Literature DB >> 26646280

Reproducibility and clinical potential of myocardial mass at risk calculated by a novel software utilizing cardiac computed tomography information.

Satoru Sumitsuji1, Seiko Ide2, Patrick T Siegrist2, Youssef Salah2, Kensuke Yokoi2, Masatoki Yoshida3, Masaki Awata2, Keita Yamasaki2, Kouichi Tachibana2, Hideaki Kaneda2,4, Shinsuke Nanto5, Yasushi Sakata6.   

Abstract

To select the best revascularization strategy a correct understanding of the ischemic territory and the coronary anatomy is crucial. Stress myocardial perfusion single photon emission computed tomography (SPECT) is the gold standard to assess ischemia, however, SPECT has important limitations such as lack of coronary anatomical information or false negative results due to balanced ischemia in multi-vessel disease. Angiographic scores are based on anatomical characteristics of coronary arteries but they lack information on the extent of jeopardized myocardium. Cardiac computed tomography (CCT) has the ability to evaluate the coronary anatomy and myocardium in one sequence, which is theoretically the ideal method to assess the myocardial mass at risk (MMAR) for any target lesion located at any point in the coronary tree. In this study we analyzed MMAR of the three main coronary arteries and three major side branches; diagonal (Dx), obtuse marginal (OM), and posterior descending artery (PDA) in 42 patients with normal coronary arteries using an algorithm based on the Voronoi method. The distribution of MMAR among the three main coronary arteries was 44.3 ± 5.6 % for the left anterior descending artery, 28.2 ± 7.3 % for the left circumflex artery, and 26.8 ± 8.6 % for the right coronary artery. MMAR of the three major side branches was 11.3 ± 3.9 % for the Dx, 12.6 ± 5.2 % for the OM and 10.2 ± 3.4 % for the PDA. Intra- and inter-observer analysis showed excellent correlation (r = 0.97; p < 0.0001 and r = 0.95; p < 0.0001, respectively). In conclusion, CCT-based MMAR assessment is reliable and may offer important information for selection of the optimal revascularization procedure.

Entities:  

Keywords:  Cardiac computed tomography; Myocardial mass at risk; Voronoi method

Mesh:

Year:  2015        PMID: 26646280     DOI: 10.1007/s12928-015-0370-0

Source DB:  PubMed          Journal:  Cardiovasc Interv Ther        ISSN: 1868-4297


  2 in total

1.  Machine learning assessment of myocardial ischemia using angiography: Development and retrospective validation.

Authors:  Hyeonyong Hae; Soo-Jin Kang; Won-Jang Kim; So-Yeon Choi; June-Goo Lee; Youngoh Bae; Hyungjoo Cho; Dong Hyun Yang; Joon-Won Kang; Tae-Hwan Lim; Cheol Hyun Lee; Do-Yoon Kang; Pil Hyung Lee; Jung-Min Ahn; Duk-Woo Park; Seung-Whan Lee; Young-Hak Kim; Cheol Whan Lee; Seong-Wook Park; Seung-Jung Park
Journal:  PLoS Med       Date:  2018-11-13       Impact factor: 11.069

2.  The Functional Severity Assessment of Coronary Stenosis Using Coronary Computed Tomography Angiography-Based Myocardial Mass at Risk and Minimal Lumen Diameter.

Authors:  Kenji Sadamatsu; Kazuhiro Nagaoka; Yasuaki Koga; Kotaro Kagiyama; Kohei Muramatsu; Kiyoshi Hironaga; Hideki Tashiro; Takafumi Ueno; Yoshihiro Fukumoto
Journal:  Cardiovasc Ther       Date:  2020-01-30       Impact factor: 3.023

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.