scholarly journals TCT-29 Mechanism of Low Fractional Flow Reserve in Lesions without angiographic significant stenosis: Role of hidden Plaque Burden

2017 ◽  
Vol 70 (18) ◽  
pp. B13
Author(s):  
Jonghanne Park ◽  
Joo Myung Lee ◽  
Eun-Seok Shin ◽  
Chang-Wook Nam ◽  
Joon-Hyung Doh ◽  
...  
Circulation ◽  
2015 ◽  
Vol 132 (suppl_3) ◽  
Author(s):  
Shunsuke Imai ◽  
Takeshi Kondoh ◽  
Yoshiaki Kawase ◽  
Hitoshi Matsuo

Introduction: Coronary angiographic anatomical stenosis has not been well correlated with physiological fractional flow reserve (FFR), however, the mechanism of the discordance remains poorly understood. We focused on the patients who had no anatomical significant stenosis by coronary angiogram (CAG) but physiological significant stenosis by FFR (reverse mismatch) in the proximal or mid left anterior descending artery (LAD). We explored what coronary CT angiography (CCTA) findings of the target lesion of the LAD predict abnormal FFR. Methods: ECG-gated CCTA was performed using SOMATOM Definition AS+ (128 slice Siemens) and CAG underwent within 4 weeks. FFR was measured using a pressure guide wire (verrata, Volcano) during ATP infusion. Forty consecutive reverse mismatch (with no anatomical stenosis and FFR≦0.8) pts and 40 no mismatch (with no anatomical stenosis and FFR>0.8) pts were selected. Results: There were no significant differences in mean age (72±10y vs 74±8y), gender (M/F 21/19 vs 28/12), coronary risk factors (DM (9 vs 17), HT(32 vs 30), dyslipidemia (23 vs 18), Smoking (5 vs 4)), angle of LAD and LCX (70±21vs71±20 deg.), proximal reference lumen area (0.14±0.14 vs 0.14±0.11 mm2) and vessel area (0.15±0.04 vs 0.15±0.06mm2), distal reference lumen area (0.11±0.12 vs 0.10±0.04mm2) and vessel area (0.14±0.13 vs 0.12±0.04mm2), grade of plaque calcification, and presence of low density plaque (8 vs 7 pts) between no mismatch and reverse mismatch groups. However, vessel area (0.21±0.07mm2, P=0.0004) and positive remodeling area index (1.40±0.26, P<0.0001) at the minimum lumen area (MLA) in reverse mismatch group were higher than those (0.16±0.05mm2, 1.01±0.18) in no mismatch groups, respectively. AUC of remodeling area index was 0.924 for diagnosis of reverse mismatch on ROC analysis. Sensitivity was 82.5%, specificity was 84.6% when the remodeling area index was 1.13. Conclusions: Even if anatomical significant stenosis is not observed, FFR was depressed in patients with large vessel area and positive remodeling area index derived from CCTA at MLA. Large plaque at MLA may be one of the mechanisms of reverse mismatch.


2018 ◽  
Vol 71 (5) ◽  
pp. 499-509 ◽  
Author(s):  
Roel S. Driessen ◽  
Wijnand J. Stuijfzand ◽  
Pieter G. Raijmakers ◽  
Ibrahim Danad ◽  
James K. Min ◽  
...  

2020 ◽  
Vol 15 ◽  
Author(s):  
Thomas D Heseltine ◽  
Scott W Murray ◽  
Balazs Ruzsics ◽  
Michael Fisher

Recent rapid technological advancements in cardiac CT have improved image quality and reduced radiation exposure to patients. Furthermore, key insights from large cohort trials have helped delineate cardiovascular disease risk as a function of overall coronary plaque burden and the morphological appearance of individual plaques. The advent of CT-derived fractional flow reserve promises to establish an anatomical and functional test within one modality. Recent data examining the short-term impact of CT-derived fractional flow reserve on downstream care and clinical outcomes have been published. In addition, machine learning is a concept that is being increasingly applied to diagnostic medicine. Over the coming decade, machine learning will begin to be integrated into cardiac CT, and will potentially make a tangible difference to how this modality evolves. The authors have performed an extensive literature review and comprehensive analysis of the recent advances in cardiac CT. They review how recent advances currently impact on clinical care and potential future directions for this imaging modality.


2018 ◽  
Vol 12 (5) ◽  
pp. 379-384 ◽  
Author(s):  
Mhairi K. Doris ◽  
Yuka Otaki ◽  
Yoav Arnson ◽  
Balaji Tamarappoo ◽  
Markus Goeller ◽  
...  

2015 ◽  
Vol 87 (9) ◽  
pp. 106 ◽  
Author(s):  
F. Yu. Kopylov ◽  
A. A. Bykova ◽  
Yu. V. Vasilevsky ◽  
S. S. Simakov

2013 ◽  
Vol 34 (suppl 1) ◽  
pp. P3972-P3972
Author(s):  
Y. H. Lee ◽  
K. W. Seo ◽  
J. S. Park ◽  
H. M. Yang ◽  
B. J. Choi ◽  
...  

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