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A Practical Algorithm for Improving Localization and Quantification of Left Ventricular Scar.

Brian Zenger1, Joshua Cates2, Alan Morris3

  • 1Comprehensive Arrhythmia Research and Management Center, Salt Lake City, United States ; Department of Bioengineering, University of Utah, Salt Lake City, United States.

Computing in Cardiology
|October 9, 2015
PubMed
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This summary is machine-generated.

This study introduces a semi-automatic method for segmenting left ventricular walls and classifying scar tissue using advanced imaging techniques. The novel approach offers a more objective and efficient alternative to manual methods for scar identification.

Area of Science:

  • Cardiovascular Imaging
  • Medical Image Analysis
  • Computational Pathology

Background:

  • Current methods for left ventricular scar classification rely on manual segmentation and tissue classification.
  • Manual approaches are time-consuming and may introduce subjectivity in scar assessment.

Purpose of the Study:

  • To develop and validate a novel, semi-automatic approach for left ventricular (LV) wall segmentation and scar tissue classification.
  • To improve objectivity and efficiency in identifying myocardial scar post-infarction.

Main Methods:

  • Utilized high-resolution magnetic resonance angiograms (MRA) and late-gadolinium enhanced magnetic resonance imaging (LGE-MRI) from 14 patients.
  • Applied a level set-based segmentation method combined with MRA and LGE-MRI for myocardium segmentation.

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  • Employed an automated Otsu thresholding algorithm for scar tissue identification based on signal intensity.

    • Main Results:

    • The semi-automated LV segmentation achieved a 94% overlap with manual segmentations.
    • Scar volumes derived from the Otsu method showed strong correlation with expert observer scar volumes (Dice coefficient 0.85±0.11).

    Conclusions:

    • The proposed semi-automatic pipeline offers a more objective method for left ventricular scar identification compared to manual techniques.
    • This approach demonstrates potential for enhanced accuracy and efficiency in cardiovascular scar assessment.