Abstract
Cardiovascular diseases (CVDs) are a leading cause of death worldwide. Cardiovascular diseases can cause many severe life-altering complications if they are not treated in a timely manner, including disability and the loss of ability to work. Of all cardiovascular disease-induced complications, acute myocardial infarction is among the most common and is responsible for nearly three million deaths globally, on a yearly basis. Fractional flow reserve is a measurement of arterial blood pressure, measured on both sides of a coronary artery narrowing which is used for the risk assessment of coronary artery stenosis. Measuring fractional flow reserve, both directly from the coronary artery and analytically, from X-ray angiography images, requires a heavy invasive procedure. Additionally, calculating fractional flow reserve from X-ray angiography images requires a lot of time and effort from the side of a medical professional for manual annotation and correction. This research strives to create a methodology for automatic coronary artery tree 3D reconstruction in the form of a surface point cloud which can be used for virtual fractional flow reserve calculation and assessment using finite element modeling techniques. The main goal of the research is to provide a methodology which reduces manual input expected from the medical professionals to a minimum, which will drastically lower the amount of time and funds required to conduct analysis on cardiovascular disease patients.
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References
GBD 2017 Causes of Death Collaborators. “Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980–2017: A systematic analysis for the Global Burden of Disease Study 2017”. Lancet, 392, pp: 1736–1788, 2018
J.A. Reyes-Retana, L.C. Duque-Ossa MSc, “Acute Myocardial Infarction Biosensor: A Review From Bottom Up”, Current problems in cardiology, vol. 46, issue 3, 2021
R. Komalasari, Nurjanah, M. M. Yoche, “Quality of Life of People with Cardiovascular Disease: A Descriptive Study”, Asian Pac Isl Nurs J, vol. 4, issue 2, pp: 92–96, 2019
M. Loukas, C. Groat, R.Khangura, D. Gueorguieva Owens, R. H. Anderson, “The Normal and Abnormal Anatomy of the Coronary Arteries”, Clinical Anatomy, vol. 22, pp: 114–128, 2009
B. Cohen, B. Hasselbring, “Coronary Heart Disease: A Guide to Diagnosis and Treatment”, second edition, Addicus Books, 2011
P.A. Wielopolski, R. J.M. van Geuns, P. J. de Feyter, M. Oudkerk, “Coronary Arteries”, European Radiology, vol. 10, pp: 12–35, 2000
M. J. Lima, C. J. White, “Coronary Angiography Is the Gold Standard for Patients with Significant Left Ventricular Dysfunction”, Progress in Cardiovascular Diseases, vol. 55, issue 5, pp: 504–508, 2013
P. Schoenhagen, et al. “Non-invasive coronary angiography with multi-detector computed tomography: comparison to conventional X-ray angiography”, Cardiovascular Imaging, vol. 21, pp:63–72, 2005
B.D. Bruyne, J. Sarma, “Fractional flow reserve: a review”, Heart, vol. 94, pp: 949–959, 2008
G.G. Toth, et al. “Standardization of Fractional Flow Reserve Measurements”, Journal of the American College of Cardiology, vol. 68, issue 7, pp:742–753, 2016
M.Stanojević Pirković, O. Pavić, F. Filipović, I. Saveljić, T. Geroski, T. Exarchos, N. Filipović, “FFR Based Patient Risk Classification”, Diagnostics, vol. 13, issue 21, 2023
Pijls, N.H.; de Bruyne, B.; Peels, K.; van der Voort, P.H.; Bonnier, H.J.; Bartunek, J.; Koolen, J.J. “Measurement of fractional flow reserve to assess the functional severity of coronary-artery stenosis” N. Engl. J. Med., vol. 334, 1703–1708., 1996
O. Pavić, L. Dašić, T. Geroski, M. Vasković Jovanović, N. Filipović, “Risk classification for sudden cardiac death in patients with hypertrophic cardiomyopathy based on machine learning algorithms”, Journal of the Serbian Society for Computational Mechanics, vol. 17, issue 2, 2023
A. Milovanović, I. Saveljic, N. Filipović, “Numerical vs analytical comparison with experimental fractional flow reserve values of right coronary artery stenosis”, Technology and Health Care, vol. 31, issue 3, pp:977–990, 2023
M. Kojić, N. Filipović, B. Stojanović, N. Kojić, “Computer Modeling in Bioengineering: Theoretical Background, Examples and Software” John Wiley & Sons: Hoboken, NJ, USA, 2008
R. Cardenes, A. Novikov, J. Gunn, R. Hose, A.F. Frangi, “3D reconstruction of coronary arteries from rotational X-ray angiography”, 9th IEEE International Symposium on Biomedical Imaging (ISBI), pp: 618–621, 2012
A. M. Neubauer et al., “Clinical Feasibility of a Fully Automated 3D Reconstruction of Rotational Coronary X-Ray Angiograms”, Circulation: Cardio-vascular Interventions, vol. 3, issue 1, 2010
X. Wang, C. Peng; X. Liu, Z. Pan, “Functional Assessment of Stenotic Coronary Artery in 3D Geometric Reconstruction From Fusion of Intravascular Ultrasound and X-Ray Angiography”, IEEE Access, vol. 6, pp:53330–53341, 2018
J.Tong, S. Xu, F. Wang, P. Qi, “3D Reconstruction with Coronary Artery Based on Curve Descriptor and Projection Geometry-Constrained Vasculature Matching”, Information. vol. 13, issue 1, 2022.
P. Zhou et al. “A framework of myocardial bridge detection with x-ray angiography sequence”, BioMedical Engineering OnLine, vol. 22, 2023
N. K. E. Abbadi and E. H. A. Saadi, “Blood Vessels Extraction Using Mathematical Morphology” Journal of computer science, vol. 9, no. 10, pp. 1389–1395, 2013.
S.l. Liu, Z.d. Niu, G. Sun and Z.p. Chen, “Gabor filter-based edge detection: A note” Optic, vol. 125, no. 15, pp. 4120–4123, 2014
W.Abu-Ain, S. N. H. S. Abdullah, B. Bataineh, T. Abu-Ain, K. Omar, “Skeletonization Algorithm for Binary Images”, Procedia Technology, vol. 11, pp:704–709, 2013
E.Widyaningrum, R. C. Lindenbergh, “Skeleton-Based Automatic Road Network Extraction From an Orthophoto Colored Point Cloud”, The 40th Asian Conference on Remote Sensing (ACRS), 2019
M. Kalmykova, A. Poyda, V. Ilyin, “An approach to point-to-point reconstruction of 3D structure of coronary arteries from 2D X-ray angiography, based on epipolar constraints”, Procedia Computer Science, vol. 136, pp: 380–389, 2018
Acknowledgments
This research was funded by the Ministry of Science, Technological Development and Innovation of the Republic of Serbia, contract numbers [451-03-47/2023-01/200378 (Institute for Information Technologies, University of Kragujevac) and 451-03-47/2023-01/200107 (Faculty of Engineering, University of Kragujevac)].
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Pavić, O., Filipović, N. (2024). Use Case: 3D Coronary Artery Reconstruction for the Purposes of Virtual FFR Calculation. In: Filipović, N. (eds) In Silico Clinical Trials for Cardiovascular Disease. Springer, Cham. https://doi.org/10.1007/978-3-031-60044-9_12
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DOI: https://doi.org/10.1007/978-3-031-60044-9_12
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