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

Bibliographic Details
Title: A whole-body diffusion MRI normal atlas: development, evaluation and initial use
Authors: Therese Sjöholm, Sambit Tarai, Filip Malmberg, Robin Strand, Alexander Korenyushkin, Gunilla Enblad, Håkan Ahlström, Joel Kullberg
Source: Cancer Imaging, Vol 23, Iss 1, Pp 1-15 (2023)
Publisher Information: BMC, 2023.
Publication Year: 2023
Collection: LCC:Medical physics. Medical radiology. Nuclear medicine
LCC:Neoplasms. Tumors. Oncology. Including cancer and carcinogens
Subject Terms: Whole-body DWI, ADC, Normal atlas, Voxel-wise analysis, Precision, Lymphoma, Medical physics. Medical radiology. Nuclear medicine, R895-920, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
More Details: Abstract 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 ADCmean 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 ADCmean varied depending on tissue assessed (4–48% at 1.5T, 6–70% at 3T). Scanner differences in ADCmean 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.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 1470-7330
Relation: https://doaj.org/toc/1470-7330
DOI: 10.1186/s40644-023-00603-5
Access URL: https://doaj.org/article/2e4d7e53c4a2448cb8072a84542c6ac9
Accession Number: edsdoj.2e4d7e53c4a2448cb8072a84542c6ac9
Database: Directory of Open Access Journals
More Details
ISSN:14707330
DOI:10.1186/s40644-023-00603-5
Published in:Cancer Imaging
Language:English