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Wu W, Oguz UM, Banga A, Zhao S, Thota AK, Gadamidi VK, Vasa CH, Harmouch KM, Naser A, Tieliwaerdi X, Chatzizisis YS. 3D reconstruction of coronary artery bifurcations from intravascular ultrasound and angiography. Sci Rep 2023; 13:13031. [PMID: 37563354 PMCID: PMC10415353 DOI: 10.1038/s41598-023-40257-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2023] [Accepted: 08/07/2023] [Indexed: 08/12/2023] Open
Abstract
Coronary bifurcation lesions represent a challenging anatomical subset, and the understanding of their 3D anatomy and plaque composition appears to play a key role in devising the optimal stenting strategy. This study proposes a new approach for the 3D reconstruction of coronary bifurcations and plaque materials by combining intravascular ultrasound (IVUS) and angiography. Three patient-specific silicone bifurcation models were 3D reconstructed and compared to micro-computed tomography (µCT) as the gold standard to test the accuracy and reproducibility of the proposed methodology. The clinical feasibility of the method was investigated in three diseased patient-specific bifurcations of varying anatomical complexity. The IVUS-based 3D reconstructed bifurcation models showed high agreement with the µCT reference models, with r2 values ranging from 0.88 to 0.99. The methodology successfully 3D reconstructed all the patient bifurcations, including plaque materials, in less than 60 min. Our proposed method is a simple, time-efficient, and user-friendly tool for accurate 3D reconstruction of coronary artery bifurcations. It can provide valuable information about bifurcation anatomy and plaque burden in the clinical setting, assisting in bifurcation stent planning and education.
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Affiliation(s)
- Wei Wu
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Usama M Oguz
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Akshat Banga
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Shijia Zhao
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Anjani Kumar Thota
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Vinay Kumar Gadamidi
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Charu Hasini Vasa
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Khaled M Harmouch
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Abdallah Naser
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Xiarepati Tieliwaerdi
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Yiannis S Chatzizisis
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, Miller School of Medicine, University of Miami, Miami, FL, USA.
- Division of Cardiovascular Medicine, Leonard M. Miller School of Medicine, University of Miami Health System, University of Miami, 1120 NW 14th Street, Suite 1124, Miami, FL, 33136, USA.
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Xia M, Yang H, Huang Y, Qu Y, Guo Y, Zhou G, Zhang F, Wang Y. AwCPM-Net: A Collaborative Constraint GAN for 3D Coronary Artery Reconstruction in Intravascular Ultrasound Sequences. IEEE J Biomed Health Inform 2022; 26:3047-3058. [PMID: 35104236 DOI: 10.1109/jbhi.2022.3147888] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
3D coronary artery reconstruction (3D-CAR) in intravascular ultrasound (IVUS) sequences allows quantitative analyses of vessel properties. Existing methods treat two main tasks of the 3D-CAR separately, including the cardiac phase retrieval (CPR) and the membrane border extraction (MBE). They ignore the CPR-MBE connection that could achieve mutual promotions to both tasks. In this paper, we pioneer to achieve one-step 3D-CAR via a collaborative constraint generative adversarial network (GAN) named the AwCPM-Net. The AwCPM-Net consists of a dual-task collaborative generator and a dual-task constraint discriminator. The generator combines a self-supervised CPR branch with a semi-supervised MBE branch via a warming-up connection. The discriminator promotes dual-branch predictions simultaneously. The CPR branch requires no annotations and outputs inter-frame deformation fields used for identifying cardiac phases. Deformation fields are additionally constrained by the MBE branch and the discriminator. The MBE branch predicts membrane boundaries for each frame. Two aspects assist the semi-supervised segmentation: annotation augmentation by deformation fields of the CPR branch; information exploitation on unlabeled images enabled by GAN design. Trained and tested on an IVUS dataset acquired from atherosclerosis patients, the AwCPM-Net is effective in both CPR and MBE tasks, superior to state-of-the-art IVUS CPR or MBE methods. Hence, the AwCPM-Net reconstructs reliable 3D artery anatomy in the IVUS modality.
