@article{oai:jichi-ir.repo.nii.ac.jp:00000082,
 author = {Otake, Yuko and Shimpo, Masahisa and Katsuski, Takaaki and Kario, Kazuomi and Sugimoto, Hideharu},
 journal = {自治医科大学紀要, Jichi Medical University Journal},
 month = {Mar},
 note = {Purpose: The aim of this study was to evaluate the accuracy of dual-source computed tomography (DSCT) for assessment of regional left ventricular (LV) wall motion abnormalities and global LV function, using left ventriculography (LVG) as a gold standard. 
Methods: Forty-three patients (25 men; mean age, 64.4±16.9 years) with confirmed or suspected coronary artery disease (CAD) underwent cardiac DSCT and invasive LVG; DSCT and LVG were performed within 3 months of one another. In the DSCT cine mode, the regional wall motion of each segment was assigned a score from 1-4 (normal=1, reduced=2, akinetic=3, dyskinetic/aneurysmal=4) based on the maximum intensity projection (MIP) in the right anterior and left anterior oblique views using a seven-segment model (cine-MIP). We also assessed global LV function by DSCT with a semiautomatic, three-dimensional region growing algorithm. LVG was used as a gold standard to evaluate regional wall motion and global LV function. Our institutional review board approved this retrospective study. 
Results: DSCT cine-MIP detected regional wall motion abnormalities on a per-patient basis with a sensitivity of 90％ (17/19), specificity of 88％ (21/24) and overall agreement rate of 88％ (39/43). There was a good correlation (Cohen’s kappa=0.766) between DSCT and LVG. On a per-segment basis, the overall agreement rate was 81％ (243/301). Ejection fraction obtained by DSCT showed a good correlation with that obtained by LVG (r=0.888). 
Conclusion: DSCT can be used to accurately evaluate global LV function as well as regional wall motion abnormalities in CAD patients.},
 pages = {1--9},
 title = {Assessment of Regional Left Ventricular Wall Motion Abnormalities and Global Left Ventricular Function Obtained by Dual Source Computed Tomography in Patients with Coronary Artery Disease},
 volume = {37},
 year = {2015}
}