Search

Objectives: To test the performance of a 3D convolutional neural network (CNN) in analysing brain [18F]DOPA PET/CT in order to identify patients with nigro-striatal neurodegeneration. We evaluated the robustness of the 3D CNN by testing it against a manual regional analysis of the striata by using a striatal-to-occipital ratio (SOR). Methods: We analyzed patients who had undergone [18F]DOPA PET/CT from 2016 to 2018. Two examiners interpreted PET/CT images as positive or negative. Only patients with at least 2 years of follow-up and an ascertained neurological diagnosis were included. A 3D CNN was developed to evaluate [18F]DOPA PET/CT and refine the diagnosis of movement disorder. This system required training and testing, which were carried out on 2/3 and 1/3 of patients, respectively. A regional analysis was also conducted by drawing region of interest on T1-weighted 3D MRI scans, on which the [18F]DOPA PET images were first co-registered. Results: Ninety-eight patients were enrolled: 43 presented nigro-striatal degeneration and 55 negative cases used as controls. After training on 69 patients, the diagnostic performance of the 3D CNN was then calculated in 29 patients. Sensitivity, specificity, negative predictive value, positive predictive value and accuracy were 100%, 89%, 100%, 85% and 93%, respectively. When we compared the 3D CNN results with the SOR analysis, we found that the two patients falsely classified as positive by the 3D CNN procedure showed SOR values ≤ 5th percentile of the negative cases' distribution. Conclusions: 3D CNNs are able to interpret [18F]DOPA PET/CT properly, revealing patients affected by Parkinson's disease. Key Points: •[18F]DOPA PET/CT is a sensitive diagnostic tool to identify patients with nigro-striatal neurodegeneration. • A semiquantitative evaluation of the images allows a more confident interpretation of the PET findings. • 3D convolutional neural network allows an accurate interpretation of 18F-DOPA PET/CT images, revealing patients affected by Parkinson's disease. [ABSTRACT FROM AUTHOR]

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]