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Kilic Y, Safi H, Bajaj R, Serruys PW, Kitslaar P, Ramasamy A, Tufaro V, Onuma Y, Mathur A, Torii R, Baumbach A, Bourantas CV. The Evolution of Data Fusion Methodologies Developed to Reconstruct Coronary Artery Geometry From Intravascular Imaging and Coronary Angiography Data: A Comprehensive Review. Front Cardiovasc Med 2020; 7:33. [PMID: 32296713 PMCID: PMC7136420 DOI: 10.3389/fcvm.2020.00033] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2019] [Accepted: 02/21/2020] [Indexed: 12/01/2022] Open
Abstract
Understanding the mechanisms that regulate atherosclerotic plaque formation and evolution is a crucial step for developing treatment strategies that will prevent plaque progression and reduce cardiovascular events. Advances in signal processing and the miniaturization of medical devices have enabled the design of multimodality intravascular imaging catheters that allow complete and detailed assessment of plaque morphology and biology. However, a significant limitation of these novel imaging catheters is that they provide two-dimensional (2D) visualization of the lumen and vessel wall and thus they cannot portray vessel geometry and 3D lesion architecture. To address this limitation computer-based methodologies and user-friendly software have been developed. These are able to off-line process and fuse intravascular imaging data with X-ray or computed tomography coronary angiography (CTCA) to reconstruct coronary artery anatomy. The aim of this review article is to summarize the evolution in the field of coronary artery modeling; we thus present the first methodologies that were developed to model vessel geometry, highlight the modifications introduced in revised methods to overcome the limitations of the first approaches and discuss the challenges that need to be addressed, so these techniques can have broad application in clinical practice and research.
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Affiliation(s)
- Yakup Kilic
- Department of Cardiology, Barts Heart Centre, Barts Health NHS Trust, London, United Kingdom
| | - Hannah Safi
- Institute of Cardiovascular Sciences, University College London, London, United Kingdom
| | - Retesh Bajaj
- Department of Cardiology, Barts Heart Centre, Barts Health NHS Trust, London, United Kingdom.,Centre for Cardiovascular Medicine and Device Innovation, Queen Mary University London, London, United Kingdom
| | - Patrick W Serruys
- Faculty of Medicine, National Heart & Lung Institute, Imperial College London, London, United Kingdom
| | - Pieter Kitslaar
- Department of Radiology, Leiden University Medical Center, Leiden, Netherlands
| | - Anantharaman Ramasamy
- Department of Cardiology, Barts Heart Centre, Barts Health NHS Trust, London, United Kingdom.,Centre for Cardiovascular Medicine and Device Innovation, Queen Mary University London, London, United Kingdom
| | - Vincenzo Tufaro
- Centre for Cardiovascular Medicine and Device Innovation, Queen Mary University London, London, United Kingdom
| | | | - Anthony Mathur
- Department of Cardiology, Barts Heart Centre, Barts Health NHS Trust, London, United Kingdom.,Centre for Cardiovascular Medicine and Device Innovation, Queen Mary University London, London, United Kingdom
| | - Ryo Torii
- Department of Mechanical Engineering, University College London, London, United Kingdom
| | - Andreas Baumbach
- Department of Cardiology, Barts Heart Centre, Barts Health NHS Trust, London, United Kingdom.,Centre for Cardiovascular Medicine and Device Innovation, Queen Mary University London, London, United Kingdom
| | - Christos V Bourantas
- Department of Cardiology, Barts Heart Centre, Barts Health NHS Trust, London, United Kingdom.,Institute of Cardiovascular Sciences, University College London, London, United Kingdom.,Centre for Cardiovascular Medicine and Device Innovation, Queen Mary University London, London, United Kingdom
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Wang J, Paritala PK, Mendieta JB, Komori Y, Raffel OC, Gu Y, Li Z. Optical coherence tomography-based patient-specific coronary artery reconstruction and fluid–structure interaction simulation. Biomech Model Mechanobiol 2019; 19:7-20. [DOI: 10.1007/s10237-019-01191-9] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2019] [Accepted: 06/21/2019] [Indexed: 01/14/2023]
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Neumann EE, Young M, Erdemir A. A pragmatic approach to understand peripheral artery lumen surface stiffness due to plaque heterogeneity. Comput Methods Biomech Biomed Engin 2019; 22:396-408. [PMID: 30712373 DOI: 10.1080/10255842.2018.1560427] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
The goal of this study was to develop a pragmatic approach to build patient-specific models of the peripheral artery that are aware of plaque inhomogeneity. Patient-specific models using element-specific material definition (to understand the role of plaque composition) and homogeneous material definition (to understand the role of artery diameter and thickness) were automatically built from intravascular ultrasound images of three artery segments classified with low, average, and high calcification. The element-specific material models had average surface stiffness values of 0.0735, 0.0826, and 0.0973 MPa/mm, whereas the homogeneous material models had average surface stiffness values of 0.1392, 0.1276, and 0.1922 MPa/mm for low, average, and high calcification, respectively. Localization of peak lumen stiffness and differences in patient-specific average surface stiffness for homogeneous and element-specific models suggest the role of plaque composition on surface stiffness in addition to local arterial diameter and thickness.
