统计图谱可以提供健康志愿者和/或患者的基于人口的描述，并可用于区域和体素分析。本研究旨在开发1.5T和3T扫描的健康志愿者的全身扩散图谱。进一步的目标包括通过建立健康组织的全身明显扩散系数（ADC）值并将健康组织偏差纳入自动肿瘤分割任务的评估中。通过多站全身扩散加权成像（DWI）和水-脂肪磁共振成像（MRI）获得了健康志愿者（n = 45）的数据，其中1.5T（n = 38）和/或3T（n = 29）进行了测试再测成像。使用变形图像配准，将整个身体的MRI数据进行配准并组成正常图谱。手动测量了十个组织的健康组织ADCmean，评估了测试再测可重复性系数（%RC）以及年龄、性别和扫描仪的影响。使用正常图谱进行基于体素的全身分析，通过ADC相关性分析和自动肿瘤分割任务进行研究。对于后者，将具有和不具有关于健康组织偏差信息的淋巴瘤患者的MRI扫描（n = 40）输入到3D U-Net体系结构中。 在1.5T和3T分别创建了根据性别和体重指数（BMI）分层的全身高b值DWI和ADC正常图谱。在1.5T和3T，健康组织ADCmean的%RC在所评估的组织上有所不同（1.5T为4-48%，3T为6-70%）。通过对双重扫描的受试者进行布兰德-奥特曼（Bland-Altman）分析，可视化了ADCmean在扫描仪之间的差异。在1.5T，肝脏、肌肉和骨骼的性别差异可测量，在3T，肌肉的性别差异可测量。基于兴趣区（VOI）的多元线性回归和正常图谱空间中的基于体素的相关性显示，年龄与1.5T的肝脏和骨骼的ADC呈负相关，与1.5T和3T的脑组织呈正相关。在自动肿瘤分割任务中添加关于健康组织偏差的体素信息可以在分割指标Dice分数、敏感性和精度方面获得数值改善。 在1.5T和3T分别创建了全身DWI和ADC正常图谱，并应用于全身基于体素的分析。 © 2023. 国际癌症影像学会（ICIS）。

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.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.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.Whole-body DWI and ADC normal atlases were created at 1.5T and 3T, and applied in whole-body voxel-wise analyses.© 2023. International Cancer Imaging Society (ICIS).