16 November 2020 Comprehensive enhanced methodology of an MRI-based automated left-ventricular chamber quantification algorithm and validation in chemotherapy-related cardiotoxicity
Julia Kar, Michael V. Cohen, Samuel A. McQuiston, Christopher M. Malozzi
Author Affiliations +
Abstract

Purpose: To comprehensively outline the methodology of a fully automated, MRI motion-guided, left-ventricular (LV) chamber quantification algorithm that enhances a similar, existing semi-automated approach. Additionally, to validate the motion-guided technique in comparison to chamber quantification with a vendor tool in post-chemotherapy breast cancer patients susceptible to cardiotoxicity.

Approach: LV deformation data were acquired with the displacement encoding with stimulated echoes (DENSE) sequence on N  =  21 post-chemotherapy female patients and N  =  21 age-matched healthy females. The new chamber quantification algorithm consists of detecting LV boundary motion via a combination of image quantization and DENSE phase-encoded displacements. LV contractility was analyzed via chamber quantification and computations of 3D strains and torsion. For validation, estimates of chamber quantification with the motion-guided algorithm on DENSE and steady-state free precession (SSFP) acquisitions, and similar estimates with an existing vendor tool on DENSE acquisitions were compared via repeated measures analysis. Patient results were compared to healthy subjects for observing abnormalities.

Results: Repeated measures analysis showed similar LV ejection fractions (LVEF), 59  %    ±  6  %  , 58  %    ±  6  %  , and 58  %    ±  6  %  , p  =  0.2, by applying the motion-guided algorithm on DENSE and SSFP and vendor tool on DENSE acquisitions, respectively. Differences found between patients and healthy subjects included enlarged basal diameters (5.0  ±  0.5  cm versus 4.4  ±  0.5  cm, p  <  0.01), torsions (p  <  0.001), and longitudinal strains (p  <  0.001), but not LVEF (p  =  0.1).

Conclusions: Measurement similarities between new and existing tools, and between DENSE and SSFP validated the motion-guided algorithm and differences found between subpopulations demonstrate the ability to detect contractile abnormalities.

© 2020 Society of Photo-Optical Instrumentation Engineers (SPIE) 2329-4302/2020/$28.00 © 2020 SPIE
Julia Kar, Michael V. Cohen, Samuel A. McQuiston, and Christopher M. Malozzi "Comprehensive enhanced methodology of an MRI-based automated left-ventricular chamber quantification algorithm and validation in chemotherapy-related cardiotoxicity," Journal of Medical Imaging 7(6), 064002 (16 November 2020). https://doi.org/10.1117/1.JMI.7.6.064002
Received: 13 August 2019; Accepted: 23 October 2020; Published: 16 November 2020
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KEYWORDS
Image segmentation

Quantization

Breast cancer

Statistical analysis

Tissues

3D image processing

Data acquisition

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