Coronary flow disturbance assessed by vorticity as a cause of functionally significant stenosis

Tomizawa, Nobuo; Nozaki, Yui; Fujimoto, Shinichiro; Takahashi, Daigo; Kudo, Ayako; Kamo, Yuki; Aoshima, Chihiro; Kawaguchi, Yuko; Takamura, Kazuhisa; Hiki, Makoto; Dohi, Tomotaka; Okazaki, Shinya; Kumamaru, Kanako K.; Minamino, Tohru; Aoki, Shigeki

doi:10.1007/s00330-022-08974-2

Cited by 4 publications

(2 citation statements)

References 26 publications

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“…Tomizawa et al 37 demonstrated that vorticity was elevated for significant lesions as compared with nonsignificant lesions, which is in alignment with our results. Chu et al 12 demonstrated that vorticity was strongly correlated with FFR, more so than when correlating FFR with flow velocity, lesion length, and percent stenosis.…”

Section: Discussionsupporting

confidence: 93%

Diagnostic Performance of Coronary Angiography Derived Computational Fractional Flow Reserve

Vardhan,

Tanade,

Chen

et al. 2024

JAHA

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Background Computational fluid dynamics can compute fractional flow reserve (FFR) accurately. However, existing models are limited by either the intravascular hemodynamic phenomarkers that can be captured or the fidelity of geometries that can be modeled. Methods and Results This study aimed to validate a new coronary angiography‐based FFR framework, FFR HARVEY , and examine intravascular hemodynamics to identify new biomarkers that could augment FFR in discerning unrevascularized patients requiring intervention. A 2‐center cohort was used to examine diagnostic performance of FFR HARVEY compared with reference wire‐based FFR (FFR INVASIVE ). Additional biomarkers, longitudinal vorticity, velocity, and wall shear stress, were evaluated for their ability to augment FFR and indicate major adverse cardiac events. A total of 160 patients with 166 lesions were investigated. FFR HARVEY was compared with FFR INVASIVE by investigators blinded to the invasive FFR results with a per‐stenosis area under the curve of 0.91, positive predictive value of 90.2%, negative predictive value of 89.6%, sensitivity of 79.3%, and specificity of 95.4%. The percentage ofdiscrepancy for continuous values of FFR was 6.63%. We identified a hemodynamic phenomarker, longitudinal vorticity, as a metric indicative of major adverse cardiac events in unrevascularized gray‐zone cases. Conclusions FFR HARVEY had high performance (area under the curve: 0.91, positive predictive value: 90.2%, negative predictive value: 89.6%) compared with FFR INVASIVE . The proposed framework provides a robust and accurate way to compute a complete set of intravascular phenomarkers, in which longitudinal vorticity was specifically shown to differentiate vessels predisposed to major adverse cardiac events.

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Section: Discussionsupporting

confidence: 93%

Diagnostic Performance of Coronary Angiography Derived Computational Fractional Flow Reserve

Vardhan,

Tanade,

Chen

et al. 2024

JAHA

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“…The presence of coronary stenosis causes disturbed flow, resulting in increased vorticity [ 27 ]. In this state, kinetic energy is partially converted to acoustic and thermal energy due to friction, viscosity, and turbulence [ 8 , 9 ].…”

Section: Discussionmentioning

confidence: 99%

Energy loss is related to CT fractional flow reserve progression in type 2 diabetes mellitus patients

Tomizawa,

Fujimoto,

Takahashi

et al. 2023

American Heart Journal Plus: Cardiology Research and Practice

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Establishing the longitudinal hemodynamic mapping framework for wearable-driven coronary digital twins

Tanade,

Khan,

Rakestraw

et al. 2024

npj Digit. Med.

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Coronary flow disturbance assessed by vorticity as a cause of functionally significant stenosis

Cited by 4 publications

References 26 publications

Diagnostic Performance of Coronary Angiography Derived Computational Fractional Flow Reserve

Diagnostic Performance of Coronary Angiography Derived Computational Fractional Flow Reserve

Energy loss is related to CT fractional flow reserve progression in type 2 diabetes mellitus patients

Establishing the longitudinal hemodynamic mapping framework for wearable-driven coronary digital twins

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