Cardiac allograft vasculopathy (CAV) accounts for about 30% of all heart-transplant (HTx) patient deaths. For patients at high risk for CAV complications after HTx, therapy must be initiated early to be effective. Therefore, new phenotyping approaches are needed to identify such HTx patients at the earliest possible time. Coronary optical coherence tomography (OCT) images were acquired from 50 HTx patients 1 and 12 months after HTx. Quantitative analysis of coronary wall morphology used LOGISMOS segmentation strategy to simultaneously identify three wall-layer surfaces for the entire pullback length in 3D: luminal, outer intimal, and outer medial surfaces. To quantify changes of coronary wall morphology between 1 and 12 months after HTx, the two pullbacks were mutually co-registered. Validation of layer thickness measurements showed high accuracy of performed layer analyses with layer thickness measures correlating well with manually-defined independent standard (Rautomated2 = 0.93, y=1.0x-6.2μm), average intimal+medial thickness errors were 4.98 ± 31.24 µm, comparable with inter-observer variability. Quantitative indices of coronary wall morphology 1 month and 12 months after HTx showed significant local as well as regional changes associated with CAV progression. Some of the newly available fully-3D baseline indices (intimal layer brightness, medial layer brightness, medial thickness, and intimal+medial thickness) were associated with CAV-related progression of intimal thickness showing promise of identifying patients subjected to rapid intimal thickening at 12 months after HTx from OCT-image data obtained just 1 month after HTx. Our approach allows quantification of location-specific alterations of coronary wall morphology over time and is sensitive even to very small changes of wall layer thicknesses that occur in patients following heart transplant.

2nd Department of Medicine Department of Cardiovascular Medicine 1st Faculty of Medicine Charles University Prague and General University Hospital Prague Czech Republic

Cardiovascular and Transplantation Surgery Center Department of Cardiovascular Diseases St Annes University Hospital and Masaryk University Brno Czech Republic

Institute of Clinical and Experimental Medicine Prague Czech Republic

Iowa Institute for Biomedical Imaging The University of Iowa Iowa City IA 52242 USA

Zobrazit více v PubMed

Bom N, Lancee CT, 1972. Apparatus for ultrasonically examining a hollow organ. UK Patent 1402192.

Chandran KB, Wahle A, Vigmostad SC, Olszewski ME, Rossen JD, Sonka M, 2006. Coronary arteries: Imaging, reconstruction, and fluid dynamic analysis. Critical Reviews in Biomedical Engineering 34, 23–103. PubMed

Chen Z, Wahle A, Guo Z, Zhang H, Karmazin V, Tomasek A, Bedanova H, Lopez JJ, Kovarnik T, Pazdernik M, Sonka M, 2017. Highly automated analysis of intimal and medial thickness in heart-transplant coronary OCT facilitates longitudinal studies of CAV progression. The Journal of Heart and Lung Transplantation 36, S155.

Chih S, Chong AY, Mielniczuk LM, Bhatt DL, Beanlands RS, 2016. Allograft Vasculopathy: The Achilles’ Heel of Heart Transplantation. J. Am. Coll. Cardiol. 68, 80–91. PubMed

Clemmensen TS, Holm NR, Eiskjær H, Jakobsen L, Berg K, Neghabat O, Løgstrup BB, Christiansen EH, Dijkstra J, Terkelsen CJ, et al., 2018. Detection of early changes in the coronary artery microstructure after heart transplantation: A prospective optical coherence tomography study. The Journal of Heart and Lung Transplantation 37, 486–495. PubMed

Clemmensen TS, Holm NR, Eiskjær H, Løgstrup BB, Christiansen EH, Dijkstra J, Barkholt TØ, Terkelsen CJ, Maeng M, Poulsen SH, 2017. Layered Fibrotic Plaques Are the Predominant Component in Cardiac Allograft Vasculopathy: Systematic Findings and Risk Stratification by OCT. JACC Cardiovasc Imaging 10, 773–784. PubMed

Huang D, Swanson E, Lin C, Schuman J, Stinson W, Chang W, Hee M, Flotte T, Gregory K, Puliafito C, Fujimoto J, 1991. Optical Coherence Tomography. Science 254, 1178–1181. PubMed PMC

Jia Y, Shelhamer E, Donahue J, Karayev S, Long J, Girshick R, Guadarrama S, Darrell T, 2014. Caffe: Convolutional architecture for fast feature embedding. arXiv preprint arXiv:1408.5093 .

