Polymeric endovascular strut and lumen detection algorithm for intracoronary optical coherence tomography images
Name
036010_1.pdf
Description
Published version
Size
9.45 MB
Format
Adobe PDF
Checksum (MD5)
82413b7a6fc7c42b2da3191271201278
Author(s)
Edelman, Elazer R
Date Issued
March 2018
Journal
Journal of biomedical optics
Publisher
SPIE-Intl Soc Optical Eng
Citation
Amrute, Junedh M. et al. “Polymeric endovascular strut and lumen detection algorithm for intracoronary optical coherence tomography images.” Journal of biomedical optics, vol. 23, no. 3, 2018, article 036010 © 2018 The Author(s)
Version
Final published version
Abstract
Polymeric endovascular implants are the next step in minimally invasive vascular interventions. As an alternative to traditional metallic drug-eluting stents, these often-erodible scaffolds present opportunities and challenges for patients and clinicians. Theoretically, as they resorb and are absorbed over time, they obviate the long-term complications of permanent implants, but in the short-term visualization and therefore positioning is problematic. Polymeric scaffolds can only be fully imaged using optical coherence tomography (OCT) imaging - they are relatively invisible via angiography - and segmentation of polymeric struts in OCT images is performed manually, a laborious and intractable procedure for large datasets. Traditional lumen detection methods using implant struts as boundary limits fail in images with polymeric implants. Therefore, it is necessary to develop an automated method to detect polymeric struts and luminal borders in OCT images; we present such a fully automated algorithm. Accuracy was validated using expert annotations on 1140 OCT images with a positive predictive value of 0.93 for strut detection and an R 2 correlation coefficient of 0.94 between detected and expert-annotated lumen areas. The proposed algorithm allows for rapid, accurate, and automated detection of polymeric struts and the luminal border in OCT images.
MIT Department
Massachusetts Institute of Technology. Institute for Medical Engineering & Science
Massachusetts Institute of Technology. Center for Biomedical Engineering
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1117/1.JBO.23.3.036010
