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Background: The application of semi-conductor detectors such as cadmium–zinc–telluride (CZT) in nuclear medicine improves extrinsic energy resolution and count sensitivity due to the direct conversion of gamma photons into electric signals. A 3D-ring pixelated CZT system named StarGuide was recently developed and implemented by GE HealthCare for SPECT acquisition. The system consists of 12 detector columns with seven modules of 16 × 16 CZT pixelated crystals, each with an integrated parallel-hole tungsten collimator. The axial coverage is 27.5 cm. The detector thickness is 7.25 mm, which allows acquisitions in the energy range [40–279] keV. Since there is currently no performance characterization specific to 3D-ring CZT SPECT systems, the National Electrical Manufacturers Association (NEMA) NU 1-2018 clinical standard can be tailored to these cameras. The aim of this study was to evaluate the performance of the SPECT/CT StarGuide system according to the NEMA NU 1-2018 clinical standard specifically adapted to characterize the new 3D-ring CZT. Results: Due to the integrated collimator, the system geometry and the pixelated nature of the detector, some NEMA tests have been adapted to the features of the system. The extrinsic measured energy resolution was about 5–6% for the tested isotopes (99mTc, 123I and 57Co); the maximum count rate was 760 kcps and the observed count rate at 20% loss was 917 kcps. The system spatial resolution in air extrapolated at 10 cm with 99mTc was 7.2 mm, while the SPECT spatial resolutions with scatter were 4.2, 3.7 and 3.6 mm in a central, radial and tangential direction respectively. Single head sensitivity value for 99mTc was 97 cps/MBq; with 12 detector columns, the system volumetric sensitivity reached 520 kcps MBq−1 cc−1. Conclusions: The performance tests of the StarGuide can be performed according to the NEMA NU 1-2018 standard with some adaptations. The system has shown promising results, particularly in terms of energy resolution, spatial resolution and volumetric sensitivity, potentially leading to higher quality clinical images. [ABSTRACT FROM AUTHOR]

This document is a letter to the editor discussing a rare manifestation of a VCP mutation. The case report describes a 58-year-old woman who experienced focal epilepsy followed by rapidly progressive frontotemporal dementia. The woman had a family history of dementia and behavioral changes. Neurological examination revealed frontal lobe syndrome, and brain imaging showed frontal lobe atrophy and hypometabolism. Genetic testing confirmed a mutation in the VCP gene. The authors emphasize the importance of genetic testing and imaging in diagnosing neurological disorders and highlight the heterogeneity of VCP-related disorders. [Extracted from the article]

Objectives: To use Dixon-MR images extracted from [18F]FDG-PET/MR scans to perform an automatic, volumetric segmentation and quantification of body composition in pediatric patients with lymphoma.Pediatric patients with lymphoma examined by [18F]FDG-PET/MR at diagnosis and restaging were included. At each time point, axial fat and water Dixon T1w images of the thighs were automatically segmented and muscle volume, subcutaneous, intramuscular, and intermuscular fat volume were quantified. The metabolic activity of the largest nodal lesion and of muscles and subcutaneous fat was recorded. The paired samples t-test and Spearman’s correlation coefficient were applied to evaluate potential differences between the two time points and the relationship between metabolic and body composition metrics, respectively. By logistic regression analysis, the prognostic role of the investigated variables was assessed. The applied significance level was p < 0.05 for all analyses.Thirty-seven patients (mean age ± SD 14 ± 3-years-old; 20 females) matched the inclusion criteria. After chemotherapy (interval between the two PET/MR scans, 56–80 days; median 65 days), muscle volume significantly decreased (629 ± 259 cm3 vs 567 ± 243 cm3, p < 0.001) while subcutaneous, intramuscular and intermuscular fat increased (476 ± 255 cm3 vs 607 ± 254 cm3, p < 0.001; 63 ± 20 cm3 vs 76 ± 26 cm3, p < 0.001; 58 ± 19 cm3 vs 71 ± 23 cm3, p < 0.001); the metabolic activity of the main nodal lesion, muscles, and subcutaneous fat significantly decreased (p < 0.05, each). None of the examined variables acted as predictors of the response to treatment (p = 0.283). A strong correlation between BMI and subcutaneous fat volume at diagnosis (r = 0.675, p < 0.001) and restaging (r = 0.600, p < 0.001) emerged.The proposed method demonstrated that pediatric patients with lymphoma undergo muscle loss and an increase of subcutaneous fat during treatment.The proposed automatic and volumetric MR-based assessment of body composition in children with lymphoma can be used to monitor the effect of chemotherapy and may guide tailored exercise programs during chemotherapy.T1w Dixon images can be used for the automatic segmentation and quantification of body composition.Muscle and subcutaneous fat volume do not act as predictors of the