Literature DB >> 27423225

Physiological Severity of Coronary Artery Stenosis Depends on the Amount of Myocardial Mass Subtended by the Coronary Artery.

Hyung Yoon Kim1, Hong-Seok Lim2, Joon-Hyung Doh3, Chang-Wook Nam4, Eun-Seok Shin5, Bon-Kwon Koo6, Myeong-Ho Yoon2, Seung-Jea Tahk2, Doo Kyoung Kang7, Young Bin Song1, Joo-Yong Hahn1, Seung Hyuk Choi1, Hyeon-Cheol Gwon1, Sang-Hoon Lee1, Eun-Kyoung Kim1, Sung Mok Kim8, Yeonhyeon Choe8, Jin-Ho Choi9.   

Abstract

OBJECTIVES: This study investigated the role of fractional myocardial mass (FMM), a vessel-specific myocardial mass, in the evaluation of physiological severity of stenosis. Using computed tomography angiography, the study investigated fractional myocardial mass, a concept of myocardial mass subtended by specific vessel, which could reduce anatomical-physiological mismatch.
BACKGROUND: Discordance between anatomical stenosis and physiological severity is common but remains poorly understood.
METHODS: This multicenter study enrolled 463 patients with 724 lesions, who underwent coronary computed tomography angiography (CCTA) and invasive coronary angiography with fractional flow reserve (FFR) measurement. FMM was assessed by allometric scaling analysis of arterial tree length and myocardial mass from CCTA.
RESULTS: FFR <0.80, a criteria for vessel-specific physiological stenosis, was found in 281 vessels (39%). FMM decreased consistently according to the vessel downstream (p < 0.001, all). The frequency of FFR <0.80 increased in proportion to FMM and inverse proportion to angiographic minimal luminal diameter (MLD) (p < 0.001). In per-vessel analysis, FMM per MLD (FMM/MLD) showed good correlation with FFR (r = 0.61) and was superior to diameter stenosis (DS) for FFR <0.80 by receiver operating characteristic and reclassification analysis (C-statistics = 0.84 versus 0.74, net reclassification improvement [NRI] = 0.63, integrated discrimination improvement [IDI] = 0.18; p < 0.001, all). The optimal cutoff of FMM/MLD was 29 g/mm, with sensitivity = 75%, specificity = 77%, positive predictive value = 68%, negative predictive value = 83%, and accuracy = 77%. Addition of FMM/MLD to DS could further discriminate vessels with FFR <0.80 (C-statistic = 0.86 vs. 0.84, NRI = 0.34, IDI = 0.03; p < 0.005, all). In per-range classification analysis, agreement between FFR and FMM/MLD maintained >80% when the severity of disease was away from cutoff.
CONCLUSIONS: FMM/MLD could find physiological severity of coronary artery with higher accuracy than anatomical stenosis. FMM may explain the anatomical-physiological discordance.
Copyright © 2016 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  anatomical-physiological discordance; coronary artery physiology; fractional myocardial mass; fractional flow reserve

Mesh:

Year:  2016        PMID: 27423225     DOI: 10.1016/j.jcin.2016.04.008

Source DB:  PubMed          Journal:  JACC Cardiovasc Interv        ISSN: 1936-8798            Impact factor:   11.195


  19 in total

1.  Influence of scan technique on intracoronary transluminal attenuation gradient in coronary CT angiography using 128-slice dual source CT: multi-beat versus one-beat scan.

Authors:  Hae Jin Kim; Sung Mok Kim; Jin-Ho Choi; Yeon Hyeon Choe
Journal:  Int J Cardiovasc Imaging       Date:  2017-02-01       Impact factor: 2.357

Review 2.  Complete versus incomplete coronary revascularization: definitions, assessment and outcomes.

Authors:  Prakriti Gaba; Bernard J Gersh; Ziad A Ali; Jeffrey W Moses; Gregg W Stone
Journal:  Nat Rev Cardiol       Date:  2020-10-16       Impact factor: 32.419

3.  Diagnostic performance of machine-learning-based computed fractional flow reserve (FFR) derived from coronary computed tomography angiography for the assessment of myocardial ischemia verified by invasive FFR.

Authors:  Xiuhua Hu; Minglei Yang; Lu Han; Yujiao Du
Journal:  Int J Cardiovasc Imaging       Date:  2018-07-30       Impact factor: 2.357

4.  Myocardial segmentation based on coronary anatomy using coronary computed tomography angiography: Development and validation in a pig model.

Authors:  Mi Sun Chung; Dong Hyun Yang; Young-Hak Kim; Soo-Jin Kang; Joonho Jung; Namkug Kim; Seung-Ho Heo; Seunghee Baek; Joon Beom Seo; Byoung Wook Choi; Joon-Won Kang; Tae-Hwan Lim
Journal:  Eur Radiol       Date:  2017-03-24       Impact factor: 5.315

5.  Comparison of fractional flow reserve and angiographic characteristics after balloon angioplasty in de novo coronary lesions.

Authors:  Ju-Hyun Chung; Kyung Eun Lee; Ae-Young Her; Joo Myung Lee; Joon-Hyung Doh; Chang-Wook Nam; Bon-Kwon Koo; Eun-Seok Shin
Journal:  Int J Cardiovasc Imaging       Date:  2019-06-18       Impact factor: 2.357

6.  Application of the DILEMMA score to improve lesion selection for invasive physiological assessment.

Authors:  Michael Michail; Hakim-Moulay Dehbi; Nitesh Nerlekar; Justin E Davies; Andrew S P Sharp; Suneel Talwar; James D Cameron; Adam J Brown; Dennis T Wong; Anthony Mathur; Alun D Hughes; Om Narayan
Journal:  Catheter Cardiovasc Interv       Date:  2019-01-02       Impact factor: 2.692

Review 7.  Ischemia-based Coronary Revascularization: Beyond Anatomy and Fractional Flow Reserve.

Authors:  Hong Seok Lim; Kyoung Woo Seo; Myeong Ho Yoon; Hyoung Mo Yang; Seung Jea Tahk
Journal:  Korean Circ J       Date:  2017-11-06       Impact factor: 3.243

8.  Allometric scaling patterns among the human coronary artery tree, myocardial mass, and coronary artery flow.

Authors:  Jin-Ho Choi; Eunsoo Kim; Hyung Yoon Kim; Seung-Hwa Lee; Sung Mok Kim
Journal:  Physiol Rep       Date:  2020-07

9.  Influence of Sex on Relationship Between Total Anatomical and Physiologic Disease Burdens and Their Prognostic Implications in Patients With Coronary Artery Disease.

Authors:  Chee Hae Kim; Bon-Kwon Koo; Joo Myung Lee; Eun-Seok Shin; Jonghanne Park; Ki Hong Choi; Doyeon Hwang; Tae-Min Rhee; Jinlong Zhang; You-Jung Choi; Seo-Young Lee; Jin-Ho Choi; Joon-Hyung Doh; Chang-Wook Nam; Jianan Wang; Shaoliang Chen; Shoichi Kuramitsu; Nobuhiro Tanaka; Hitoshi Matsuo; Takashi Akasaka
Journal:  J Am Heart Assoc       Date:  2019-03-05       Impact factor: 5.501

10.  Non-invasive coronary physiology based on computational analysis of intracoronary transluminal attenuation gradient.

Authors:  Yong Gyun Bae; Seung Tae Hwang; Huan Han; Sung Mok Kim; Hyung-Yoon Kim; Il Park; Joo Myung Lee; Young-June Moon; Jin-Ho Choi
Journal:  Sci Rep       Date:  2018-03-16       Impact factor: 4.379

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