A whole-body diffusion MRI normal atlas: development, evaluation and initial use

• Published in: Cancer imaging Vol. 23; no. 1; pp. 1 - 15
• Main Authors: Sjöholm, Therese, Tarai, Sambit, Malmberg, Filip, Strand, Robin, Korenyushkin, Alexander, Enblad, Gunilla, Ahlström, Håkan, Kullberg, Joel
• Format: Journal Article
• Language: English
• Published: London BioMed Central Ltd 14.09.2023; BioMed Central; BMC
• Subjects: ADC; Age factors; Algorithms; Automation; Body fat; Body image; Body mass index; Body size; Cancer; Contraindications; Correlation analysis; Deviation; Diffusion coefficient; Disease; Drunk driving; Ethics; Evaluation; Females; Formability; Image registration; Image segmentation; Liver; Lymphoma; Lymphomas; Magnetic resonance imaging; Males; Medical imaging; Medical imaging equipment; Muscles; Normal atlas; Patients; Precision; Registration; Scanners; Self image; Statistical analysis; Tumors; Voxel-wise analysis; Whole-body DWI
• ISSN: 1470-7330; 1740-5025; 1470-7330
• DOI: 10.1186/s40644-023-00603-5

Background Statistical atlases can provide population-based descriptions of healthy volunteers and/or patients and can be used for region- and voxel-based analysis. This work aims to develop whole-body diffusion atlases of healthy volunteers scanned at 1.5T and 3T. Further aims include evaluating the atlases by establishing whole-body Apparent Diffusion Coefficient (ADC) values of healthy tissues and including healthy tissue deviations in an automated tumour segmentation task. Methods Multi-station whole-body Diffusion Weighted Imaging (DWI) and water-fat Magnetic Resonance Imaging (MRI) of healthy volunteers (n = 45) were acquired at 1.5T (n = 38) and/or 3T (n = 29), with test-retest imaging for five subjects per scanner. Using deformable image registration, whole-body MRI data was registered and composed into normal atlases. Healthy tissue ADC.sub.mean was manually measured for ten tissues, with test-retest percentage Repeatability Coefficient (%RC), and effect of age, sex and scanner assessed. Voxel-wise whole-body analyses using the normal atlases were studied with ADC correlation analyses and an automated tumour segmentation task. For the latter, lymphoma patient MRI scans (n = 40) with and without information about healthy tissue deviations were entered into a 3D U-Net architecture. Results Sex- and Body Mass Index (BMI)-stratified whole-body high b-value DWI and ADC normal atlases were created at 1.5T and 3T. %RC of healthy tissue ADC.sub.mean varied depending on tissue assessed (4-48% at 1.5T, 6-70% at 3T). Scanner differences in ADC.sub.mean were visualised in Bland-Altman analyses of dually scanned subjects. Sex differences were measurable for liver, muscle and bone at 1.5T, and muscle at 3T. Volume of Interest (VOI)-based multiple linear regression, and voxel-based correlations in normal atlas space, showed that age and ADC were negatively associated for liver and bone at 1.5T, and positively associated with brain tissue at 1.5T and 3T. Adding voxel-wise information about healthy tissue deviations in an automated tumour segmentation task gave numerical improvements in the segmentation metrics Dice score, sensitivity and precision. Conclusions Whole-body DWI and ADC normal atlases were created at 1.5T and 3T, and applied in whole-body voxel-wise analyses. Keywords: Whole-body DWI, ADC, Normal atlas, Voxel-wise analysis, Precision, Lymphoma, Automated segmentation