Michal Pazdernik1, Zhi Chen2, Helena Bedanova3, Josef Kautzner4, Vojtech Melenovsky4, Vladimir Karmazin4, Ivan Malek4, Ales Tomasek3, Eva Ozabalova5, Jan Krejci5, Janka Franekova6, Andreas Wahle2, Honghai Zhang2, Tomas Kovarnik7, Milan Sonka2. 1. Department of Cardiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic; Department of Cardiology, Second Medical School, Charles University, University Hospital Motol, Prague, Czech Republic. Electronic address: michal.pazdernik@email.cz. 2. Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, Iowa, USA. 3. Cardiovascular and Transplantation Surgery, Brno, Czech Republic. 4. Department of Cardiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic. 5. Department of Cardiovascular Diseases, St. Anne's University Hospital and Masaryk University, Brno, Czech Republic. 6. Department of Laboratory Methods, Institute for Clinical and Experimental Medicine, Prague, Czech Republic. 7. Department of Cardiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic; Second Department of Internal Medicine, Department of Cardiovascular Medicine, First Faculty of Medicine, Charles University in Prague and General University Hospital in Prague, Prague, Czech Republic.
Abstract
BACKGROUND: Optical coherence tomography (OCT)-based studies of cardiac allograft vasculopathy (CAV) published thus far have focused mainly on frame-based qualitative analysis of the vascular wall. Full capabilities of this inherently 3-dimensional (3D) imaging modality to quantify CAV have not been fully exploited. METHODS: Coronary OCT imaging was performed at 1 month and 12 months after heart transplant (HTx) during routine surveillance cardiac catheterization. Both baseline and follow-up OCT examinations were analyzed using proprietary, highly automated 3D graph-based optimal segmentation software. Automatically identified borders were efficiently adjudicated using our "just-enough-interaction" graph-based segmentation approach that allows to efficiently correct local and regional segmentation errors without slice-by-slice retracing of borders. RESULTS: A total of 50 patients with paired baseline and follow-up OCT studies were included. After registration of baseline and follow-up pullbacks, a total of 356 ± 89 frames were analyzed per patient. During the first post-transplant year, significant reduction in the mean luminal area (p = 0.028) and progression in mean intimal thickness (p = 0.001) were observed. Proximal parts of imaged coronary arteries were affected more than distal parts (p < 0.001). High levels of LDL cholesterol (p = 0.02) and total cholesterol (p = 0.031) in the first month after HTx were the main factors associated with early CAV development. CONCLUSIONS: Our novel, highly automated 3D OCT image analysis method for analyzing intimal and medial thickness in HTx recipients provides fast, accurate, and highly detailed quantitative data on early CAV changes, which are characterized by significant luminal reduction and intimal thickness progression as early as within the first 12 months after HTx.
BACKGROUND: Optical coherence tomography (OCT)-based studies of cardiac allograft vasculopathy (CAV) published thus far have focused mainly on frame-based qualitative analysis of the vascular wall. Full capabilities of this inherently 3-dimensional (3D) imaging modality to quantify CAV have not been fully exploited. METHODS: Coronary OCT imaging was performed at 1 month and 12 months after heart transplant (HTx) during routine surveillance cardiac catheterization. Both baseline and follow-up OCT examinations were analyzed using proprietary, highly automated 3D graph-based optimal segmentation software. Automatically identified borders were efficiently adjudicated using our "just-enough-interaction" graph-based segmentation approach that allows to efficiently correct local and regional segmentation errors without slice-by-slice retracing of borders. RESULTS: A total of 50 patients with paired baseline and follow-up OCT studies were included. After registration of baseline and follow-up pullbacks, a total of 356 ± 89 frames were analyzed per patient. During the first post-transplant year, significant reduction in the mean luminal area (p = 0.028) and progression in mean intimal thickness (p = 0.001) were observed. Proximal parts of imaged coronary arteries were affected more than distal parts (p < 0.001). High levels of LDL cholesterol (p = 0.02) and total cholesterol (p = 0.031) in the first month after HTx were the main factors associated with early CAV development. CONCLUSIONS: Our novel, highly automated 3D OCT image analysis method for analyzing intimal and medial thickness in HTx recipients provides fast, accurate, and highly detailed quantitative data on early CAV changes, which are characterized by significant luminal reduction and intimal thickness progression as early as within the first 12 months after HTx.
Authors: Michal Pazdernik; Dan Wichterle; Zhi Chen; Helena Bedanova; Josef Kautzner; Vojtech Melenovsky; Vladimir Karmazin; Ivan Malek; Peter Stiavnicky; Ales Tomasek; Eva Ozabalova; Jan Krejci; Andreas Wahle; Honghai Zhang; Tomas Kovarnik; Milan Sonka Journal: Clin Transplant Date: 2020-01-09 Impact factor: 2.863
Authors: Michal Pazdernik; Helena Bedanova; Zhi Chen; Josef Kautzner; Vojtech Melenovsky; Ivan Malek; Antonij Slavcev; Michaela Bartonova; Vladimir Karmazin; Tomas Eckhardt; Ales Tomasek; Eva Ozabalova; Tomas Kovarnik; Peter Wohlfahrt; Milan Sonka Journal: Transpl Immunol Date: 2020-10-15 Impact factor: 2.032