Using UK Biobank data to establish population-specific atlases from whole body MRI

TL;DR

This paper presents a pipeline to create standardized, population-specific whole-body MRI atlases from UK Biobank data, capturing anatomical variability and disease-related differences, to aid medical research and diagnostics.

Contribution

The authors develop a novel pipeline for generating high-quality, realistic whole-body atlases from heterogeneous datasets, including probabilistic maps of fat and organ distributions, publicly available for research.

Findings

Created six healthy population atlases from UK Biobank data

Generated probabilistic atlases for fat and five abdominal organs

Identified differences in fat distribution between healthy and diseased subjects

Abstract

Reliable reference data in medical imaging is largely unavailable. Developing tools that allow for the comparison of individual patient data to reference data has a high potential to improve diagnostic imaging. Population atlases are a commonly used tool in medical imaging to facilitate this. Constructing such atlases becomes particularly challenging when working with highly heterogeneous datasets, such as whole-body images, which contain significant anatomical variations. In this work, we propose a pipeline for generating a standardised whole-body atlas for a highly heterogeneous population by partitioning the population into anatomically meaningful subgroups. Using magnetic resonance images from the UK Biobank dataset, we create six whole-body atlases representing a healthy population average. We furthermore unbias them, and this way obtain a realistic representation of the population. In addition to the anatomical atlases, we generate probabilistic atlases that capture the distributions of abdominal fat (visceral and subcutaneous) and five abdominal organs across the population (liver, spleen, pancreas, left and right kidneys). Our pipeline effectively generates high-quality, realistic whole-body atlases with clinical applicability. The probabilistic atlases show differences in fat distribution between subjects with medical conditions such as diabetes and cardiovascular diseases and healthy subjects in the atlas space. With this work, we make the constructed anatomical and label atlases publically available, with the expectation that they will support medical research involving whole-body MR images.