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Application of open-source computational tools to focal laser ablation of the prostate
Author(s): Kyle MacNeil; Aritrick Chatterjee; Clare Tempany; Aytekin Oto; Andriy Fedorov
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Paper Abstract

Standard treatment of prostate cancer has traditionally been invasive and radical, with the whole gland being treated, even in those instances of localized prostate cancer. The ongoing development of computational tools and improvements to MRI techniques has led to an increase in research exploring alternative treatment solutions. The goal of this study was to investigate the application of open-source computational tools to MR guided Prostate Cancer Focal Laser Ablation (PCaFLA). To this end, we explore the use of image registration tools within 3D Slicer to assess target coverage with the treated ablation zone. Three different registration tools were investigated for registration between a planning MRI (day of procedure MRI examination prior to ablation) and a post-treatment MRI (day of procedure MRI examination immediately after ablation). Prostate whole gland, focal tumor volume ROI, and ablation zone were segmented manually for each case. Overlap between the ablation zone and tumor ROI was quantified using volume overlap measures and directed Hausdorff distance (HD) metrics and experimental results were reported. Experimental results demonstrate the ability to apply open-source computational tools to investigate outcomes of focal laser ablation of the prostate from imaging. This study provides a preliminary evaluation of the utility of open-source computational tools in intra-procedural feedback and post-treatment assessment for focal therapy.

Paper Details

Date Published: 8 March 2019
PDF: 9 pages
Proc. SPIE 10951, Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling, 109511S (8 March 2019); doi: 10.1117/12.2512999
Show Author Affiliations
Kyle MacNeil, Queen's Univ. (Canada)
Aritrick Chatterjee, The Univ. of Chicago (United States)
Clare Tempany, Brigham and Women's Hospital (United States)
Aytekin Oto, The Univ. of Chicago (United States)
Andriy Fedorov, Brigham and Women's Hospital (United States)


Published in SPIE Proceedings Vol. 10951:
Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling
Baowei Fei; Cristian A. Linte, Editor(s)

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