Computational Shape Models Characterize Shape Change of the Left Atrium in Atrial Fibrillation
Author(s) -
Joshua Cates,
Erik Bieging,
Alan Morris,
Gregory Gardner,
Nazem Akoum,
Eugene Kholmovski,
Nassir Marrouche,
Christopher McGann,
Rob MacLeod
Publication year - 2014
Publication title -
clinical medicine insights cardiology
Language(s) - English
Resource type - Journals
ISSN - 1179-5468
DOI - 10.4137/cmc.s15710
Subject(s) - left atrium , atrial fibrillation , shape change , appendage , shape analysis (program analysis) , active shape model , geometric shape , artificial intelligence , cardiology , medicine , computer science , mathematics , anatomy , geometry , biology , static analysis , evolutionary biology , programming language , segmentation
Shape change of the left atrium (LA) and LA appendage in atrial fibrillation (AF) patients is hypothesized to be linked to AF pathology and to play a role in thrombogenesis; however, many aspects of shape variation in the heart are poorly understood. To date, studies of the LA shape in AF have been limited to empirical observation and summary metrics, such as volume and its likeness to a sphere. This paper describes a more comprehensive approach to the study of the LA shape through the use of computationally derived statistical shape models. We describe practical approaches that we have developed to extract shape parameters automatically from the three-dimensional MR images of the patient. From these images and our techniques, we can produce a more comprehensive description of LA geometric variability than that has been previously possible. We present the methodology and results from two examples of specific analyses using shape models: (1) we describe statistically significant group differences between the normal control and AF patient populations (n = 137) and (2) we describe characteristic shapes of the LA appendage that are associated with the risk of thrombogenesis determined by transesophageal echocardiography (n = 203).
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