An Automatic Service for the Personalization of Ventricular Cardiac Meshes

Overview

Journal J R Soc Interface

Specialties Biology
Biomedical Engineering
Biophysics

Date 2013 Dec 17

PMID 24335562

Citations 29

Authors

Pablo Lamata

Matthew Sinclair

Eric Kerfoot

Angela Lee

Andrew Crozier

Bojan Blazevic

Sander Land

Adam J Lewandowski

David Barber

Steve Niederer

Nic Smith

Affiliations

Soon will be listed here.

Abstract

Computational cardiac physiology has great potential to improve the management of cardiovascular diseases. One of the main bottlenecks in this field is the customization of the computational model to the anatomical and physiological status of the patient. We present a fully automatic service for the geometrical personalization of cardiac ventricular meshes with high-order interpolation from segmented images. The method is versatile (able to work with different species and disease conditions) and robust (fully automatic results fulfilling accuracy and quality requirements in 87% of 255 cases). Results also illustrate the capability to minimize the impact of segmentation errors, to overcome the sparse resolution of dynamic studies and to remove the sometimes unnecessary anatomical detail of papillary and trabecular structures. The smooth meshes produced can be used to simulate cardiac function, and in particular mechanics, or can be used as diagnostic descriptors of anatomical shape by cardiologists. This fully automatic service is deployed in a cloud infrastructure, and has been made available and accessible to the scientific community.

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