Literature DB >> 26892449

Better Diagnosis of Functionally Significant Intermediate Sized Narrowings Using Intravascular Ultrasound-Minimal Lumen Area and Coronary Computed Tomographic Angiography-Based Myocardial Segmentation.

Soo-Jin Kang1, Dong Hyun Yang2, Jihoon Kweon1, Young-Hak Kim3, June-Goo Lee2, Joonho Jung2, Namkug Kim2, Gary S Mintz4, Joon-Won Kang2, Tae-Hwan Lim2, Seong-Wook Park1.   

Abstract

Lesion morphology poorly predicts functional significance of intermediate coronary artery stenosis. The aim of this study was to determine whether a coronary artery-based myocardial segmentation method that quantifies subtended myocardium can improve the diagnostic accuracy of intravascular ultrasound (IVUS)-derived parameters for detecting ischemia-producing lesions. Coronary computed tomography angiography, IVUS, and fractional flow reserve (FFR) data were analyzed in 101 non-left main lesions (20% to 80% angiographic stenosis). Using the coronary artery-based myocardial segmentation method, total left ventricular myocardial volume (Vtotal), myocardial volume subtended by the stenotic coronary segment (Vsub), and Vratio (the ratio of the Vsub to the Vtotal) were assessed. Both Vsub >30.7 cm(3) and Vratio >25.4% were determinants of FFR ≤0.75 (area under the curve = 0.696 and 0.744). Overall, an IVUS-measured minimum lumen area (IVUS-MLA) ≤2.83 mm(2) predicted FFR ≤0.75 with a sensitivity 88% and specificity 73%. Among lesions with IVUS-MLA ≤2.83 mm(2) and FFR >0.75, 89% showed Vsub <30.7 cm(3). In 50 lesions with Vsub >30.7 cm(3), an IVUS-MLA ≤2.85 mm(2) predicted FFR ≤0.75 with sensitivity 85%, specificity 92%, positive predictive value 92%, and negative predictive value 85%. Conversely, in 51 lesions with a Vsub ≤30.7 cm(3), IVUS-MLA ≤2.67 mm(2) showed sensitivity 100%, specificity 69%, positive predictive value 38%, and negative predictive value 100% for predicting FFR ≤0.75. Body surface area, reference lumen diameter, and vessel area had modest correlations with Vsub. In those lesion subsets, IVUS-MLA ≈2.8 mm(2) accurately predicted an FFR ≤0.75, whereas the clinical relevance of assessing and treating lesions with a smaller myocardial territory may be limited (ClinicalTrials.gov number NCT1696006).
Copyright © 2016 Elsevier Inc. All rights reserved.

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Year:  2016        PMID: 26892449     DOI: 10.1016/j.amjcard.2016.01.022

Source DB:  PubMed          Journal:  Am J Cardiol        ISSN: 0002-9149            Impact factor:   2.778


  8 in total

1.  Association of quantitative flow ratio-derived microcirculatory indices with anatomical-functional discordance in intermediate coronary lesions.

Authors:  Liang Geng; Yuan Yuan; Peizhao Du; Liming Gao; Yunkai Wang; Jiming Li; Wei Guo; Ying Huang; Qi Zhang
Journal:  Int J Cardiovasc Imaging       Date:  2021-05-31       Impact factor: 2.357

Review 2.  A systematic review of imaging anatomy in predicting functional significance of coronary stenoses determined by fractional flow reserve.

Authors:  Miao Chu; Neng Dai; Junqing Yang; Jelmer Westra; Shengxian Tu
Journal:  Int J Cardiovasc Imaging       Date:  2017-03-06       Impact factor: 2.357

3.  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

4.  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

5.  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

6.  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

7.  Meta-analysis and systematic review of intravascular ultrasound versus angiography-guided drug eluting stent implantation in left main coronary disease in 4592 patients.

Authors:  Yue Wang; Gary S Mintz; Zhichun Gu; Yue Qi; Yue Wang; Mengru Liu; Xiaofan Wu
Journal:  BMC Cardiovasc Disord       Date:  2018-06-14       Impact factor: 2.298

8.  Pre-percutaneous Coronary Intervention Pericoronary Adipose Tissue Attenuation Evaluated by Computed Tomography Predicts Global Coronary Flow Reserve After Urgent Revascularization in Patients With Non-ST-Segment-Elevation Acute Coronary Syndrome.

Authors:  Yoshihisa Kanaji; Hidenori Hirano; Tomoyo Sugiyama; Masahiro Hoshino; Tomoki Horie; Toru Misawa; Kai Nogami; Hiroki Ueno; Masahiro Hada; Masao Yamaguchi; Yohei Sumino; Rikuta Hamaya; Eisuke Usui; Taishi Yonetsu; Tetsuo Sasano; Tsunekazu Kakuta
Journal:  J Am Heart Assoc       Date:  2020-08-28       Impact factor: 5.501

  8 in total

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