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Affiliation(s)
- Erica E Neumann
- a Department of Biomedical Engineering , Lerner Research Institute, Cleveland Clinic , Cleveland , OH , USA.,b Computational Biomodeling (CoBi) Core, Lerner Research Institute , Cleveland Clinic , Cleveland , OH , USA
| | - Melissa Young
- c Division of Cardiovascular Diseases , Mayo Clinic , Rochester , MN , USA
| | - Ahmet Erdemir
- a Department of Biomedical Engineering , Lerner Research Institute, Cleveland Clinic , Cleveland , OH , USA.,b Computational Biomodeling (CoBi) Core, Lerner Research Institute , Cleveland Clinic , Cleveland , OH , USA
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6
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Chatzizisis YS, Toutouzas K, Giannopoulos AA, Riga M, Antoniadis AP, Fujinom Y, Mitsouras D, Koutkias VG, Cheimariotis G, Doulaverakis C, Tsampoulatidis I, Chouvarda I, Kompatsiaris I, Nakamura S, Rybicki FJ, Maglaveras N, Tousoulis D, Giannoglou GD. Association of global and local low endothelial shear stress with high-risk plaque using intracoronary 3D optical coherence tomography: Introduction of 'shear stress score'. Eur Heart J Cardiovasc Imaging 2018; 18:888-897. [PMID: 27461211 DOI: 10.1093/ehjci/jew134] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2015] [Accepted: 06/02/2016] [Indexed: 11/15/2022] Open
Abstract
Aims The association of low endothelial shear stress (ESS) with high-risk plaque (HRP) has not been thoroughly investigated in humans. We investigated the local ESS and lumen remodelling patterns in HRPs using optical coherence tomography (OCT), developed the shear stress score, and explored its association with the prevalence of HRPs and clinical outcomes. Methods and results A total of 35 coronary arteries from 30 patients with stable angina or acute coronary syndrome (ACS) were reconstructed with three dimensional (3D) OCT. ESS was calculated using computational fluid dynamics and classified into low, moderate, and high in 3-mm-long subsegments. In each subsegment, (i) fibroatheromas (FAs) were classified into HRPs and non-HRPs based on fibrous cap (FC) thickness and lipid pool size, and (ii) lumen remodelling was classified into constrictive, compensatory, and expansive. In each artery the shear stress score was calculated as metric of the extent and severity of low ESS. FAs in low ESS subsegments had thinner FC compared with high ESS (89 ± 84 vs.138 ± 83 µm, P < 0.05). Low ESS subsegments predominantly co-localized with HRPs vs. non-HRPs (29 vs. 9%, P < 0.05) and high ESS subsegments predominantly with non-HRPs (9 vs. 24%, P < 0.05). Compensatory and expansive lumen remodelling were the predominant responses within subsegments with low ESS and HRPs. In non-stenotic FAs, low ESS was associated with HRPs vs. non-HRPs (29 vs. 3%, P < 0.05). Arteries with increased shear stress score had increased frequency of HRPs and were associated with ACS vs. stable angina. Conclusion Local low ESS and expansive lumen remodelling are associated with HRP. Arteries with increased shear stress score have increased frequency of HRPs and propensity to present with ACS.
