Myocardial segmentation based on coronary anatomy using coronary computed tomography angiography: Development and validation in a pig model.
OBJECTIVE
To validate a method for performing myocardial segmentation based on coronary anatomy using coronary CT angiography (CCTA).


METHODS
Coronary artery-based myocardial segmentation (CAMS) was developed for use with CCTA. To validate and compare this method with the conventional American Heart Association (AHA) classification, a single coronary occlusion model was prepared and validated using six pigs. The unstained occluded coronary territories of the specimens and corresponding arterial territories from CAMS and AHA segmentations were compared using slice-by-slice matching and 100 virtual myocardial columns.


RESULTS
CAMS more precisely predicted ischaemic area than the AHA method, as indicated by 95% versus 76% (p < 0.001) of the percentage of matched columns (defined as percentage of matched columns of segmentation method divided by number of unstained columns in the specimen). According to the subgroup analyses, CAMS demonstrated a higher percentage of matched columns than the AHA method in the left anterior descending artery (100% vs. 77%; p < 0.001) and mid- (99% vs. 83%; p = 0.046) and apical-level territories of the left ventricle (90% vs. 52%; p = 0.011).


CONCLUSIONS
CAMS is a feasible method for identifying the corresponding myocardial territories of the coronary arteries using CCTA.


CONCLUSIONS
• CAMS is a feasible method for identifying corresponding coronary territory using CTA • CAMS is more accurate in predicting coronary territory than the AHA method • The AHA method may underestimate the ischaemic territory of LAD stenosis.
Department of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, 102, Heukseok-ro, Dongjakgu, Seoul, 06973, South Korea.
Mi Sun
MS
Chung
Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Asanbyeongwon-gil 86, Seoul, 138-736, South Korea. donghyun.yang@gmail.com.
Dong Hyun
DH
Yang
Heart Institute, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
Young-Hak
YH
Kim
Heart Institute, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
Soo-Jin
SJ
Kang
Heart Institute, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
Joonho
J
Jung
Department of Convergence Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
Namkug
N
Kim
Asan institute for Life Science, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
Seung-Ho
SH
Heo
Department of Clinical Epidemiology and Biostatistics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
Seunghee
S
Baek
Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Asanbyeongwon-gil 86, Seoul, 138-736, South Korea.
Joon Beom
JB
Seo
Department of Diagnostic Radiology, College of Medicine, Yonsei University, Seoul, South Korea.
Byoung Wook
BW
Choi
Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Asanbyeongwon-gil 86, Seoul, 138-736, South Korea.
Joon-Won
JW
Kang
Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Asanbyeongwon-gil 86, Seoul, 138-736, South Korea.
Tae-Hwan
TH
Lim
D000818:Animals; D000072226:Computed Tomography Angiography; D017023:Coronary Angiography / Q000379:methods*; D003324:Coronary Artery Disease / Q000000981:diagnostic imaging*; D003331:Coronary Vessels / Q000000981:diagnostic imaging*; D004195:Disease Models, Animal; D006321:Heart / Q000000981:diagnostic imaging*; D009206:Myocardium / Q000473:pathology*; D013552:Swine
Animal experimentation; Computed tomography; Coronary artery disease; Myocardial ischaemia; Software validation