response to treatment in children with lymphoma.Chemotherapy induces changes in body composition in children with lymphoma.T1w Dixon images can be used for the automatic segmentation and quantification of body composition.Muscle and subcutaneous fat volume do not act as predictors of the response to treatment in children with lymphoma.Chemotherapy induces changes in body composition in children with lymphoma.Materials and methods: To use Dixon-MR images extracted from [18F]FDG-PET/MR scans to perform an automatic, volumetric segmentation and quantification of body composition in pediatric patients with lymphoma.Pediatric patients with lymphoma examined by [18F]FDG-PET/MR at diagnosis and restaging were included. At each time point, axial fat and water Dixon T1w images of the thighs were automatically segmented and muscle volume, subcutaneous, intramuscular, and intermuscular fat volume were quantified. The metabolic activity of the largest nodal lesion and of muscles and subcutaneous fat was recorded. The paired samples t-test and Spearman’s correlation coefficient were applied to evaluate potential differences between the two time points and the relationship between metabolic and body composition metrics, respectively. By logistic regression analysis, the prognostic role of the investigated variables was assessed. The applied significance level was p < 0.05 for all analyses.Thirty-seven patients (mean age ± SD 14 ± 3-years-old; 20 females) matched the inclusion criteria. After chemotherapy (interval between the two PET/MR scans, 56–80 days; median 65 days), muscle volume significantly decreased (629 ± 259 cm3 vs 567 ± 243 cm3, p < 0.001) while subcutaneous, intramuscular and intermuscular fat increased (476 ± 255 cm3 vs 607 ± 254 cm3, p < 0.001; 63 ± 20 cm3 vs 76 ± 26 cm3, p < 0.001; 58 ± 19 cm3 vs 71 ± 23 cm3, p < 0.001); the metabolic activity of the main nodal lesion, muscles, and subcutaneous fat significantly decreased (p < 0.05, each). None of the examined variables acted as predictors of the response to treatment (p = 0.283). A strong correlation between BMI and subcutaneous fat volume at diagnosis (r = 0.675, p < 0.001) and restaging (r = 0.600, p < 0.001) emerged.The proposed method demonstrated that pediatric patients with lymphoma undergo muscle loss and an increase of subcutaneous fat during treatment.The proposed automatic and volumetric MR-based assessment of body composition in children with lymphoma can be used to monitor the effect of chemotherapy and may guide tailored exercise programs during chemotherapy.T1w Dixon images can be used for the automatic segmentation and quantification of body composition.Muscle and subcutaneous fat volume do not act as predictors of the response to treatment in children with lymphoma.Chemotherapy induces changes in body composition in children with lymphoma.T1w Dixon images can be used for the automatic segmentation and quantification of body composition.Muscle and subcutaneous fat volume do not act as predictors of the response to treatment in children with lymphoma.Chemotherapy induces changes in body composition in children with lymphoma.Results: To use Dixon-MR images extracted from [18F]FDG-PET/MR scans to perform an automatic, volumetric segmentation and quantification of body composition in pediatric patients with lymphoma.Pediatric patients with lymphoma examined by [18F]FDG-PET/MR at diagnosis and restaging were included. At each time point, axial fat and water Dixon T1w images of the thighs were automatically segmented and muscle volume, subcutaneous, intramuscular, and intermuscular fat volume were quantified. The metabolic activity of the largest nodal lesion and of muscles and subcutaneous fat was recorded. The paired samples t-test and Spearman’s correlation coefficient were applied to evaluate potential differences between the two time points and the relationship between metabolic and body composition metrics, respectively. By logistic regression analysis, the prognostic role of the investigated variables was assessed. The applied significance level was p < 0.05 for all analyses.Thirty-seven patients (mean age ± SD 14 ± 3-years-old; 20 females) matched the inclusion criteria. After chemotherapy (interval between the two PET/MR scans, 56–80 days; median 65 days), muscle volume significantly decreased (629 ± 259 cm3 vs 567 ± 243 cm3, p < 0.001) while subcutaneous, intramuscular and intermuscular fat increased (476 ± 255 cm3 vs 607 ± 254 cm3, p < 0.001; 63 ± 20 cm3 vs 76 ± 26 cm3, p < 0.001; 58 ± 19 cm3 vs 71 ± 23 cm3, p < 0.001); the metabolic activity of the main nodal lesion, muscles, and subcutaneous fat significantly decreased (p < 0.05, each). None of the examined variables acted as predictors of the response to treatment (p = 0.283). A strong correlation between BMI and subcutaneous fat volume at diagnosis (r = 0.675, p < 0.001) and restaging (r = 0.600, p < 0.001) emerged.The proposed method demonstrated that pediatric patients with lymphoma undergo muscle loss and an increase of subcutaneous fat during treatment.The proposed automatic and volumetric MR-based assessment of body composition