Morphologically normalized left ventricular motion indicators from MRI feature tracking characterize myocardial infarction /692/4019 /692/4019/592/75/230 /59 /59/57 article

13Citations
Citations of this article
36Readers
Mendeley users who have this article in their library.

Abstract

We characterized motion attributes arising from LV spatio-temporal analysis of motion distributions in myocardial infarction. Time-varying 3D finite element shape models were obtained in 300 Controls and 300 patients with myocardial infarction. Inter-individual left ventricular shape differences were eliminated using parallel transport to the grand mean of all cases. The first three principal component (PC) scores were used to characterize trajectory attributes. Scores were tested with ANOVA/MANOVA using patient disease status (Infarcts vs. Controls) as a factor. Infarcted patients had significantly different magnitude, orientation and shape of left ventricular trajectories in comparison to Controls. Significant differences were found for the angle between PC scores 1 and 2 in the endocardium, and PC scores 1 and 3 in the epicardium. The largest differences were found in the magnitude of endocardial motion. Endocardial PC scores in shape space showed the highest classification power using support vector machine, with higher total accuracy in comparison to previous methods. Shape space performed better than size-and-shape space for both epicardial and endocardial features. In conclusion, LV spatio-temporal motion attributes accurately characterize the presence of infarction. This approach is easily generalizable to different pathologies, enabling more precise study of the pathophysiological consequences of a wide spectrum of cardiac diseases.

References Powered by Scopus

Generalized procrustes analysis

2522Citations
N/AReaders
Get full text

Assessment of Myocardial Mechanics Using Speckle Tracking Echocardiography: Fundamentals and Clinical Applications

938Citations
N/AReaders
Get full text

A field comes of age: Geometric morphometrics in the 21<sup>st</sup> century

593Citations
N/AReaders
Get full text

Cited by Powered by Scopus

Deep-learning cardiac motion analysis for human survival prediction

183Citations
N/AReaders
Get full text

Gaussian process regressions for inverse problems and parameter searches in models of ventricular mechanics

32Citations
N/AReaders
Get full text

Machine Learning Approaches for Myocardial Motion and Deformation Analysis

22Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Piras, P., Teresi, L., Puddu, P. E., Torromeo, C., Young, A. A., Suinesiaputra, A., & Medrano-Gracia, P. (2017). Morphologically normalized left ventricular motion indicators from MRI feature tracking characterize myocardial infarction /692/4019 /692/4019/592/75/230 /59 /59/57 article. Scientific Reports, 7(1). https://doi.org/10.1038/s41598-017-12539-5

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 12

46%

Researcher 8

31%

Professor / Associate Prof. 5

19%

Lecturer / Post doc 1

4%

Readers' Discipline

Tooltip

Engineering 15

60%

Medicine and Dentistry 6

24%

Computer Science 2

8%

Nursing and Health Professions 2

8%

Save time finding and organizing research with Mendeley

Sign up for free