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Affiliation(s)
- Yiannis S Chatzizisis
- Cardiovascular Biology and Biomechanics Laboratory, Cardiovascular Division, College of Medicine, University of Nebraska Medical Center, Omaha, NE, USA.,Cardiovascular Division, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.,First Department of Cardiology, AHEPA University Hospital, Aristotle University Medical School, Thessaloniki, Greece
| | - Konstantinos Toutouzas
- First Department of Cardiology, Hippokration Hospital, Athens University Medical School, Athens, Greece
| | - Andreas A Giannopoulos
- First Department of Cardiology, AHEPA University Hospital, Aristotle University Medical School, Thessaloniki, Greece.,Applied Imaging Science Laboratory, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Maria Riga
- First Department of Cardiology, Hippokration Hospital, Athens University Medical School, Athens, Greece
| | - Antonios P Antoniadis
- Cardiovascular Division, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.,First Department of Cardiology, AHEPA University Hospital, Aristotle University Medical School, Thessaloniki, Greece
| | - Yusuke Fujinom
- Department of Cardiology, New Tokyo Hospital, Chiba, Japan
| | - Dimitrios Mitsouras
- Applied Imaging Science Laboratory, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Vassilis G Koutkias
- Laboratory of Medical Informatics, Aristotle University Medical School, Thessaloniki, Greece.,Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Grigorios Cheimariotis
- Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Charalampos Doulaverakis
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Ioannis Tsampoulatidis
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Ioanna Chouvarda
- Laboratory of Medical Informatics, Aristotle University Medical School, Thessaloniki, Greece.,Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Ioannis Kompatsiaris
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Sunao Nakamura
- Department of Cardiology, New Tokyo Hospital, Chiba, Japan
| | - Frank J Rybicki
- Applied Imaging Science Laboratory, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Nicos Maglaveras
- Laboratory of Medical Informatics, Aristotle University Medical School, Thessaloniki, Greece.,Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Dimitris Tousoulis
- First Department of Cardiology, Hippokration Hospital, Athens University Medical School, Athens, Greece
| | - George D Giannoglou
- First Department of Cardiology, AHEPA University Hospital, Aristotle University Medical School, Thessaloniki, Greece
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7
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Shi C, Luo X, Guo J, Najdovski Z, Fukuda T, Ren H. Three-Dimensional Intravascular Reconstruction Techniques Based on Intravascular Ultrasound: A Technical Review. IEEE J Biomed Health Inform 2018; 22:806-817. [DOI: 10.1109/jbhi.2017.2703903] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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8
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Ormiston JA, Kassab G, Finet G, Chatzizisis YS, Foin N, Mickley TJ, Chiastra C, Murasato Y, Hikichi Y, Wentzel JJ, Darremont O, Iwasaki K, Lefèvre T, Louvard Y, Beier S, Hojeibane H, Netravali A, Wooton J, Cowan B, Webster MW, Medrano-Gracia P, Stankovic G. Bench testing and coronary artery bifurcations: a consensus document from the European Bifurcation Club. EUROINTERVENTION 2018; 13:e1794-e1803. [PMID: 29131803 DOI: 10.4244/eij-d-17-00270] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
This is a consensus document from the European Bifurcation Club concerning bench testing in coronary artery bifurcations. It is intended to provide guidelines for bench assessment of stents and other strategies in coronary bifurcation treatment where the United States Food and Drug Administration (FDA) or International Organization for Standardization (ISO) guidelines are limited or absent. These recommendations provide guidelines rather than a step-by-step manual. We provide data on the anatomy of bifurcations and elastic response of coronary arteries to aid model construction. We discuss testing apparatus, bench testing endpoints and bifurcation nomenclature.
