20 March 2018 Polymeric endovascular strut and lumen detection algorithm for intracoronary optical coherence tomography images
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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 R2 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.
© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)
Junedh M. Amrute, Lambros S. Athanasiou, Farhad Rikhtegar, José M. de la Torre Hernández, Tamara García Camarero, Elazer R. Edelman, "Polymeric endovascular strut and lumen detection algorithm for intracoronary optical coherence tomography images," Journal of Biomedical Optics 23(3), 036010 (20 March 2018). https://doi.org/10.1117/1.JBO.23.3.036010 . Submission: Received: 15 August 2017; Accepted: 23 February 2018
Received: 15 August 2017; Accepted: 23 February 2018; Published: 20 March 2018
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