  Cardiovascular disease, the leading cause of death globally, is an
age-related disease. Understanding the morphological and functional changes of
the heart during ageing is a key scientific question, the answer to which will
help us define important risk factors of cardiovascular disease and monitor
disease progression. In this work, we propose a novel conditional generative
model to describe the changes of 3D anatomy of the heart during ageing. The
proposed model is flexible and allows integration of multiple clinical factors
(e.g. age, gender) into the generating process. We train the model on a
large-scale cross-sectional dataset of cardiac anatomies and evaluate on both
cross-sectional and longitudinal datasets. The model demonstrates excellent
performance in predicting the longitudinal evolution of the ageing heart and
modelling its data distribution. The codes are available at
https://github.com/MengyunQ/AgeHeart.