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9
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Cheimariotis GA, Chatzizisis YS, Koutkias VG, Toutouzas K, Giannopoulos A, Riga M, Chouvarda I, Antoniadis AP, Doulaverakis C, Tsamboulatidis I, Kompatsiaris I, Giannoglou GD, Maglaveras N. ARCOCT: Automatic detection of lumen border in intravascular OCT images. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2017; 151:21-32. [PMID: 28947003 DOI: 10.1016/j.cmpb.2017.08.007] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2016] [Revised: 07/29/2017] [Accepted: 08/08/2017] [Indexed: 06/07/2023]
Abstract
BACKGROUND AND OBJECTIVE Intravascular optical coherence tomography (OCT) is an invaluable tool for the detection of pathological features on the arterial wall and the investigation of post-stenting complications. Computational lumen border detection in OCT images is highly advantageous, since it may support rapid morphometric analysis. However, automatic detection is very challenging, since OCT images typically include various artifacts that impact image clarity, including features such as side branches and intraluminal blood presence. This paper presents ARCOCT, a segmentation method for fully-automatic detection of lumen border in OCT images. METHODS ARCOCT relies on multiple, consecutive processing steps, accounting for image preparation, contour extraction and refinement. In particular, for contour extraction ARCOCT employs the transformation of OCT images based on physical characteristics such as reflectivity and absorption of the tissue and, for contour refinement, local regression using weighted linear least squares and a 2nd degree polynomial model is employed to achieve artifact and small-branch correction as well as smoothness of the artery mesh. Our major focus was to achieve accurate contour delineation in the various types of OCT images, i.e., even in challenging cases with branches and artifacts. RESULTS ARCOCT has been assessed in a dataset of 1812 images (308 from stented and 1504 from native segments) obtained from 20 patients. ARCOCT was compared against ground-truth manual segmentation performed by experts on the basis of various geometric features (e.g. area, perimeter, radius, diameter, centroid, etc.) and closed contour matching indicators (the Dice index, the Hausdorff distance and the undirected average distance), using standard statistical analysis methods. The proposed method was proven very efficient and close to the ground-truth, exhibiting non statistically-significant differences for most of the examined metrics. CONCLUSIONS ARCOCT allows accurate and fully-automated lumen border detection in OCT images.
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Affiliation(s)
- Grigorios-Aris Cheimariotis
- Lab of Computing Medical Informatics and Biomedical Imaging Technologies, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece; Institute of Applied Biosciences, Center for Research and Technology - Hellas, Thermi, Thessaloniki, Greece
| | - Yiannis S Chatzizisis
- Cardiovascular Division, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Vassilis G Koutkias
- Institute of Applied Biosciences, Center for Research and Technology - Hellas, Thermi, Thessaloniki, Greece; Lab of Computing Medical Informatics and Biomedical Imaging Technologies, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Konstantinos Toutouzas
- 1st Department of Cardiology, Athens Medical School, Hippokration Hospital, Athens, Greece
| | - Andreas Giannopoulos
- Applied Imaging Science Lab, Radiology Department, Brigham and Women's Hospital, Harvard Medical School, Massachusetts, USA
| | - Maria Riga
- 1st Department of Cardiology, Athens Medical School, Hippokration Hospital, Athens, Greece
| | - Ioanna Chouvarda
- Lab of Computing Medical Informatics and Biomedical Imaging Technologies, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece; Institute of Applied Biosciences, Center for Research and Technology - Hellas, Thermi, Thessaloniki, Greece
| | - Antonios P Antoniadis
- Cardiovascular Division, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Charalambos Doulaverakis
- Information Technologies Institute, Center for Research and Technology - Hellas, Thermi, Thessaloniki, Greece
| | - Ioannis Tsamboulatidis
- Information Technologies Institute, Center for Research and Technology - Hellas, Thermi, Thessaloniki, Greece
| | - Ioannis Kompatsiaris
- Information Technologies Institute, Center for Research and Technology - Hellas, Thermi, Thessaloniki, Greece
| | - George D Giannoglou
- 1st Department of Cardiology, AHEPA University Hospital, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Nicos Maglaveras
- Lab of Computing Medical Informatics and Biomedical Imaging Technologies, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece; Institute of Applied Biosciences, Center for Research and Technology - Hellas, Thermi, Thessaloniki, Greece.
