Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/135798
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Type: | Journal article |
Title: | Automated Coronary Optical Coherence Tomography Feature Extraction with Application to Three-Dimensional Reconstruction |
Author: | Carpenter, H.J. Ghayesh, M.H. Zander, A.C. Li, J. Di Giovanni, G. Psaltis, P.J. |
Citation: | Tomography, 2022; 8(3):1307-1349 |
Publisher: | MDPI AG |
Issue Date: | 2022 |
ISSN: | 2379-1381 2379-139X |
Statement of Responsibility: | Harry J. Carpenter, Mergen H. Ghayesh, Anthony C. Zander, Jiawen Li, Giuseppe Di Giovanni, and Peter J. Psaltis |
Abstract: | Coronary optical coherence tomography (OCT) is an intravascular, near-infrared lightbased imaging modality capable of reaching axial resolutions of 10–20 um. This resolution allows for accurate determination of high-risk plaque features, such as thin cap fibroatheroma; however, visualization of morphological features alone still provides unreliable positive predictive capability for plaque progression or future major adverse cardiovascular events (MACE). Biomechanical simulation could assist in this prediction, but this requires extracting morphological features from intravascular imaging to construct accurate three-dimensional (3D) simulations of patients’ arteries. Extracting these features is a laborious process, often carried out manually by trained experts. To address this challenge, numerous techniques have emerged to automate these processes while simultaneously overcoming difficulties associated with OCT imaging, such as its limited penetration depth. This systematic review summarizes advances in automated segmentation techniques from the past five years (2016–2021) with a focus on their application to the 3D reconstruction of vessels and their subsequent simulation. We discuss four categories based on the feature being processed, namely: coronary lumen; artery layers; plaque characteristics and subtypes; and stents. Areas for future innovation are also discussed as well as their potential for future translation. |
Keywords: | atherosclerosis; biomechanics; border detection; coronary artery disease; optical coherence tomography; stents; vulnerable plaque |
Rights: | © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). |
DOI: | 10.3390/tomography8030108 |
Grant ID: | http://purl.org/au-research/grants/nhmrc/GNT2008462 http://purl.org/au-research/grants/nhmrc/CDF1161506 http://purl.org/au-research/grants/nhmrc/2001646 |
Published version: | http://dx.doi.org/10.3390/tomography8030108 |
Appears in Collections: | Mechanical Engineering publications |
Files in This Item:
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hdl_135798.pdf | Published version | 3.19 MB | Adobe PDF | View/Open |
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