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Proceedings Paper

Co-registration of pre- and post-stent intravascular OCT images for validation of finite element model simulation of stent expansion
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Paper Abstract

Intravascular optical coherence tomography (IVOCT) provides high-resolution images of coronary calcifications and detailed measurements of acute stent deployment following stent implantation. Since pre- and post-stent IVOCT image “pull-back” acquisitions start from different locations, registration of corresponding pullbacks is needed for assessing treatment outcomes. In particular, we are interested in assessing finite element model (FEM) prediction of lumen gain following stenting, requiring registration. We used deep learning to segment calcifications in corresponding pre- and poststent IVOCT pullbacks. We created 1D representations of calcium thickness as a function of the angle of the helical IVOCT scans. Registration of two scans was done by maximizing the cross correlation of these two 1D representations. Registration was accurate, as determined by visual comparisons of 2D image frames. We used our pre-stent calcification segmentations to create a lesion-specific FEM, which took into account balloon size, balloon pressure, and stent measurements. We then compared simulated lumen gain from FEM analysis to actual stent deployment results. Actual lumen gain across ~200 registered pre and post-stent images was 1.52 ± 0.51, while FEM prediction was 1.43 ± 0.41. Comparison between actual and FEM results showed no significant difference (p < 0.001), suggesting accurate prediction of FEM modeling. Registered image data showed good visual agreement regarding lumen gain and stent strut malapposition. Hence, we have developed a platform for evaluation of FEM prediction of lumen gain. This platform can be used to guide development of FEM prediction software, which could ultimately help physicians with stent treatment planning of calcified lesions.

Paper Details

Date Published: 28 February 2020
PDF: 11 pages
Proc. SPIE 11317, Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging, 1131717 (28 February 2020);
Show Author Affiliations
Yazan Gharaibeh, Case Western Reserve Univ. (United States)
Juhwan Lee, Case Western Reserve Univ. (United States)
David Prabhu, Case Western Reserve Univ. (United States)
Pengfei Dong, Univ. of Nebraska-Lincoln (United States)
Florida Institute of Technology (United States)
Vladislav N. Zimin, Harrington Heart & Vascular Institute, Univ. Hospitals of Cleveland (United States)
Luis A. Dallan, Harrington Heart & Vascular Institute, Univ. Hospitals of Cleveland (United States)
Hiram Bezerra, Harrington Heart & Vascular Institute, Univ. Hospitals of Cleveland (United States)
Linxia Gu, Univ. of Nebraska-Lincoln (United States)
Florida Institute of Technology (United States)
David Wilson, Case Western Reserve Univ. (United States)


Published in SPIE Proceedings Vol. 11317:
Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging
Andrzej Krol; Barjor S. Gimi, Editor(s)

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