Hierarchical Template Matching for 3D Myocardial Tracking and Cardiac Strain Estimation

• Published in: Scientific reports Vol. 9; no. 1; pp. 12450 - 13
• Main Authors: Bhalodiya, Jayendra M., Palit, Arnab, Ferrante, Enzo, Tiwari, Manoj K., Bhudia, Sunil K., Arvanitis, Theodoros N., Williams, Mark A.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 28.08.2019; Nature Publishing Group
• Subjects: 639/166/985; 639/705/117; Accuracy; Algorithms; Datasets; Heart; Humanities and Social Sciences; Humans; Image processing; Imaging, Three-Dimensional; Magnetic Resonance Imaging; Methods; Models, Cardiovascular; multidisciplinary; Myocardium; Science; Science (multidisciplinary); Spatial analysis; Three dimensional imaging; Ultrasonic imaging; Ventricle
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-019-48927-2

Myocardial tracking and strain estimation can non-invasively assess cardiac functioning using subject-specific MRI. As the left-ventricle does not have a uniform shape and functioning from base to apex, the development of 3D MRI has provided opportunities for simultaneous 3D tracking, and 3D strain estimation. We have extended a Local Weighted Mean (LWM) transformation function for 3D, and incorporated in a Hierarchical Template Matching model to solve 3D myocardial tracking and strain estimation problem. The LWM does not need to solve a large system of equations, provides smooth displacement of myocardial points, and adapt local geometric differences in images. Hence, 3D myocardial tracking can be performed with 1.49 mm median error, and without large error outliers. The maximum error of tracking is up to 24% reduced compared to benchmark methods. Moreover, the estimated strain can be insightful to improve 3D imaging protocols, and the computer code of LWM could also be useful for geo-spatial and manufacturing image analysis researchers.