Seiko Ide1, Satoru Sumitsuji2, Osamu Yamaguchi3, Yasushi Sakata3. 1. Department of Cardiology for International Education and Research, Osaka University Graduate School of Medicine, Suita, Osaka, Japan. 2. Department of Cardiology for International Education and Research, Osaka University Graduate School of Medicine, Suita, Osaka, Japan. Electronic address: satoru@sumi2g.sakura.ne.jp. 3. Division of Cardiology, Osaka University Graduate School of Medicine, Suita, Osaka, Japan.
Abstract
BACKGROUND: Myocardial mass at risk (MMAR) is an important predictor of adverse cardiac events in patients with ischemic heart disease. This study aims to validate the accuracy of MMAR calculated from cardiac computed tomography (CCT) data using the Voronoi-based segmentation algorithm in comparison with actual MMAR measured on ex-vivo swine hearts prepared by injecting a dye into the coronary arteries. METHODS: Fifteen extracted swine hearts had India ink injected into one of the major coronary arteries. Subsequently, all coronary arteries manually injected with methylcellulose-based iohexiol-370 were imaged by 16-row CT. The ventricles were cross-sectioned perpendicularly to the long axis of the left ventricle (LV). The stained area and the total LV area of individual slices were measured, and actual MMAR was calculated as the ratio of the LV volume with the disc-summation method. CT-based MMAR of each coronary artery was calculated automatically with the Voronoi-based segmentation algorithm. The results were compared using Pearson's correlation coefficient. RESULTS: The median value of CT-based MMAR was 50.8% for the left anterior descending artery (LAD), 36.6% for the left circumflex artery (LCX), and 23.0% for the right coronary artery (RCA). Actual MMAR was 49.8% for LAD, 32.2% for LCX, and 25.9% for RCA. CT-based MMAR was significantly related to actual MMAR (r = 0.92, p = 0.02 for LAD; r = 0.96, p = 0.009 for LCX; r = 0.96, p = 0.009 for RCA). CONCLUSION: CT-based MMAR obtained by Voronoi-based segmentation algorithm reliably estimates actual MMAR measured on ex-vivo swine hearts.
BACKGROUND: Myocardial mass at risk (MMAR) is an important predictor of adverse cardiac events in patients with ischemic heart disease. This study aims to validate the accuracy of MMAR calculated from cardiac computed tomography (CCT) data using the Voronoi-based segmentation algorithm in comparison with actual MMAR measured on ex-vivo swine hearts prepared by injecting a dye into the coronary arteries. METHODS: Fifteen extracted swine hearts had India ink injected into one of the major coronary arteries. Subsequently, all coronary arteries manually injected with methylcellulose-based iohexiol-370 were imaged by 16-row CT. The ventricles were cross-sectioned perpendicularly to the long axis of the left ventricle (LV). The stained area and the total LV area of individual slices were measured, and actual MMAR was calculated as the ratio of the LV volume with the disc-summation method. CT-based MMAR of each coronary artery was calculated automatically with the Voronoi-based segmentation algorithm. The results were compared using Pearson's correlation coefficient. RESULTS: The median value of CT-based MMAR was 50.8% for the left anterior descending artery (LAD), 36.6% for the left circumflex artery (LCX), and 23.0% for the right coronary artery (RCA). Actual MMAR was 49.8% for LAD, 32.2% for LCX, and 25.9% for RCA. CT-based MMAR was significantly related to actual MMAR (r = 0.92, p = 0.02 for LAD; r = 0.96, p = 0.009 for LCX; r = 0.96, p = 0.009 for RCA). CONCLUSION: CT-based MMAR obtained by Voronoi-based segmentation algorithm reliably estimates actual MMAR measured on ex-vivo swine hearts.
Authors: Daniëlle C J Keulards; Stephane Fournier; Marcel van 't Veer; Iginio Colaiori; Jo M Zelis; Mohamed El Farissi; Frederik M Zimmermann; Carlos Collet; Bernard De Bruyne; Nico H J Pijls Journal: Heart Date: 2020-05-29 Impact factor: 5.994
Authors: F Y van Driest; R J van der Geest; A Broersen; J Dijkstra; M El Mahdiui; J W Jukema; A J H A Scholte Journal: Int J Cardiovasc Imaging Date: 2021-06-23 Impact factor: 2.357