Paper
12 March 2014 Patient-specific left atrial wall-thickness measurement and visualization for radiofrequency ablation
Jiro Inoue, Allan C. Skanes, James A. White, Martin Rajchl, Maria Drangova
Author Affiliations +
Abstract
INTRODUCTION: For radiofrequency (RF) catheter ablation of the left atrium, safe and effective dosing of RF energy requires transmural left atrium ablation without injury to extra-cardiac structures. The thickness of the left atrial wall may be a key parameter in determining the appropriate amount of energy to deliver. While left atrial wall-thickness is known to exhibit inter- and intra-patient variation, this is not taken into account in the current clinical workflow. Our goal is to develop a tool for presenting patient-specific left atrial thickness information to the clinician in order to assist in the determination of the proper RF energy dose. METHODS: We use an interactive segmentation method with manual correction to segment the left atrial blood pool and heart wall from contrast-enhanced cardiac CT images. We then create a mesh from the segmented blood pool and determine the wall thickness, on a per–vertex basis, orthogonal to the mesh surface. The thickness measurement is visualized by assigning colors to the vertices of the blood pool mesh. We applied our method to 5 contrast-enhanced cardiac CT images. RESULTS: Left atrial wall-thickness measurements were generally consistent with published thickness ranges. Variations were found to exist between patients, and between regions within each patient. CONCLUSION: It is possible to visually determine areas of thick vs. thin heart wall with high resolution in a patient-specific manner.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jiro Inoue, Allan C. Skanes, James A. White, Martin Rajchl, and Maria Drangova "Patient-specific left atrial wall-thickness measurement and visualization for radiofrequency ablation", Proc. SPIE 9036, Medical Imaging 2014: Image-Guided Procedures, Robotic Interventions, and Modeling, 90361N (12 March 2014); https://doi.org/10.1117/12.2043630
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
Image segmentation

Blood

Visualization

Heart

Computed tomography

Tissues

3D metrology

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