@inbook{7f11ebbe1aa54310be8c95a0e590f2f4,
title = "Learning Associations Between Clinical Information and Motion-Based Descriptors Using a Large Scale MR-derived Cardiac Motion Atlas",
abstract = "The availability of large scale databases containing imaging and non-imaging data, such as the UK Biobank, represents an opportunity to improve our understanding of healthy and diseased bodily function. Cardiac motion atlases provide a space of reference in which the motion fields of a cohort of subjects can be directly compared. In this work, a cardiac motion atlas is built from cine MR data from the UK Biobank ((Formula Presented) 6000 subjects). Two automated quality control strategies are proposed to reject subjects with insufficient image quality. Based on the atlas, three dimensionality reduction algorithms are evaluated to learn data-driven cardiac motion descriptors, and statistical methods used to study the association between these descriptors and non-imaging data. Results show a positive correlation between the atlas motion descriptors and body fat percentage, basal metabolic rate, hypertension, smoking status and alcohol intake frequency. The proposed method outperforms the ability to identify changes in cardiac function due to these known cardiovascular risk factors compared to ejection fraction, the most commonly used descriptor of cardiac function. In conclusion, this work represents a framework for further investigation of the factors influencing cardiac health.",
keywords = "Cardiac motion atlas, Dimensionality reduction, Multivariate statistics, Non-imaging data",
author = "Esther Puyol-Ant{\'o}n and Bram Ruijsink and H{\'e}l{\`e}ne Langet and {De Craene}, Mathieu and Paolo Piro and Schnabel, {Julia A.} and King, {Andrew P.}",
year = "2019",
month = jan,
day = "1",
doi = "10.1007/978-3-030-12029-0_11",
language = "English",
isbn = "9783030120283",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "94--102",
editor = "Maxime Sermesant and Jichao Zhao and Alistair Young and Kawal Rhode and Mihaela Pop and Kristin McLeod and Tommaso Mansi and Shuo Li",
booktitle = "Statistical Atlases and Computational Models of the Heart. Atrial Segmentation and LV Quantification Challenges - 9th International Workshop, STACOM 2018, Held in Conjunction with MICCAI 2018, Revised Selected Papers",
address = "Germany",
note = "9th International Workshop on Statistical Atlases and Computational Models of the Heart: Atrial Segmentation and LV Quantification Challenges, STACOM 2018, held in conjunction with Medical Image Computing and Computer-Assisted Intervention, MICCAI 2018 ; Conference date: 16-09-2018 Through 16-09-2018",
}