in children with lymphoma can be used to monitor the effect of chemotherapy and may guide tailored exercise programs during chemotherapy.T1w Dixon images can be used for the automatic segmentation and quantification of body composition.Muscle and subcutaneous fat volume do not act as predictors of the response to treatment in children with lymphoma.Chemotherapy induces changes in body composition in children with lymphoma.T1w Dixon images can be used for the automatic segmentation and quantification of body composition.Muscle and subcutaneous fat volume do not act as predictors of the response to treatment in children with lymphoma.Chemotherapy induces changes in body composition in children with lymphoma.Conclusions: To use Dixon-MR images extracted from [18F]FDG-PET/MR scans to perform an automatic, volumetric segmentation and quantification of body composition in pediatric patients with lymphoma.Pediatric patients with lymphoma examined by [18F]FDG-PET/MR at diagnosis and restaging were included. At each time point, axial fat and water Dixon T1w images of the thighs were automatically segmented and muscle volume, subcutaneous, intramuscular, and intermuscular fat volume were quantified. The metabolic activity of the largest nodal lesion and of muscles and subcutaneous fat was recorded. The paired samples t-test and Spearman’s correlation coefficient were applied to evaluate potential differences between the two time points and the relationship between metabolic and body composition metrics, respectively. By logistic regression analysis, the prognostic role of the investigated variables was assessed. The applied significance level was p < 0.05 for all analyses.Thirty-seven patients (mean age ± SD 14 ± 3-years-old; 20 females) matched the inclusion criteria. After chemotherapy (interval between the two PET/MR scans, 56–80 days; median 65 days), muscle volume significantly decreased (629 ± 259 cm3 vs 567 ± 243 cm3, p < 0.001) while subcutaneous, intramuscular and intermuscular fat increased (476 ± 255 cm3 vs 607 ± 254 cm3, p < 0.001; 63 ± 20 cm3 vs 76 ± 26 cm3, p < 0.001; 58 ± 19 cm3 vs 71 ± 23 cm3, p < 0.001); the metabolic activity of the main nodal lesion, muscles, and subcutaneous fat significantly decreased (p < 0.05, each). None of the examined variables acted as predictors of the response to treatment (p = 0.283). A strong correlation between BMI and subcutaneous fat volume at diagnosis (r = 0.675, p < 0.001) and restaging (r = 0.600, p < 0.001) emerged.The proposed method demonstrated that pediatric patients with lymphoma undergo muscle loss and an increase of subcutaneous fat during treatment.The proposed automatic and volumetric MR-based assessment of body composition in children with lymphoma can be used to monitor the effect of chemotherapy and may guide tailored exercise programs during chemotherapy.T1w Dixon images can be used for the automatic segmentation and quantification of body composition.Muscle and subcutaneous fat volume do not act as predictors of the response to treatment in children with lymphoma.Chemotherapy induces changes in body composition in children with lymphoma.T1w Dixon images can be used for the automatic segmentation and quantification of body composition.Muscle and subcutaneous fat volume do not act as predictors of the response to treatment in children with lymphoma.Chemotherapy induces changes in body composition in children with lymphoma.Clinical relevance statement: To use Dixon-MR images extracted from [18F]FDG-PET/MR scans to perform an automatic, volumetric segmentation and quantification of body composition in pediatric patients with lymphoma.Pediatric patients with lymphoma examined by [18F]FDG-PET/MR at diagnosis and restaging were included. At each time point, axial fat and water Dixon T1w images of the thighs were automatically segmented and muscle volume, subcutaneous, intramuscular, and intermuscular fat volume were quantified. The metabolic activity of the largest nodal lesion and of muscles and subcutaneous fat was recorded. The paired samples t-test and Spearman’s correlation coefficient were applied to evaluate potential differences between the two time points and the relationship between metabolic and body composition metrics, respectively. By logistic regression analysis, the prognostic role of the investigated variables was assessed. The applied significance level was p < 0.05 for all analyses.Thirty-seven patients (mean age ± SD 14 ± 3-years-old; 20 females) matched the inclusion criteria. After chemotherapy (interval between the two PET/MR scans, 56–80 days; median 65 days), muscle volume significantly decreased (629 ± 259 cm3 vs 567 ± 243 cm3, p < 0.001) while subcutaneous, intramuscular and intermuscular fat increased (476 ± 255 cm3 vs 607 ± 254 cm3, p < 0.001; 63 ± 20 cm3 vs 76 ± 26 cm3, p < 0.001; 58 ± 19 cm3 vs 71 ± 23 cm3, p < 0.001); the metabolic activity of the main nodal lesion, muscles, and subcutaneous fat significantly decreased (p < 0.05, each). None of the examined variables acted as predictors of the response to treatment (p = 0.283). A strong correlation between BMI and subcutaneous