a requirement for automated measurements of keel geometry and density, which can subsequently be connected to susceptibility to keel deviations and fractures.

Deep learning applications for quantitative and qualitative PET in PET/MR: technical and clinical unmet needs.

We aim to provide an overview of technical and clinical unmet needs in deep learning (DL) applications for quantitative and qualitative PET in PET/MR, with a focus on attenuation correction, image enhancement, motion correction, kinetic modeling, and simulated data generation. (1) DL-based attenuation correction (DLAC) remains an area of limited exploration for pediatric whole-body PET/MR and lung-specific DLAC due to data shortages and technical limitations. (2) DL-based image enhancement approximating MR-guided regularized reconstruction with a high-resolution MR prior has shown promise in enhancing PET image quality. However, its clinical value has not been thoroughly evaluated across various radiotracers, and applications outside the head may pose challenges due to motion artifacts. (3) Robust training for DL-based motion correction requires pairs of motion-corrupted and motion-corrected PET/MR data. However, these pairs are rare. (4) DL-based approaches can address the limitations of dynamic PET, such as long scan durations that may cause patient discomfort and motion, providing new research opportunities. (5) Monte-Carlo simulations using anthropomorphic digital phantoms can provide extensive datasets to address the shortage of clinical data. This summary of technical/clinical challenges and potential solutions may provide research opportunities for the research community towards the clinical translation of DL solutions.

Update on MRI in Rheumatic Diseases.

Over the past decade, MRI has significantly advanced the diagnosis of rheumatic disease in both adults and juveniles. In this article, the authors present an update on MRI applications in rheumatology, based on a review of the most recent publications. New developments in adults related to, among others, axial spondyloarthritis, peripheral arthritis, and the whole body-MRI (WB-MRI) are presented. In juveniles, this update addresses the latest advancements in diagnostic MRI of peripheral joints, followed by MRI of the axial skeleton and implementation of the WB-MRI for the screening of inflammation. The authors also discuss topics of interest concerning contrast-enhanced MRI examinations in children.

Whole-Body Magnetic Resonance Imaging in Rheumatology.

This review focuses on the most frequent whole-body MRI applications in patients with rheumatological pathologies, for which this tool can be helpful to both radiologists and clinicians. It reports technical aspects of the acquisition of both 1.5 and 3.0 T scanners. The article lists the main findings that help radiologists during the evaluation of a specific pathology, both in the diagnostic phase and during follow-up.

DCE-MRI to distinguish all monoclonal plasma cell disease stages and correlation with diffusion-weighted MRI/PET-based biomarkers in a hybrid simultaneous whole body-2-[18F]FDG-PET/MRI imaging approach.

BACKGROUND: Dynamic contrast-enhanced-MRI (DCE-MRI) is able to study bone marrow angiogenesis in patients with multiple myeloma (MM) and asymptomatic precursor diseases but its role in the management of MM has not yet been established. The aims of this prospective study was to compare DCE-MRI-based parameters between all monoclonal plasma cell disease stages in order to find out discriminatory parameters and to seek correlations with other diffusion-weighted MRI and positron emission tomography (PET)-based biomarkers in a hybrid simultaneous whole-body-2-[18F]fluorodeoxyglucose (FDG)-PET/MRI (WB-2-[18F]FDG-PET/MRI) imaging approach. METHODS: Patients with newly diagnosed Monoclonal gammopathy of undetermined significance (MGUS), smoldering multiple myeloma (SMM) or symptomatic MM according to international myeloma working group and underwent WB-2-[18F]FDG-PET/MRI imaging including bone marrow DCE sequences at the Nantes University Hospital were prospectively enrolled in this study before receiving treatment. RESULTS: One hundred and sixty-seven patients (N = 167, mean age: 64 years ± 11 [Standard deviation], 66 males) were considered for the analysis. DCE-MRI-based Peak Enhancement Intensity (PEI), Time to PEI (TPEI) and their maximum intensity time ratio (MITR: PEI/TPEI) values were significantly different between the different monoclonal plasma cell disease stages, PEI values increasing and TPEI values decreasing progressively along the spectrum of plasma cell disorders, from MGUS stage to symptomatic multiple myeloma. PEI values were significantly higher in patients with diffuse bone marrow involvement (either in PET or in MRI images) than in those without diffuse bone marrow involvement, unlike TPEI values. PEI and TPEI values were not significantly different between patients with or without focal bone lesions. CONCLUSION: Different DCE-MRI-based parameters (PEI, TPEI, MITR) could significantly differentiate all monoclonal plasma cell disease stages and complemented conventional MRI and PET-based biomarkers.

