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Proceedings Paper

3D registration of intravascular optical coherence tomography and cryo-image volumes for microscopic-resolution validation
Author(s): David Prabhu; Emile Mehanna; Madhusudhana Gargesha; Di Wen; Eric Brandt; Nienke S. van Ditzhuijzen; Daniel Chamie; Hirosada Yamamoto; Yusuke Fujino; Ali Farmazilian; Jaymin Patel; Marco Costa; Hiram G. Bezerra; David L. Wilson
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Paper Abstract

High resolution, 100 frames/sec intravascular optical coherence tomography (IVOCT) can distinguish plaque types, but further validation is needed, especially for automated plaque characterization. We developed experimental and 3D registration methods, to provide validation of IVOCT pullback volumes using microscopic, brightfield and fluorescent cryoimage volumes, with optional, exactly registered cryo-histology. The innovation was a method to match an IVOCT pullback images, acquired in the catheter reference frame, to a true 3D cryo-image volume. Briefly, an 11-parameter, polynomial virtual catheter was initialized within the cryo-image volume, and perpendicular images were extracted, mimicking IVOCT image acquisition. Virtual catheter parameters were optimized to maximize cryo and IVOCT lumen overlap. Local minima were possible, but when we started within reasonable ranges, every one of 24 digital phantom cases converged to a good solution with a registration error of only +1.34±2.65μm (signed distance). Registration was applied to 10 ex-vivo cadaver coronary arteries (LADs), resulting in 10 registered cryo and IVOCT volumes yielding a total of 421 registered 2D-image pairs. Image overlays demonstrated high continuity between vascular and plaque features. Bland- Altman analysis comparing cryo and IVOCT lumen area, showed mean and standard deviation of differences as 0.01±0.43 mm2. DICE coefficients were 0.91±0.04. Finally, visual assessment on 20 representative cases with easily identifiable features suggested registration accuracy within one frame of IVOCT (±200μm), eliminating significant misinterpretations introduced by 1mm errors in the literature. The method will provide 3D data for training of IVOCT plaque algorithms and can be used for validation of other intravascular imaging modalities.

Paper Details

Date Published: 29 March 2016
PDF: 9 pages
Proc. SPIE 9788, Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging, 97882C (29 March 2016); doi: 10.1117/12.2217537
Show Author Affiliations
David Prabhu, Case Western Reserve Univ. (United States)
Emile Mehanna, Harrington-McLaughlin Heart & Vascular Institute, Univ. Hospitals Case Medical Ctr. (United States)
Madhusudhana Gargesha, Case Western Reserve Univ. (United States)
Di Wen, Case Western Reserve Univ (United States)
Eric Brandt, Harrington-McLaughlin Heart & Vascular Institute, Univ. Hospitals Case Medical Ctr. (United States)
Nienke S. van Ditzhuijzen, Harrington-McLaughlin Heart & Vascular Institute, Univ. Hospitals Case Medical Ctr. (United States)
Daniel Chamie, Harrington-McLaughlin Heart & Vascular Institute, Univ. Hospitals Case Medical Ctr. (United States)
Hirosada Yamamoto, Harrington-McLaughlin Heart & Vascular Institute, Univ. Hospitals Case Medical Ctr. (United States)
Yusuke Fujino, Harrington-McLaughlin Heart & Vascular Institute, Univ. Hospitals Case Medical Ctr. (United States)
Ali Farmazilian, Harrington-McLaughlin Heart & Vascular Institute, Univ. Hospitals Case Medical Ctr. (United States)
Jaymin Patel, Case Western Reserve Univ. (United States)
Marco Costa, Harrington-McLaughlin Heart & Vascular Institute, Univ. Hospitals Case Medical Ctr. (United States)
Hiram G. Bezerra, Harrington-McLaughlin Heart & Vascular Institute, Univ. Hospitals Case Medical Ctr. (United States)
David L. Wilson, Case Western Reserve Univ (United States)


Published in SPIE Proceedings Vol. 9788:
Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging
Barjor Gimi; Andrzej Krol, Editor(s)

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