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Automated mitral valve vortex ring extraction from 4D-flow MRI. | LitMetric

AI Article Synopsis

  • The study aims to develop and validate an automated method for analyzing the mitral valve vortex ring using MR 4D-flow data to better understand its evolution over time.
  • The method involves identifying and tracking the vortex ring within the left ventricle using specific velocity criteria and was tested on data from 20 subjects (10 healthy and 10 with ischemic heart disease).
  • Results show that the algorithm effectively extracts vortex rings in sync with visual assessments, revealing significant differences in vortex characteristics between healthy individuals and patients, highlighting the vortex ring's relevance to left ventricular function.

Article Abstract

Purpose: To present and validate a method for automated extraction and analysis of the temporal evolution of the mitral valve (MV) vortex ring from MR 4D-flow data.

Methods: The proposed algorithm uses the divergence-free part of the velocity vector field for Q criterion-based identification and tracking of MV vortex ring core and region within the left ventricle (LV). The 4D-flow data of 20 subjects (10 healthy controls, 10 patients with ischemic heart disease) were used to validate the algorithm against visual analysis as well as to assess the method's sensitivity to manual LV segmentation. Quantitative MV vortex ring parameters were analyzed with respect to both their differences between healthy subjects and patients and their correlation with transmitral peak velocities.

Results: The algorithm successfully extracted MV vortex rings throughout the entire cardiac cycle, which agreed substantially with visual analysis (Cohen's kappa = 0.77). Furthermore, vortex cores and regions were robustly detected even if a static end-diastolic LV segmentation mask was applied to all frames (Dice coefficients 0.82 ± 0.08 and 0.94 ± 0.02 for core and region, respectively). Early diastolic MV vortex ring vorticity, kinetic energy and circularity index differed significantly between healthy controls and patients. In contrast to vortex shape parameters, vorticity and kinetic energy correlated strongly with transmitral peak velocities.

Conclusion: An automated method for temporal MV vortex ring extraction demonstrating robustness with respect to LV segmentation strategies is introduced. Quantitative vortex parameter analysis indicates importance of the MV vortex ring for LV diastolic (dys)function.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7540523PMC
http://dx.doi.org/10.1002/mrm.28361DOI Listing

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