The culprit lesion and its consequences: combined visualization of the coronary arteries and delayed myocardial enhancement in dual-source CT: a pilot study.
OBJECTIVE
To assess combined analysis of coronary arteries and delayed myocardial contrast enhancement based on co-registration of coronary CT angiography and late-phase CT and automatic segmentation.


METHODS
Co-registration and late enhancement segmentation were applied to coronary CT angiography and late-phase CT images from six pigs with acute myocardial infarction (MI) and six patients with chronic MI. MI size was quantified by manual delineation, the established 3SD method, and a new mixture model approach. Correspondence between coronary artery lesions and MI was assessed visually from fused segmentation results.


RESULTS
Co-registration was successful in all cases. There was substantial agreement in the number of segments diagnosed with MI, comparing manual delineation and the mixture model for animal (κ = 0.839) and patient studies (κ = 0.770). There were no significant differences between the two methods (P > 0.05). In patients there was a discrepancy between the segmental distribution of MI and empirical coronary artery perfusion in 10/96 segments when compared with the true coronary branching pattern.


CONCLUSIONS
The mixture model approach is well suited for automated assessment of MI size from late-phase cardiac CT. Fusion imaging eliminates the need for empirical knowledge of the anatomical relationship between the coronary artery lesion and the area of myocardial ischaemia.
Mahnken
Andreas H
AH
Department of Diagnostic Radiology, University Hospital, RWTH Aachen University, Pauwelsstrasse 30, 52074, Aachen, Germany. mahnken@rad.rwth-aachen.de
Bruners
Philipp
P
Friman
Ola
O
Hennemuth
Anja
A
D000368:Aged; D000465:Algorithms; D000818:Animals; D017023:Coronary Angiography / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D009203:Myocardial Infarction / Q000000981:diagnostic imaging*; D010363:Pattern Recognition, Automated / Q000379:methods*; D010865:Pilot Projects; D011856:Radiographic Image Enhancement / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D013552:Swine; D014057:Tomography, X-Ray Computed / Q000379:methods*