Literature DB >> 27429997

Three-dimensional registration of intravascular optical coherence tomography and cryo-image volumes for microscopic-resolution validation.

David Prabhu1, Emile Mehanna2, Madhusudhana Gargesha1, Eric Brandt2, Di Wen3, Nienke S van Ditzhuijzen2, Daniel Chamie2, Hirosada Yamamoto2, Yusuke Fujino2, Ali Alian2, Jaymin Patel1, Marco Costa2, Hiram G Bezerra2, David L Wilson1.   

Abstract

Evidence suggests high-resolution, high-contrast, [Formula: see text] intravascular optical coherence tomography (IVOCT) can distinguish plaque types, but further validation is needed, especially for automated plaque characterization. We developed experimental and three-dimensional (3-D) registration methods to provide validation of IVOCT pullback volumes using microscopic, color, and fluorescent cryo-image volumes with optional registered cryo-histology. A specialized registration method matched IVOCT pullback images acquired in the catheter reference frame to a true 3-D cryo-image volume. Briefly, an 11-parameter registration model including a 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. Multiple assessments suggested that the registration error was better than the [Formula: see text] spacing between IVOCT image frames. Tests on a digital synthetic phantom gave a registration error of only [Formula: see text] (signed distance). Visual assessment of randomly presented nearby frames suggested registration accuracy within 1 IVOCT frame interval ([Formula: see text]). This would eliminate potential misinterpretations confronted by the typical histological approaches to validation, with estimated 1-mm errors. The method can be used to create annotated datasets and automated plaque classification methods and can be extended to other intravascular imaging modalities.

Keywords:  cryo-imaging; histology; intravascular imaging; optical coherence tomography; three-dimensional image registration; validation

Year:  2016        PMID: 27429997      PMCID: PMC4923671          DOI: 10.1117/1.JMI.3.2.026004

Source DB:  PubMed          Journal:  J Med Imaging (Bellingham)        ISSN: 2329-4302


  33 in total

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Journal:  Arterioscler Thromb Vasc Biol       Date:  2000-05       Impact factor: 8.311

2.  Visualization of coronary atherosclerotic plaques in patients using optical coherence tomography: comparison with intravascular ultrasound.

Authors:  Ik-Kyung Jang; Brett E Bouma; Dong-Heon Kang; Seung-Jung Park; Seong-Wook Park; Ki-Bae Seung; Kyu-Bo Choi; Milen Shishkov; Kelly Schlendorf; Eugene Pomerantsev; Stuart L Houser; H Thomas Aretz; Guillermo J Tearney
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Authors:  R T Lee; P Libby
Journal:  Arterioscler Thromb Vasc Biol       Date:  1997-10       Impact factor: 8.311

4.  Parameter estimation of atherosclerotic tissue optical properties from three-dimensional intravascular optical coherence tomography.

Authors:  Madhusudhana Gargesha; Ronny Shalev; David Prabhu; Kentaro Tanaka; Andrew M Rollins; Marco Costa; Hiram G Bezerra; David L Wilson
Journal:  J Med Imaging (Bellingham)       Date:  2015-01-02

5.  Sources of error and interpretation of plaque morphology by optical coherence tomography.

Authors:  Olivia Manfrini; Erik Mont; Ornella Leone; Eloisa Arbustini; Vincenzo Eusebi; Renu Virmani; Raffale Bugiardini
Journal:  Am J Cardiol       Date:  2006-05-19       Impact factor: 2.778

6.  Measurement of the thickness of the fibrous cap by optical coherence tomography.

Authors:  Teruyoshi Kume; Takashi Akasaka; Takahiro Kawamoto; Hiroyuki Okura; Nozomi Watanabe; Eiji Toyota; Yoji Neishi; Renan Sukmawan; Yoshito Sadahira; Kiyoshi Yoshida
Journal:  Am Heart J       Date:  2006-10       Impact factor: 4.749

7.  Coronary risk factors and plaque morphology in men with coronary disease who died suddenly.

Authors:  A P Burke; A Farb; G T Malcom; Y H Liang; J Smialek; R Virmani
Journal:  N Engl J Med       Date:  1997-05-01       Impact factor: 91.245

Review 8.  Intracoronary optical coherence tomography: a comprehensive review clinical and research applications.

Authors:  Hiram G Bezerra; Marco A Costa; Giulio Guagliumi; Andrew M Rollins; Daniel I Simon
Journal:  JACC Cardiovasc Interv       Date:  2009-11       Impact factor: 11.195

9.  Quantification of macrophage content in atherosclerotic plaques by optical coherence tomography.

Authors:  Guillermo J Tearney; Hiroshi Yabushita; Stuart L Houser; H Thomas Aretz; Ik-Kyung Jang; Kelly H Schlendorf; Christopher R Kauffman; Milen Shishkov; Elkan F Halpern; Brett E Bouma
Journal:  Circulation       Date:  2003-01-07       Impact factor: 29.690

10.  Volumetric characterization of human coronary calcification by frequency-domain optical coherence tomography.

Authors:  Emile Mehanna; Hiram G Bezerra; David Prabhu; Eric Brandt; Daniel Chamié; Hirosada Yamamoto; Guilherme F Attizzani; Satoko Tahara; Nienke Van Ditzhuijzen; Yusuke Fujino; Tomoaki Kanaya; Gregory Stefano; Wei Wang; Madhusudhana Gargesha; David Wilson; Marco A Costa
Journal:  Circ J       Date:  2013-06-19       Impact factor: 2.993

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  4 in total

1.  Method for accurate registration of tissue autofluorescence imaging data with corresponding histology: a means for enhanced tumor margin assessment.

Authors:  Jakob Unger; Tianchen Sun; Yi-Ling Chen; Jennifer E Phipps; Richard J Bold; Morgan A Darrow; Kwan-Liu Ma; Laura Marcu
Journal:  J Biomed Opt       Date:  2018-01       Impact factor: 3.170

2.  Automated plaque characterization using deep learning on coronary intravascular optical coherence tomographic images.

Authors:  Juhwan Lee; David Prabhu; Chaitanya Kolluru; Yazan Gharaibeh; Vladislav N Zimin; Hiram G Bezerra; David L Wilson
Journal:  Biomed Opt Express       Date:  2019-11-25       Impact factor: 3.732

3.  Automated A-line coronary plaque classification of intravascular optical coherence tomography images using handcrafted features and large datasets.

Authors:  David Prabhu; Hiram Bezerra; Chaitanya Kolluru; Yazan Gharaibeh; Emile Mehanna; Hao Wu; David Wilson
Journal:  J Biomed Opt       Date:  2019-10       Impact factor: 3.170

4.  Coronary calcification segmentation in intravascular OCT images using deep learning: application to calcification scoring.

Authors:  Yazan Gharaibeh; David Prabhu; Chaitanya Kolluru; Juhwan Lee; Vladislav Zimin; Hiram Bezerra; David Wilson
Journal:  J Med Imaging (Bellingham)       Date:  2019-12-27
  4 in total

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