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10
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Narayan SA, Qureshi S. Multimodality medical image fusion: applications in congenital cardiology. Future Cardiol 2017. [PMID: 28631508 DOI: 10.2217/fca-2017-0041] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Affiliation(s)
| | - Shakeel Qureshi
- Evelina London Children's Hospital, Guy's and St Thomas Hospital, London, UK
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11
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Reconstruction of coronary arteries from X-ray angiography: A review. Med Image Anal 2016; 32:46-68. [PMID: 27054277 DOI: 10.1016/j.media.2016.02.007] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2015] [Revised: 01/29/2016] [Accepted: 02/22/2016] [Indexed: 01/18/2023]
Abstract
Despite continuous progress in X-ray angiography systems, X-ray coronary angiography is fundamentally limited by its 2D representation of moving coronary arterial trees, which can negatively impact assessment of coronary artery disease and guidance of percutaneous coronary intervention. To provide clinicians with 3D/3D+time information of coronary arteries, methods computing reconstructions of coronary arteries from X-ray angiography are required. Because of several aspects (e.g. cardiac and respiratory motion, type of X-ray system), reconstruction from X-ray coronary angiography has led to vast amount of research and it still remains as a challenging and dynamic research area. In this paper, we review the state-of-the-art approaches on reconstruction of high-contrast coronary arteries from X-ray angiography. We mainly focus on the theoretical features in model-based (modelling) and tomographic reconstruction of coronary arteries, and discuss the evaluation strategies. We also discuss the potential role of reconstructions in clinical decision making and interventional guidance, and highlight areas for future research.
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12
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Toutouzas K, Chatzizisis YS, Riga M, Giannopoulos A, Antoniadis AP, Tu S, Fujino Y, Mitsouras D, Doulaverakis C, Tsampoulatidis I, Koutkias VG, Bouki K, Li Y, Chouvarda I, Cheimariotis G, Maglaveras N, Kompatsiaris I, Nakamura S, Reiber JHC, Rybicki F, Karvounis H, Stefanadis C, Tousoulis D, Giannoglou GD. Accurate and reproducible reconstruction of coronary arteries and endothelial shear stress calculation using 3D OCT: comparative study to 3D IVUS and 3D QCA. Atherosclerosis 2015; 240:510-9. [PMID: 25932791 DOI: 10.1016/j.atherosclerosis.2015.04.011] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2015] [Revised: 03/15/2015] [Accepted: 04/06/2015] [Indexed: 11/29/2022]
Abstract
BACKGROUND Geometrically-correct 3D OCT is a new imaging modality with the potential to investigate the association of local hemodynamic microenvironment with OCT-derived high-risk features. We aimed to describe the methodology of 3D OCT and investigate the accuracy, inter- and intra-observer agreement of 3D OCT in reconstructing coronary arteries and calculating ESS, using 3D IVUS and 3D QCA as references. METHODS-RESULTS 35 coronary artery segments derived from 30 patients were reconstructed in 3D space using 3D OCT. 3D OCT was validated against 3D IVUS and 3D QCA. The agreement in artery reconstruction among 3D OCT, 3D IVUS and 3D QCA was assessed in 3-mm-long subsegments using lumen morphometry and ESS parameters. The inter- and intra-observer agreement of 3D OCT, 3D IVUS and 3D QCA were assessed in a representative sample of 61 subsegments (n = 5 arteries). The data processing times for each reconstruction methodology were also calculated. There was a very high agreement between 3D OCT vs. 3D IVUS and 3D OCT vs. 3D QCA in terms of total reconstructed artery length and volume, as well as in terms of segmental morphometric and ESS metrics with mean differences close to zero and narrow limits of agreement (Bland-Altman analysis). 3D OCT exhibited excellent inter- and intra-observer agreement. The analysis time with 3D OCT was significantly lower compared to 3D IVUS. CONCLUSIONS Geometrically-correct 3D OCT is a feasible, accurate and reproducible 3D reconstruction technique that can perform reliable ESS calculations in coronary arteries.
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Affiliation(s)
- Konstantinos Toutouzas
- First Department of Cardiology, Hippokration Hospital, Athens University Medical School, Athens, Greece
| | - Yiannis S Chatzizisis
- Cardiovascular Division, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; First Department of Cardiology, AHEPA University Hospital, Aristotle University Medical School, Thessaloniki, Greece.
