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Myocardial Strain Imaging Using Feature Tracking Method of Cardiac MRI: Our Initial Experience of This Novel Parameter as an Additional Diagnostic Tool
Background Left ventricular ejection fraction (LVEF) is used as quantitative parameter to evaluate myocardial function. However, interobserver variation, limited reproducibility, and dependence on pre-load and after-load reduces its accuracy. The fall in LVEF occurs very late, when myocardial dysfunction is already advanced. Myocardial strain measurements (especially global longitudinal strain) is a new parameter to detect myocardial dysfunction before derangements in LVEF. The aim of this article is to share our experience of this novel diagnostic tool.
Methods Feature tracking method of strain assessment is performed using routine long and short axis cine images of cardiac MRI (CMR). Dedicated post-processing CMR software can perform off-line analysis and provide results in form of color-coded maps, percentage values as well as strain over time curve for each myocardial segments.
Results Global longitudinal strain (GLS) is more sensitive than LVEF and can identify sub-clinical left ventricular (LV) dysfunction in various cardiomyopathies. It is also an important prognostic marker in serial assessment of heart failure patients. Regional differences in strain parameters can provide clues in hypertrophic cardiomyopathy as well as amyloidosis. GLS is recommended as routine measurement in patients undergoing chemotherapy to detect LV dysfunction prior to fall in LVEF. Strain imaging can be applied to guide placement of the LV pacing lead in patients receiving cardiac resynchronization therapy. More clinical data is needed to evaluate its role in ischemic heart disease.
Conclusion Strain imaging can identify LV dysfunction earlier than conventional methods and this opens a new perspective in risk stratification and therapeutic decision-making of various cardiac pathologies.
Article published online:
30 August 2022
© 2022. Indian Radiological Association. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)
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