Kashyap S, Zhang H, Rao K, Sonka M, 2018. Learning-based cost functions for 3-d and 4-d multi-surface multi-object segmentation of knee mri: Data from the osteoarthritis initiative. IEEE transactions on medical imaging 37, 1103–1113. PubMed PMC

Kohli P, Torr PH, 2007. Dynamic graph cuts for efficient inference in Markov Random Fields. IEEE Trans. Pattern Anal. 29, 2079–2088. PubMed

Li K, Wu X, Chen DZ, Sonka M, 2006. Optimal surface segmentation in volumetric images-a graph-theoretic approach. IEEE Trans. Pattern Anal. 28, 119–134. PubMed PMC

Liu S, Eggermont J, Wolterbeek R, Broersen A, Busk CA, Precht H, Lelieveldt BP, Dijkstra J, 2016. Analysis and compensation for the effect of the catheter position on image intensities in intravascular optical coherence tomography. Journal of biomedical optics 21, 126005. PubMed

Mehra MR, Ventura HO, Stapleton DD, Smart FW, Collins TC, Ramee SR, 1995. Presence of severe intimal thickening by intravascular ultrasonography predicts cardiac events in cardiac allograft vasculopathy. J. Heart Lung Transplant. 14, 632–639. PubMed

Oguz I, Sonka M, 2014. LOGISMOS-B: layered optimal graph image segmentation of multiple objects and surfaces for the brain. IEEE Trans Med Imaging 33, 1220–1235. PubMed PMC

Olender ML, Athanasiou LS, José M, Camarero TG, Cascón JD, Consuegra-Sanchez L, Edelman ER, 2017. Estimating the internal elastic membrane cross-sectional area of coronary arteries autonomously using optical coherence tomography images, in: Biomedical & Health Informatics (BHI), 2017 IEEE EMBS International Conference on, IEEE; pp. 109–112.

Pazdernik M, Kovarnik T, Chen Z, Wahle A, Karmazin V, Melenovsky V, Kautzner J, Tomasek A, Bedanova H, Sonka M, 2017a. Increased heart rate after heart transplant is not associated with early progression of cardiac allograft vasculopathy (CAV) — a prospective study using highly automatic coronary optical coherence tomography segmentation software in 3D. The Journal of Heart and Lung Transplantation 36, S297–S298.

Pazdernik M, Kovarnik T, Sonka M, Wahle A, Chen Z, Karmazin V, Kautzner J, Tomasek A, Melenovsky V, Bedanova H, 2017b. Should we pharmacologically modulate renin-aldosterone-angiotensin system (RAAS) to attenuate cardiac allograft vasculopathy (CAV)? A prospective study using highly automated coronary optical coherence tomography segmentation software in 3D. The Journal of Heart and Lung Transplantation 36, S292.

R Core Team, 2016. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing; Vienna, Austria: URL: https://www.R-project.org.

Sermanet P, Eigen D, Zhang X, Mathieu M, Fergus R, LeCun Y, 2013. Over-feat: Integrated recognition, localization and detection using convolutional networks. arXiv preprint arXiv:1312.6229 .

Sharif-Razavian A, Azizpour H, Sullivan J, Carlsson S, 2014. CNN features off-the-shelf: An astounding baseline for recognition, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Workshops, pp. 806–813.

Slager CJ, Wentzel JJ, Schuurbiers JC, Oomen JA, Kloet J, Krams R, von Birgelen C, van der Giessen WJ, Serruys PW, de Feyter PJ, 2000. True 3-dimensional reconstruction of coronary arteries in patients by fusion of angiography and IVUS (ANGUS) and its quantitative validation. Circulation 102, 511–516. PubMed

Sones FM, Shirey EK, 1962. Cine coronary arteriography. Mod Concepts Cardiovasc Dis 31, 735–738. PubMed

Sonka M, Abramoff MD, 2016. Quantitative analysis of retinal OCT. Med Image Anal 33, 165–169. PubMed

Starling RC, Stehlik J, Baran DA, Armstrong B, Stone JR, Ikle D, Morrison Y, Bridges ND, Putheti P, Strom TB, Bhasin M, Guleria I, Chandraker A, Sayegh M, Daly KP, Briscoe DM, Heeger PS, 2016. Multicenter Analysis of Immune Biomarkers and Heart Transplant Outcomes: Results of the Clinical Trials in Organ Transplantation-05 Study. Am. J. Transplant 16, 121–136. PubMed PMC

