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Updated: May 27, 2026

Transthoracic Speckle Tracking Echocardiography for the Quantitative Assessment of Left Ventricular Myocardial Deformation
Published on: October 20, 2016
Fourier analysis of STimulated echoes (FAST) for the quantitative analysis of left ventricular twist
Meral Reyhan1, Yutaka Natsuaki, Daniel B Ennis
1Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, California, USA. meral@ucla.edu
Purpose:
To validate a novel method for the rapid and facile quantification of left ventricular (LV) twist from tagged magnetic resonance images and demonstrate the potential clinical utility in a series of 20 healthy volunteers.
Materials And Methods:
Cardiac magnetic resonance imaging (MRI) short-axis images were acquired with tissue tagging in 20 healthy subjects and six canines. The tagged images were processed using a novel Fourier Analysis of the STimulated echoes (FAST) method, which uses a series of Fourier-space operations to measure LV twist with limited user interaction. A subset of eight healthy subjects and the canine data were compared to results from previously validated "gold standard" software (FindTags). Interobserver and intraobserver coefficients of variation (CV(INTER) and CV(INTRA) ), linear regression, and Bland-Altman analyses were used to assess agreement between observers and methods.
Results:
CV(INTRA) for peak systolic twist (2.9% and 2.6%) and CV(INTER) (4.3% and 4.2%) were all small. Linear regression analysis of the FAST and FindTags twist values indicated very good agreement in healthy subjects (R = 0.91) and in canines (R = 0.95). Bland-Altman comparison of the FAST and FindTags twist results indicated excellent agreement in healthy subjects (bias of -0.5°, 95% confidence intervals (-4.3°, 4.3°)) and canines (bias of 0.2°, 95% confidence intervals (-2.7°, 3.1°)). Peak systolic twist in healthy subjects averaged 10.5 ± 1.9° degrees.
Conclusion:
The FAST method for quantifying LV twist produces results that are not significantly different from the current "gold standard" in a fraction of the user interaction time and has demonstrated feasibility in human subjects.
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