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Tsiknakis N, Spanakis C, Tsoumpou P, Karanasiou G, Karanasiou G, Sakellarios A, Rigas G, Kyriakidis S, Papafaklis MI, Nikopoulos S, Gijsen F, Michalis L, Fotiadis DI, Marias K. OCT sequence registration before and after percutaneous coronary intervention (stent implantation). Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2022.104251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
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Karmakar A, Olender ML, Marlevi D, Shlofmitz E, Shlofmitz RA, Edelman ER, Nezami FR. Framework for lumen-based nonrigid tomographic coregistration of intravascular images. J Med Imaging (Bellingham) 2022; 9:044006. [PMID: 36043032 PMCID: PMC9402451 DOI: 10.1117/1.jmi.9.4.044006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 08/09/2022] [Indexed: 08/25/2023] Open
Abstract
Purpose: Modern medical imaging enables clinicians to effectively diagnose, monitor, and treat diseases. However, clinical decision-making often relies on combined evaluation of either longitudinal or disparate image sets, necessitating coregistration of multiple acquisitions. Promising coregistration techniques have been proposed; however, available methods predominantly rely on time-consuming manual alignments or nontrivial feature extraction with limited clinical applicability. Addressing these issues, we present a fully automated, robust, nonrigid registration method, allowing for coregistering of multimodal tomographic vascular image datasets using luminal annotation as the sole alignment feature. Approach: Registration is carried out by the use of the registration metrics defined exclusively for lumens shapes. The framework is primarily broken down into two sequential parts: longitudinal and rotational registration. Both techniques are inherently nonrigid in nature to compensate for motion and acquisition artifacts in tomographic images. Results: Performance was evaluated across multimodal intravascular datasets, as well as in longitudinal cases assessing pre-/postinterventional coronary images. Low registration error in both datasets highlights method utility, with longitudinal registration errors-evaluated throughout the paired tomographic sequences-of 0.29 ± 0.14 mm ( < 2 longitudinal image frames) and 0.18 ± 0.16 mm ( < 1 frame) for multimodal and interventional datasets, respectively. Angular registration for the interventional dataset rendered errors of 7.7 ° ± 6.7 ° , and 29.1 ° ± 23.2 ° for the multimodal set. Conclusions: Satisfactory results across datasets, along with additional attributes such as the ability to avoid longitudinal over-fitting and correct nonlinear catheter rotation during nonrigid rotational registration, highlight the potential wide-ranging applicability of our presented coregistration method.
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Affiliation(s)
- Abhishek Karmakar
- Cornell University, Department of Biomedical Engineering, Ithaca, New York, United States
| | - Max L. Olender
- Massachusetts Institute of Technology, Institute for Medical Engineering and Science, Cambridge, Massachusetts, United States
| | - David Marlevi
- Massachusetts Institute of Technology, Institute for Medical Engineering and Science, Cambridge, Massachusetts, United States
| | - Evan Shlofmitz
- St. Francis Hospital, Department of Cardiology, Roslyn, New York, United States
| | | | - Elazer R. Edelman
- Massachusetts Institute of Technology, Institute for Medical Engineering and Science, Cambridge, Massachusetts, United States
| | - Farhad R. Nezami
- Brigham and Women’s Hospital, Harvard Medical School, Division of Thoracic and Cardiac Surgery, Boston, Massachusetts, United States
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Tsiknakis N, Spanakis C, Tsompou P, Karanasiou G, Karanasiou G, Sakellarios A, Rigas G, Kyriakidis S, Papafaklis M, Nikopoulos S, Gijsen F, Michalis L, Fotiadis DI, Marias K. IVUS Longitudinal and Axial Registration for Atherosclerosis Progression Evaluation. Diagnostics (Basel) 2021; 11:1513. [PMID: 34441447 PMCID: PMC8394087 DOI: 10.3390/diagnostics11081513] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 08/20/2021] [Accepted: 08/21/2021] [Indexed: 11/16/2022] Open
Abstract
Intravascular ultrasound (IVUS) imaging offers accurate cross-sectional vessel information. To this end, registering temporal IVUS pullbacks acquired at two time points can assist the clinicians to accurately assess pathophysiological changes in the vessels, disease progression and the effect of the treatment intervention. In this paper, we present a novel two-stage registration framework for aligning pairs of longitudinal and axial IVUS pullbacks. Initially, we use a Dynamic Time Warping (DTW)-based algorithm to align the pullbacks in a temporal fashion. Subsequently, an intensity-based registration method, that utilizes a variant of the Harmony Search optimizer to register each matched pair of the pullbacks by maximizing their Mutual Information, is applied. The presented method is fully automated and only required two single global image-based measurements, unlike other methods that require extraction of morphology-based features. The data used includes 42 synthetically generated pullback pairs, achieving an alignment error of 0.1853 frames per pullback, a rotation error 0.93° and a translation error of 0.0161 mm. In addition, it was also tested on 11 baseline and follow-up, and 10 baseline and post-stent deployment real IVUS pullback pairs from two clinical centres, achieving an alignment error of 4.3±3.9 for the longitudinal registration, and a distance and a rotational error of 0.56±0.323 mm and 12.4°±10.5°, respectively, for the axial registration. Although the performance of the proposed method does not match that of the state-of-the-art, our method relies on computationally lighter steps for its computations, which is crucial in real-time applications. On the other hand, the proposed method performs even or better that the state-of-the-art when considering the axial registration. The results indicate that the proposed method can support clinical decision making and diagnosis based on sequential imaging examinations.