Stone PH, Coskun AU, Kinlay S, Popma JJ, Sonk a.M., Wahle A, Yeghiazarians Y, Maynard C, Kuntz RE, Feldman CL, 2007. Regions of low endothelial shear stress are the sites where coronary plaque progresses and vascular remodelling occurs in humans: an in vivo serial study. Eur Heart J 28, 705–710. PubMed

Sun S, Sonka M, Beichel RR, 2013. Graph-based IVUS segmentation with efficient computer-aided refinement. IEEE Trans Med Imaging 32, 1536–1549. PubMed PMC

Tsutsui H, Ziada KM, Schoenhagen P, Iyisoy A, Magyar WA, Crowe TD, Klingensmith JD, Vince DG, Rincon G, Hobbs RE, Yamagishi M, Nissen SE, Tuzcu EM, 2001. Lumen loss in transplant coronary artery disease is a biphasic process involving early intimal thickening and late constrictive remodeling: results from a 5-year serial intravascular ultrasound study. Circulation 104, 653–657. PubMed

Wahle A, Lopez JJ, Olszewski ME, Vigmostad SC, Chandran KB, Rossen JD, Sonka M, 2006. Plaque development, vessel curvature, and wall shear stress in coronary arteries assessed by x-ray angiography and intravascular ultrasound. Medical Image Analysis 10, 615–631. PubMed PMC

Wahle A, Prause GP, von Birgelen C, Erbel R, Sonka M, 1999a. Fusion of angiography and intravascular ultrasound in vivo: establishing the absolute 3-D frame orientation. IEEE Trans Biomed Eng 46, 1176–1180. PubMed

Wahle A, Prause PM, DeJong SC, Sonka M, 1999b. Geometrically correct 3-D reconstruction of intravascular ultrasound images by fusion with biplane angiography–methods and validation. IEEE Trans Med Imaging 18, 686–699. PubMed

Wever-Pinzon O, Romero J, Kelesidis I, Wever-Pinzon J, Manrique C, Budge D, Drakos SG, Pina IL, Kfoury AG, Garcia MJ, Stehlik J, 2014. Coronary computed tomography angiography for the detection of cardiac allograft vasculopathy: A meta-analysis of prospective trials. J. Am. Coll. Cardiol. 63, 1992–2004. PubMed

Woo V, Chen Z, Hirai T, Weber JR, Kovarnik T, Wahle A, Sonka M, Lopez JJ, 2015. [TCT-355] An automated computational method for quantification of total fibrous cap volume and mean fibrous cap thickness with optical coherence tomography. Journal of the American College of Cardiology 15, B143–B144.

Yin Y, Zhang X, Williams R, Wu X, Anderson D, Sonka M, 2010. LOGISMOS-Layered optimal graph image segmentation of multiple objects and surfaces: Cartilage segmentation in the knee joint. IEEE Trans. Med. Imaging 29, 2023–2037. PubMed PMC

Zahnd G, Hoogendoorn A, Combaret N, Karanasos A, Péry E, Sarry L, Motreff P, Niessen W, Regar E, Van Soest G, et al., 2017. Contour segmentation of the intima, media, and adventitia layers in intracoronary oct images: application to fully automatic detection of healthy wall regions. International journal of computer assisted radiology and surgery 12, 1923–1936. PubMed PMC

Zhang L, Wahle A, Chen Z, Zhang L, Downe RW, Kovarnik T, Sonka M, 2015. Simultaneous registration of location and orientation in intravascular ultrasound pullbacks pairs via 3D graph-based optimization. IEEE Transactions on Medical Imaging 34, 2550–2561. doi:10.1109/TMI.2015.2444815. PubMed DOI PMC

Acetylsalicylic acid use and development of cardiac allograft vasculopathy: A national prospective study using highly automated 3-D optical coherence tomography analysis

Validation of a semi-automatic software for optical coherence tomography - analysis in heart transplanted patients

Fibrous Cap Thickness Predicts Stable Coronary Plaque Progression: Early Clinical Validation of a Semiautomated OCT Technology

Donor specific anti-HLA antibodies and cardiac allograft vasculopathy: A prospective study using highly automated 3-D optical coherence tomography analysis

Heart rate and early progression of cardiac allograft vasculopathy: A prospective study using highly automated 3-D optical coherence tomography analysis