Feasibility of whole-body MRI for cancer screening in children and young people with ataxia telangiectasia: A mixed methods cross-sectional study.

BACKGROUND/OBJECTIVES: Ataxia telangiectasia (A-T) is an inherited multisystem disorder with increased sensitivity to ionising radiation and elevated cancer risk. Although other cancer predisposition syndromes have established cancer screening protocols, evidence-based guidelines for cancer screening in A-T are lacking. This study sought to assess feasibility of a cancer screening protocol based on whole-body MRI (WB-MRI) in children and young people with A-T. DESIGN/METHODS: Children and young people with A-T were invited to undergo a one-off non-sedated 3-Tesla WB-MRI. Completion rate of WB-MRI was recorded and diagnostic image quality assessed by two experienced radiologists, with pre-specified success thresholds for scan completion of >50% participants and image quality between acceptable to excellent in 65% participants. Positive imaging findings were classified according to the ONCO-RADS system. Post-participation interviews were performed with recruited families to assess the experience of participating and feelings about waiting for, and communication of, the findings of the scan. RESULTS: Forty-six children and young people with A-T were identified, of which 36 were eligible to participate, 18 were recruited and 16 underwent WB-MRI. Nineteen parents participated in interviews. Fifteen participants (83%) completed the full WB-MRI scan protocol. The pre-specified image quality criterion was achieved with diagnostic images obtained in at least 93% of each MRI sequence. Non-malignant scan findings were present in 4 (25%) participants. Six themes were identified from the interviews: (1) anxiety is a familiar feeling, (2) the process of MRI scanning is challenging for some children and families, (3) preparation is essential to reduce stress, (4) WB-MRI provides the reassurance about the physical health that families need, (5) WB-MRI experience turned out to be a positive experience and (6) WB-MRI allows families to be proactive. CONCLUSION: This study shows that WB-MRI for cancer screening is feasible and well-accepted by children and young people with A-T and their families.

Fat Fraction Extracted from Whole-Body Magnetic Resonance (WB-MR) in Bone Metastatic Prostate Cancer: Intra- and Inter-Reader Agreement of Single-Slice and Volumetric Measurements.

BACKGROUND: This study evaluates the repeatability and reproducibility of fat-fraction percentage (FF%) in whole-body magnetic resonance imaging (WB-MRI) of prostate cancer patients with bone metastatic hormone naive disease. METHODS: Patients were selected from the database of a prospective phase-II trial. The treatment response was assessed using the METastasis Reporting and Data System for Prostate (MET-RADS-P). Two operators identified a Small Active Lesion (SAL, <10 mm) and a Large Active Lesion (LAL, ≥10 mm) per patient, performing manual segmentation of lesion volume and the largest cross-sectional area. Measurements were repeated by one operator after two weeks. Intra- and inter-reader agreements were assessed via Interclass Correlation Coefficient (ICC) on first-order radiomics features. RESULTS: Intra-reader ICC showed high repeatability for both SAL and LAL in a single slice (SS) and volumetric (VS) measurements with values ranging from 0.897 to 0.971. Inter-reader ICC ranged from 0.641 to 0.883, indicating moderate to good reproducibility. Spearman's rho analysis confirmed a strong correlation between SS and VS measurements for SAL (0.817) and a moderate correlation for LAL (0.649). Both intra- and inter-rater agreement exceeded 0.75 for multiple first-order features across lesion sizes. CONCLUSION: This study suggests that FF% measurements are reproducible, particularly for larger lesions in both SS and VS assessments.

Whole-body MRI in oncology: acquisition protocols, current guidelines, and beyond.

Acknowledging the increasing use of whole-body magnetic resonance imaging (WB-MRI) in the oncological setting, we conducted a narrative review focusing on practical aspects of the examination and providing a synthesis of various acquisition protocols described in the literature. Firstly, we addressed the topic of patient preparation, emphasizing methods to enhance examination acceptance. This included strategies for reducing anxiety and patient distress, improving staff-patient interactions, and increasing overall patient comfort. Secondly, we analysed WB-MRI acquisition protocols recommended in existing imaging guidelines, such as MET-RADS-P, MY-RADS, and ONCO-RADS, and provided an overview of acquisition protocols reported in the literature regarding other expanding applications of WB-MRI in oncology, in patients with breast cancer, ovarian cancer, melanoma, colorectal and lung cancer, lymphoma, and cancers of unknown primary. Finally, we suggested possible acquisition parameters for whole-body images across MR systems from three different vendors.