Determining in-silico left ventricular contraction force of myocardial infarct tissue using a composite material model

Sergio C. H. Dempsey; Abbas Samani

doi:10.1117/12.2292914

13 March 2018 Determining in-silico left ventricular contraction force of myocardial infarct tissue using a composite material model

Sergio C. H. Dempsey, Abbas Samani

Author Affiliations +

Proceedings Volume 10576, Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling; 105761B (2018) https://doi.org/10.1117/12.2292914
Event: SPIE Medical Imaging, 2018, Houston, Texas, United States

Abstract

A computational method is presented in this paper for determining the severity of myocardial infarction of the left ventricle (LV) using its image data. In-silico generated displacement fields for a healthy and damaged LV are used to mimic imaging modalities by adding appropriate levels of noise. To reconstruct the contraction force from the displacement field, a composite material model of the LV is optimized using genetic algorithms and a neural network to return the contraction force and distribution of forces for infarct tissue. The healthy LV contraction force was accurately returned within 1% for all displacement field tests indicating that all imaging methods could be used to measure healthy patient LV displacement fields for the purpose of contraction force reconstruction. With the damaged LV, contraction forces of the healthy region, as well as infarct border and infarct regions were considered. The optimization model found the contraction force distribution within 2% for the healthy region, while for the border zone and infarct regions the average contraction force reconstruction errors were 8.4 kPa and 5.1 kPa, respectively. These errors are reasonably small while no significant SNR dependence was observed. The inverse problem algorithm provided good estimates regardless of the SNR, however, further training of the neural network system is required to improve the robustness of the inversion framework with low contraction forces, since the accuracy of the optimization limited the SNR response.

Conference Presentation

Citation Download Citation

Sergio C. H. Dempsey and Abbas Samani "Determining in-silico left ventricular contraction force of myocardial infarct tissue using a composite material model", Proc. SPIE 10576, Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling, 105761B (13 March 2018); https://doi.org/10.1117/12.2292914

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available