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Tamarappoo, B.K., Gutstein, A., Cheng, V.Y., Nakazato, R., Gransar, H., Dey, D., Thomson, L.E., Hayes, S.W., Friedman, J.D., Germano, G., Slomka, P.J. and Berman, D.S. (2010) Assessment of the Relationship between Stenosis Severity and Distribution of Coronary Artery Stenosis on Multislice Computed Tomographic Angiography and Myocardial Ischemia Detected by Single Photon Emission Computed Tomography. Journal of Nuclear Cardiology, 17, 791-802.
https://doi.org/10.1007/s12350-010-9230-6

has been cited by the following article:

• TITLE: Myocardial Segmentation of Area at Risk Based on Coronary Computed Tomography Angiography and Voronoi Diagram in Comparison with Magnetic Resonance Perfusion Imaging

  AUTHORS: Naoki Fukuyama, Teruhito Kido, Akira Kurata, Yuki Tanabe, Tomoyuki Kido, Takahiro Yokoi, Ryo Ogawa, Hikaru Nishiyama, Teruyoshi Uetani, Teruhito Mochizuki

  KEYWORDS: Computed Tomography, Ischemia, Myocardial Area at Risk

  JOURNAL NAME: Open Journal of Radiology, Vol.7 No.1, March 1, 2017

  ABSTRACT: Purpose: To assess the clinical feasibility of automated segmentation of the myocardial area at risk (MAAR) using coronary computed tomography angiography (CT-MAAR), as compared to stress magnetic resonance myocardial perfusion imaging (MR-MPI). Materials and Methods: Thirty patients who underwent coronary computed tomography angiography (CTA) and stress MR-MPI were retrospectively evaluated. The myocardial territory of the left ventricle (LV) distal to coronary artery stenosis (≥50% or ≥70% stenosis on coronary CTA) was three-dimensionally quantified using a Voronoi diagram. The ratio of all stenosis-related territories to the LV volume was defined as CT-MAAR (%-LV volume). The proportion of segments with perfusion defects in stress MR-MPI to the total of 16 segments (range: 0% - 100%; with a 6.3%-interval scale) was defined as the reference. Correlation was assessed using Spearman’s test. The capability of CT-MAAR to predict the ischemic burden was assessed. Results: Stress MR-MPI depicted a median ischemic burden of 25.2% (range: 18.9% - 44.1%) in 30 patients without myocardial infarction. When CTA stenosis criteria of ≥50% (n = 30) and ≥70% (n = 27) were applied to estimate CT-MAAR, the median CT-MAAR values were 48.2% (31.6% - 64.3%) and 32.5% (23.7% - 51.9%), respectively. The correlations between the CT-MAAR values and the MR-based ischemic burden were significant (0.73 and 0.97 for ≥50% and ≥70% stenosis, respectively). CT-MAAR predicted the MR-based ischemic burden within ±1 segment of %-LV (6.3%) in 40% (12/30) of patients with ≥50% stenosis, and in 81.5% (22/27) of patients with ≥70% stenosis. Conclusions: Comprehensive assessment of resting coronary CTA combined with Voronoi diagram-based myocardial segmentation may help predict the myocardial ischemic burden in patients with severe coronary CTA stenosis.