Learning a dynamic four-chamber shape model of the human heart for 95,695 UK Biobank participants

TL;DR

This paper introduces a comprehensive 3D+t statistical shape model of all four cardiac chambers, learned from nearly 100,000 UK Biobank participants, enhancing cardiovascular analysis and disease prediction.

Contribution

It develops a deep learning pipeline for reconstructing four-chamber heart meshes and creates a large-scale shape model linking shape variations to health factors.

Findings

Shape-derived phenotypes improve disease classification accuracy.

The model reveals associations between heart shape and health factors.

Reconstructed meshes and the shape model will be publicly released.

Abstract

The human heart is a sophisticated system composed of four cardiac chambers with distinct shapes, which function in a coordinated manner. Existing shape models of the heart mainly focus on the ventricular chambers and they are derived from relatively small datasets. Here, we present a spatio-temporal (3D+t) statistical shape model of all four cardiac chambers, learnt from a large population of nearly 100,000 participants from the UK Biobank. A deep learning-based pipeline is developed to reconstruct 3D+t four-chamber meshes from the cardiac magnetic resonance images of the UK Biobank imaging population. Based on the reconstructed meshes, a 3D+t statistical shape model is learnt to characterise the shape variations and motion patterns of the four cardiac chambers. We reveal the associations of the four-chamber shape model with demographics, anthropometrics, cardiovascular risk factors, and cardiac diseases. Compared to conventional image-derived phenotypes, we validate that the four-chamber shape-derived phenotypes significantly enhance the performance in downstream tasks, including cardiovascular disease classification and heart age prediction. Furthermore, we demonstrate the effectiveness of shape-derived phenotypes in novel applications such as heart shape retrieval and heart re-identification from longitudinal data. To facilitate future research, we will release the learning-based mesh reconstruction pipeline, the four-chamber cardiac shape model, and return all derived four-chamber meshes to the UK Biobank.