fat volume at diagnosis (r = 0.675, p < 0.001) and restaging (r = 0.600, p < 0.001) emerged.The proposed method demonstrated that pediatric patients with lymphoma undergo muscle loss and an increase of subcutaneous fat during treatment.The proposed automatic and volumetric MR-based assessment of body composition in children with lymphoma can be used to monitor the effect of chemotherapy and may guide tailored exercise programs during chemotherapy.T1w Dixon images can be used for the automatic segmentation and quantification of body composition.Muscle and subcutaneous fat volume do not act as predictors of the response to treatment in children with lymphoma.Chemotherapy induces changes in body composition in children with lymphoma.T1w Dixon images can be used for the automatic segmentation and quantification of body composition.Muscle and subcutaneous fat volume do not act as predictors of the response to treatment in children with lymphoma.Chemotherapy induces changes in body composition in children with lymphoma.Key Points: To use Dixon-MR images extracted from [18F]FDG-PET/MR scans to perform an automatic, volumetric segmentation and quantification of body composition in pediatric patients with lymphoma.Pediatric patients with lymphoma examined by [18F]FDG-PET/MR at diagnosis and restaging were included. At each time point, axial fat and water Dixon T1w images of the thighs were automatically segmented and muscle volume, subcutaneous, intramuscular, and intermuscular fat volume were quantified. The metabolic activity of the largest nodal lesion and of muscles and subcutaneous fat was recorded. The paired samples t-test and Spearman’s correlation coefficient were applied to evaluate potential differences between the two time points and the relationship between metabolic and body composition metrics, respectively. By logistic regression analysis, the prognostic role of the investigated variables was assessed. The applied significance level was p < 0.05 for all analyses.Thirty-seven patients (mean age ± SD 14 ± 3-years-old; 20 females) matched the inclusion criteria. After chemotherapy (interval between the two PET/MR scans, 56–80 days; median 65 days), muscle volume significantly decreased (629 ± 259 cm3 vs 567 ± 243 cm3, p < 0.001) while subcutaneous, intramuscular and intermuscular fat increased (476 ± 255 cm3 vs 607 ± 254 cm3, p < 0.001; 63 ± 20 cm3 vs 76 ± 26 cm3, p < 0.001; 58 ± 19 cm3 vs 71 ± 23 cm3, p < 0.001); the metabolic activity of the main nodal lesion, muscles, and subcutaneous fat significantly decreased (p < 0.05, each). None of the examined variables acted as predictors of the response to treatment (p = 0.283). A strong correlation between BMI and subcutaneous fat volume at diagnosis (r = 0.675, p < 0.001) and restaging (r = 0.600, p < 0.001) emerged.The proposed method demonstrated that pediatric patients with lymphoma undergo muscle loss and an increase of subcutaneous fat during treatment.The proposed automatic and volumetric MR-based assessment of body composition in children with lymphoma can be used to monitor the effect of chemotherapy and may guide tailored exercise programs during chemotherapy.T1w Dixon images can be used for the automatic segmentation and quantification of body composition.Muscle and subcutaneous fat volume do not act as predictors of the response to treatment in children with lymphoma.Chemotherapy induces changes in body composition in children with lymphoma.T1w Dixon images can be used for the automatic segmentation and quantification of body composition.Muscle and subcutaneous fat volume do not act as predictors of the response to treatment in children with lymphoma.Chemotherapy induces changes in body composition in children with lymphoma. [ABSTRACT FROM AUTHOR]

Therapeutic approaches to brain tumors remain a challenge, with considerable limitations regarding delivery of drugs. There has been renewed and increasing interest in translating the popular theranostic approach well known from prostate and neuroendocrine cancer to neurooncology. Although far from perfect, some of these approaches show encouraging preliminary results, such as for meningioma and leptomeningeal spread of certain pediatric brain tumors. In brain metastases and gliomas, clinical results have failed to impress. Perspectives on these theranostic approaches regarding meningiomas, brain metastases, gliomas, and common pediatric brain tumors will be discussed. For each tumor entity, the general context, an overview of the literature, and future perspectives will be provided. Ongoing studies will be discussed in the supplemental materials. As most theranostic agents are unlikely to cross the blood-brain barrier, the delivery of these agents will be dependent on the successful development and clinical implementation of techniques enhancing permeability and retention. Moreover, the international community should strive toward sufficiently large and randomized studies to generate high-level evidence on theranostic approaches with radioligand therapies for central nervous system tumors., (© 2024 by the Society of Nuclear Medicine and Molecular Imaging.)