| | - Maria Riga
- First Department of Cardiology, Hippokration Hospital, Athens University Medical School, Athens, Greece
| | - Andreas Giannopoulos
- First Department of Cardiology, AHEPA University Hospital, Aristotle University Medical School, Thessaloniki, Greece
| | - Antonios P Antoniadis
- Cardiovascular Division, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; First Department of Cardiology, AHEPA University Hospital, Aristotle University Medical School, Thessaloniki, Greece
| | - Shengxian Tu
- Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands; Biomedical Instrument Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Yusuke Fujino
- Department of Cardiology, New Tokyo Hospital, Chiba, Japan
| | - Dimitrios Mitsouras
- Applied Imaging Science Laboratory, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Charalampos Doulaverakis
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Ioannis Tsampoulatidis
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Vassilis G Koutkias
- Laboratory of Medical Informatics, Aristotle University Medical School, Thessaloniki, Greece; Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Konstantina Bouki
- Second Department of Cardiology, General Hospital of Nikaia, Piraeus, Greece
| | - Yingguang Li
- Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Ioanna Chouvarda
- Laboratory of Medical Informatics, Aristotle University Medical School, Thessaloniki, Greece; Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Grigorios Cheimariotis
- Laboratory of Medical Informatics, Aristotle University Medical School, Thessaloniki, Greece; Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Nicos Maglaveras
- Laboratory of Medical Informatics, Aristotle University Medical School, Thessaloniki, Greece; Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Ioannis Kompatsiaris
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Sunao Nakamura
- Department of Cardiology, New Tokyo Hospital, Chiba, Japan
| | - Johan H C Reiber
- Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Frank Rybicki
- Applied Imaging Science Laboratory, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Haralambos Karvounis
- First Department of Cardiology, AHEPA University Hospital, Aristotle University Medical School, Thessaloniki, Greece
| | - Christodoulos Stefanadis
- First Department of Cardiology, Hippokration Hospital, Athens University Medical School, Athens, Greece
| | - Dimitris Tousoulis
- First Department of Cardiology, Hippokration Hospital, Athens University Medical School, Athens, Greece
| | - George D Giannoglou
- First Department of Cardiology, AHEPA University Hospital, Aristotle University Medical School, Thessaloniki, Greece
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13
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Ragkousis GE, Curzen N, Bressloff NW. Computational Modelling of Multi-folded Balloon Delivery Systems for Coronary Artery Stenting: Insights into Patient-Specific Stent Malapposition. Ann Biomed Eng 2015; 43:1786-802. [PMID: 25575740 DOI: 10.1007/s10439-014-1237-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2014] [Accepted: 12/22/2014] [Indexed: 10/24/2022]
Abstract
Despite the clinical effectiveness of coronary artery stenting, percutaneous coronary intervention or "stenting" is not free of complications. Stent malapposition (SM) is a common feature of "stenting" particularly in challenging anatomy, such as that characterized by long, tortuous and bifurcated segments. SM is an important risk factor for stent thrombosis and recently it has been associated with longitudinal stent deformation. SM is the result of many factors including reference diameter, vessel tapering, the deployment pressure and the eccentric anatomy of the vessel. For the purpose of the present paper, virtual multi-folded balloon models have been developed for simulated deployment in both constant and varying diameter vessels under uniform pressure. The virtual balloons have been compared to available compliance charts to ensure realistic inflation response at nominal pressures. Thereafter, patient-specific simulations of stenting have been conducted aiming to reduce SM. Different scalar indicators, which allow a more global quantitative judgement of the mechanical performance of each delivery system, have been implemented. The results indicate that at constant pressure, the proposed balloon models can increase the minimum stent lumen area and thereby significantly decrease SM.
