IVUS validation of patient coronary artery lumen area obtained from CT images.
OBJECTIVE
Accurate computed tomography (CT)-based reconstruction of coronary morphometry (diameters, length, bifurcation angles) is important for construction of patient-specific models to aid diagnosis and therapy. The objective of this study is to validate the accuracy of patient coronary artery lumen area obtained from CT images based on intravascular ultrasound (IVUS).


RESULTS
Morphometric data of 5 patient CT scans with 11 arteries from IVUS were reconstructed including the lumen cross sectional area (CSA), diameter and length. The volumetric data from CT images were analyzed at sub-pixel accuracy to obtain accurate vessel center lines and CSA. A new center line extraction approach was used where an initial estimated skeleton in discrete value was obtained using a traditional thinning algorithm. The CSA was determined directly without any circular shape assumptions to provide accurate reconstruction of stenosis. The root-mean-square error (RMSE) for CSA and diameter were 16.2% and 9.5% respectively.


CONCLUSIONS
The image segmentation and CSA extraction algorithm for reconstruction of coronary arteries proved to be accurate for determination of vessel lumen area. This approach provides fundamental morphometric data for patient-specific models to diagnose and treat coronary artery disease.
Department of Biomedical Engineering, Indiana University Purdue University Indianapolis, Indianapolis, Indiana, United States of America.
Tong
T
Luo
Department of Computer Science and Engineering, Wright State University, Fairborn, Ohio, United States of America.
Thomas
T
Wischgoll
Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea.
Bon
B
Kwon Koo
Department of Biomedical Engineering, Indiana University Purdue University Indianapolis, Indianapolis, Indiana, United States of America.
Yunlong
Y
Huo
Department of Biomedical Engineering, Indiana University Purdue University Indianapolis, Indianapolis, Indiana, United States of America ; Department of Surgery, Indiana University Purdue University Indianapolis, Indianapolis, Indiana, United States of America ; Department of Cellular and Integrative Physiology, Indiana University Purdue University Indianapolis, Indianapolis, Indiana, United States of America.
Ghassan S
GS
Kassab
D000465:Algorithms; D003324:Coronary Artery Disease / Q000000981:diagnostic imaging*; D003331:Coronary Vessels / Q000000981:diagnostic imaging*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008953:Models, Anatomic; D014057:Tomography, X-Ray Computed; D018084:Ultrasonography, Interventional