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Affiliation(s)
- Nikos Tsiknakis
- Computational BioMedicine Laboratory, Institute of Computer Science, Foundation for Research and Technology Hellas—FORTH, 70013 Heraklion, Greece;
| | - Constantinos Spanakis
- Computational BioMedicine Laboratory, Institute of Computer Science, Foundation for Research and Technology Hellas—FORTH, 70013 Heraklion, Greece;
| | - Panagiota Tsompou
- Department of Biomedical Research, Institute of Molecular Biology and Biotechnology—FORTH, University Campus of Ioannina, 45115 Ioannina, Greece; (P.T.); (G.K.); (G.K.); (A.S.); (S.K.); (D.I.F.)
- Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, 45110 Ioannina, Greece;
| | - Georgia Karanasiou
- Department of Biomedical Research, Institute of Molecular Biology and Biotechnology—FORTH, University Campus of Ioannina, 45115 Ioannina, Greece; (P.T.); (G.K.); (G.K.); (A.S.); (S.K.); (D.I.F.)
| | - Gianna Karanasiou
- Department of Biomedical Research, Institute of Molecular Biology and Biotechnology—FORTH, University Campus of Ioannina, 45115 Ioannina, Greece; (P.T.); (G.K.); (G.K.); (A.S.); (S.K.); (D.I.F.)
| | - Antonis Sakellarios
- Department of Biomedical Research, Institute of Molecular Biology and Biotechnology—FORTH, University Campus of Ioannina, 45115 Ioannina, Greece; (P.T.); (G.K.); (G.K.); (A.S.); (S.K.); (D.I.F.)
- Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, 45110 Ioannina, Greece;
| | - George Rigas
- Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, 45110 Ioannina, Greece;
| | - Savvas Kyriakidis
- Department of Biomedical Research, Institute of Molecular Biology and Biotechnology—FORTH, University Campus of Ioannina, 45115 Ioannina, Greece; (P.T.); (G.K.); (G.K.); (A.S.); (S.K.); (D.I.F.)
| | - Michael Papafaklis
- Department of Cardiology, Medical School, University of Ioannina, 45110 Ioannina, Greece; (M.P.); (S.N.); (L.M.)
| | - Sotirios Nikopoulos
- Department of Cardiology, Medical School, University of Ioannina, 45110 Ioannina, Greece; (M.P.); (S.N.); (L.M.)
| | - Frank Gijsen
- Department of Cardiology, Erasmus University Rotterdam, 3062 PA Rotterdam, The Netherlands;
| | - Lampros Michalis
- Department of Cardiology, Medical School, University of Ioannina, 45110 Ioannina, Greece; (M.P.); (S.N.); (L.M.)
| | - Dimitrios I. Fotiadis
- Department of Biomedical Research, Institute of Molecular Biology and Biotechnology—FORTH, University Campus of Ioannina, 45115 Ioannina, Greece; (P.T.); (G.K.); (G.K.); (A.S.); (S.K.); (D.I.F.)
- Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, 45110 Ioannina, Greece;
| | - Kostas Marias
- Computational BioMedicine Laboratory, Institute of Computer Science, Foundation for Research and Technology Hellas—FORTH, 70013 Heraklion, Greece;
- Department of Electrical and Computer Engineering, Hellenic Mediterranean University, 71004 Heraklion, Greece
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Evaluation of a framework for the co-registration of intravascular ultrasound and optical coherence tomography coronary artery pullbacks. J Biomech 2016; 49:4048-4056. [PMID: 27836501 DOI: 10.1016/j.jbiomech.2016.10.040] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2016] [Revised: 10/24/2016] [Accepted: 10/25/2016] [Indexed: 01/03/2023]
Abstract
A growing number of studies have used a combination of intravascular ultrasound (IVUS) and optical coherence tomography (OCT) for the assessment of atherosclerotic plaques. Given their respective strengths these imaging modalities highly complement each other. Correlations of hemodynamics and coronary artery disease (CAD) have been extensively investigated with both modalities separately, though not concurrently due to challenges in image registration. Manual co-registration of these modalities is a time expensive task subject to human error, and the development of an automatic method has not been previously addressed. We developed a framework that uses dynamic time warping for the longitudinal co-registration and dynamic programming for the circumferential co-registration of images and evaluated the methodology in a cohort (n = 12) of patients with moderate CAD. Excellent correlation was seen between the algorithm and two expert readers for longitudinal co-registration (CCC = 0.9964, CCC = 0.9959) and circumferential co-registration (CCC = 0.9688, CCC = 0.9598). The mean error of the circumferential co-registration angle was found to be within 10%. A framework for the co-registration of IVUS and OCT pullbacks has been developed which provides a foundation for comprehensive studies of CAD biomechanics.
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Zhang L, Wahle A, Chen Z, Zhang L, Downe RW, Kovarnik T, Sonka M. Simultaneous Registration of Location and Orientation in Intravascular Ultrasound Pullbacks Pairs Via 3D Graph-Based Optimization. IEEE TRANSACTIONS ON MEDICAL IMAGING 2015; 34:2550-61. [PMID: 26080381 PMCID: PMC4700818 DOI: 10.1109/tmi.2015.2444815] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
A novel method is reported for simultaneous registration of location (axial direction) and orientation (circumferential direction) of two intravascular ultrasound (IVUS) pullbacks of the same vessel taken at different times. Monitoring plaque progression or regression (e.g., during lipid treatment) is of high clinical relevance. Our method uses a 3D graph optimization approach, in which the cost function jointly reflects similarity of plaque morphology and plaque/perivascular image appearance. Graph arcs incorporate prior information about temporal correspondence of the two IVUS sequences and limited angular twisting between consecutive IVUS images. Additionally, our approach automatically identifies starting and ending frame pairs in the two IVUS pullbacks. Validation of our method was performed in 29 pairs of IVUS baseline/follow-up pullback sequences consisting of 8 622 IVUS image frames in total. In comparison to manual registration by three experts, the average location and orientation registration errors ranged from 0.72 mm to 0.79 mm and from 7.3(°) to 9.3(°), respectively, all close to the inter-observer variability with no difference being statistically significant (p = NS). Rotation angles determined by our automated approach and expert observers showed high correlation (r(2) of 0.97 to 0.98) and agreed closely (mutual bias between the automated method and expert observers ranged from -1.57(°) to 0.15(°)). Compared with state-of-the-art approaches, the new method offers lower errors in both location and orientation registration. Our method offers highly automated and accurate IVUS pullback registration and can be employed in IVUS-based studies of coronary disease progression, enabling more focal studies of coronary plaque development and transition of vulnerability.
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Affiliation(s)
- Ling Zhang
- Iowa Institute for Biomedical Imaging and the Department of Electrical & Computer Engineering, University of Iowa, Iowa City, IA 52242, USA
| | - Andreas Wahle
- Iowa Institute for Biomedical Imaging and the Department of Electrical & Computer Engineering, University of Iowa, Iowa City, IA 52242, USA
| | - Zhi Chen
- Iowa Institute for Biomedical Imaging and the Department of Electrical & Computer Engineering, University of Iowa, Iowa City, IA 52242, USA
| | - Li Zhang
- Iowa Institute for Biomedical Imaging and the Department of Electrical & Computer Engineering, University of Iowa, Iowa City, IA 52242, USA
| | - Richard W. Downe
- Iowa Institute for Biomedical Imaging and the Department of Electrical & Computer Engineering, University of Iowa, Iowa City, IA 52242, USA
| | - Tomas Kovarnik
- The 2nd Department of Internal Medicine of General University Hospital in Prague and Charles University, Prague, Czech Republic
| | - Milan Sonka
- Iowa Institute for Biomedical Imaging and the Department of Electrical & Computer Engineering, University of Iowa, Iowa City, IA 52242, USA
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