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Optimisation of Left Atrial Feature Tracking Using Retrospective Gated Computed Tomography Images.

Charles Sillett1, Orod Razeghi1, Marina Strocchi1

  • 1School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.

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PubMed
Summary
This summary is machine-generated.

Optimizing the temporal sparse free-form deformations (TSFFDs) method for left atrial (LA) feature tracking in cardiac computed tomography (CCT) significantly improved accuracy. This chamber-specific optimization enhances the analysis of cardiac function from CCT images.

Keywords:
Atrial fibrosisLeft atrial feature trackingRetrospective gated computed tomography

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Area of Science:

  • Medical Imaging
  • Biomedical Engineering
  • Computational Anatomy

Background:

  • Retrospective gated cardiac computed tomography (CCT) offers high-resolution cardiac imaging.
  • Previous work optimized feature tracking using temporal sparse free-form deformations (TSFFDs) for the left ventricle (LV).
  • Limited research exists on optimizing nonrigid registration for left atrial (LA) feature tracking in CCT.

Purpose of the Study:

  • To systematically optimize the TSFFD method for LA endocardial feature tracking in CCT.
  • To investigate the impact of sparsity weight (SW), bending energy (BE), and control point (CP) grid resolution on TSFFD performance for LA tracking.
  • To compare optimized LA tracking performance against a baseline LV-optimized configuration.

Main Methods:

  • Systematic optimization of SW and BE hyperparameters for TSFFD.
  • Evaluation of two control point (CP) grid resolutions.
  • Assessment of tracking accuracy using average surface distance (ASD), directed Hausdorff distance (DHD), and Dice score against ground truth segmentations.
  • Comparison of case-specific optimized parameters versus a fixed LV-optimized configuration.

Main Results:

  • The LV-optimized TSFFD configuration yielded baseline errors of 0.826 ± 0.172mm ASD, 5.882 ± 1.524mm DHD, and 0.912 ± 0.033 Dice score.
  • Optimizing SW and BE for LA tracking reduced errors to 0.750 ± 0.144mm ASD, 5.096 ± 1.246mm DHD, and 0.919 ± 0.029 Dice score.
  • Further improvement with higher CP resolution and optimized SW/BE resulted in cohort errors of 0.372 ± 0.051mm ASD, 2.739 ± 0.843mm DHD, and 0.949 ± 0.018 Dice score.

Conclusions:

  • TSFFD method performance for LA feature tracking in CCT is significantly enhanced by chamber-specific parameter optimization.
  • Optimized SW, BE, and increased CP resolution lead to more accurate LA endocardial tracking.
  • This study demonstrates the benefit of tailored optimization for improving cardiac feature tracking in specific heart chambers using CCT data.