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Affiliation(s)
- Georgios E Ragkousis
- Computational Engineering & Design Group, Engineering & the Environment, University of Southampton, Boldrewood Campus, Southampton, SO16 7QF, UK
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14
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Carrizo S, Xie X, Peinado-Peinado R, Sánchez-Recalde A, Jiménez-Valero S, Galeote-Garcia G, Moreno R. Functional assessment of coronary artery disease by intravascular ultrasound and computational fluid dynamics simulation. Rev Port Cardiol 2014; 33:645.e1-4. [DOI: 10.1016/j.repc.2014.03.013] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2014] [Accepted: 03/28/2014] [Indexed: 11/17/2022] Open
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15
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Carrizo S, Xie X, Peinado-Peinado R, Sánchez-Recalde A, Jiménez-Valero S, Galeote-Garcia G, Moreno R. Functional assessment of coronary artery disease by intravascular ultrasound and computational fluid dynamics simulation. REVISTA PORTUGUESA DE CARDIOLOGIA (ENGLISH EDITION) 2014. [DOI: 10.1016/j.repce.2014.03.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
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16
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Chatzizisis YS, Koutkias VG, Toutouzas K, Giannopoulos A, Chouvarda I, Riga M, Antoniadis AP, Cheimariotis G, Doulaverakis C, Tsampoulatidis I, Bouki K, Kompatsiaris I, Stefanadis C, Maglaveras N, Giannoglou GD. Clinical validation of an algorithm for rapid and accurate automated segmentation of intracoronary optical coherence tomography images. Int J Cardiol 2014; 172:568-80. [PMID: 24529948 DOI: 10.1016/j.ijcard.2014.01.071] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2013] [Accepted: 01/18/2014] [Indexed: 11/29/2022]
Abstract
OBJECTIVES The analysis of intracoronary optical coherence tomography (OCT) images is based on manual identification of the lumen contours and relevant structures. However, manual image segmentation is a cumbersome and time-consuming process, subject to significant intra- and inter-observer variability. This study aims to present and validate a fully-automated method for segmentation of intracoronary OCT images. METHODS We studied 20 coronary arteries (mean length=39.7±10.0 mm) from 20 patients who underwent a clinically-indicated cardiac catheterization. The OCT images (n=1812) were segmented manually, as well as with a fully-automated approach. A semi-automated variation of the fully-automated algorithm was also applied. Using certain lumen size and lumen shape characteristics, the fully- and semi-automated segmentation algorithms were validated over manual segmentation, which was considered as the gold standard. RESULTS Linear regression and Bland-Altman analysis demonstrated that both the fully-automated and semi-automated segmentation had a very high agreement with the manual segmentation, with the semi-automated approach being slightly more accurate than the fully-automated method. The fully-automated and semi-automated OCT segmentation reduced the analysis time by more than 97% and 86%, respectively, compared to manual segmentation. CONCLUSIONS In the current work we validated a fully-automated OCT segmentation algorithm, as well as a semi-automated variation of it in an extensive "real-life" dataset of OCT images. The study showed that our algorithm can perform rapid and reliable segmentation of OCT images.
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Affiliation(s)
- Yiannis S Chatzizisis
- Cardiovascular Engineering and Atherosclerosis Laboratory, First Department of Cardiology, AHEPA University Hospital, Aristotle University Medical School, Thessaloniki, Greece.
| | - Vassilis G Koutkias
- Laboratory of Medical Informatics, Aristotle University Medical School, Thessaloniki, Greece
| | - Konstantinos Toutouzas
- First Department of Cardiology, Hippokration Hospital, Athens University Medical School, Athens, Greece
| | - Andreas Giannopoulos
- Cardiovascular Engineering and Atherosclerosis Laboratory, First Department of Cardiology, AHEPA University Hospital, Aristotle University Medical School, Thessaloniki, Greece
| | - Ioanna Chouvarda
- Laboratory of Medical Informatics, Aristotle University Medical School, Thessaloniki, Greece
| | - Maria Riga
- First Department of Cardiology, Hippokration Hospital, Athens University Medical School, Athens, Greece
| | - Antonios P Antoniadis
- Cardiovascular Engineering and Atherosclerosis Laboratory, First Department of Cardiology, AHEPA University Hospital, Aristotle University Medical School, Thessaloniki, Greece
| | - Grigorios Cheimariotis
- Laboratory of Medical Informatics, Aristotle University Medical School, Thessaloniki, Greece
| | - Charalampos Doulaverakis
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Ioannis Tsampoulatidis
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Konstantina Bouki
- Second Department of Cardiology, General Hospital of Nikaia, Piraeus, Greece
| | - Ioannis Kompatsiaris
- Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Christodoulos Stefanadis
- First Department of Cardiology, Hippokration Hospital, Athens University Medical School, Athens, Greece
| | - Nicos Maglaveras
- Laboratory of Medical Informatics, Aristotle University Medical School, Thessaloniki, Greece
| | - George D Giannoglou
- Cardiovascular Engineering and Atherosclerosis Laboratory, First Department of Cardiology, AHEPA University Hospital, Aristotle University Medical School, Thessaloniki, Greece
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