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  1. Sakai K, Storozhenko T, Mizukami T, Ohashi H, Bouisset F, Tajima A, et al.
    Catheter Cardiovasc Interv, 2024 May;103(6):885-896.
    PMID: 38566527 DOI: 10.1002/ccd.31020
    BACKGROUND: Two invasive methods are available to estimate microvascular resistance: bolus and continuous thermodilution. Comparative studies have revealed a lack of concordance between measurements of microvascular resistance obtained through these techniques.

    AIMS: This study aimed to examine the influence of vessel volume on bolus thermodilution measurements.

    METHODS: We prospectively included patients with angina with non-obstructive coronary arteries (ANOCA) undergoing bolus and continuous thermodilution assessments. All patients underwent coronary CT angiography to extract vessel volume. Coronary microvascular dysfunction was defined as coronary flow reserve (CFR) 

  2. Munhoz D, Collet C, Mizukami T, Yong A, Leone AM, Eftekhari A, et al.
    Am Heart J, 2023 Nov;265:170-179.
    PMID: 37611857 DOI: 10.1016/j.ahj.2023.07.016
    INTRODUCTION: Diffuse disease has been identified as one of the main reasons leading to low post-PCI fractional flow reserve (FFR) and residual angina after PCI. Coronary pressure pullbacks allow for the evaluation of hemodynamic coronary artery disease (CAD) patterns. The pullback pressure gradient (PPG) is a novel metric that quantifies the distribution and magnitude of pressure losses along the coronary artery in a focal-to-diffuse continuum.

    AIM: The primary objective is to determine the predictive capacity of the PPG for post-PCI FFR.

    METHODS: This prospective, large-scale, controlled, investigator-initiated, multicenter study is enrolling patients with at least 1 lesion in a major epicardial vessel with a distal FFR ≤ 0.80 intended to be treated by PCI. The study will include 982 subjects. A standardized physiological assessment will be performed pre-PCI, including the online calculation of PPG from FFR pullbacks performed manually. PPG quantifies the CAD pattern by combining several parameters from the FFR pullback curve. Post-PCI physiology will be recorded using a standardized protocol with FFR pullbacks. We hypothesize that PPG will predict optimal PCI results (post-PCI FFR ≥ 0.88) with an area under the ROC curve (AUC) ≥ 0.80. Secondary objectives include patient-reported and clinical outcomes in patients with focal vs. diffuse CAD defined by the PPG. Clinical follow-up will be collected for up to 36 months, and an independent clinical event committee will adjudicate events.

    RESULTS: Recruitment is ongoing and is expected to be completed in the second half of 2023.

    CONCLUSION: This international, large-scale, prospective study with pre-specified powered hypotheses will determine the ability of the preprocedural PPG index to predict optimal revascularization assessed by post-PCI FFR. In addition, it will evaluate the impact of PPG on treatment decisions and the predictive performance of PPG for angina relief and clinical outcomes.

  3. Collet C, Munhoz D, Mizukami T, Sonck J, Matsuo H, Shinke T, et al.
    Circulation, 2024 Aug 20;150(8):586-597.
    PMID: 38742491 DOI: 10.1161/CIRCULATIONAHA.124.069450
    BACKGROUND: Diffuse coronary artery disease affects the safety and efficacy of percutaneous coronary intervention (PCI). Pathophysiologic coronary artery disease patterns can be quantified using fractional flow reserve (FFR) pullbacks incorporating the pullback pressure gradient (PPG) calculation. This study aimed to establish the capacity of PPG to predict optimal revascularization and procedural outcomes.

    METHODS: This prospective, investigator-initiated, single-arm, multicenter study enrolled patients with at least one epicardial lesion with an FFR ≤0.80 scheduled for PCI. Manual FFR pullbacks were used to calculate PPG. The primary outcome of optimal revascularization was defined as an FFR ≥0.88 after PCI.

    RESULTS: A total of 993 patients with 1044 vessels were included. The mean FFR was 0.68±0.12, PPG 0.62±0.17, and the post-PCI FFR was 0.87±0.07. PPG was significantly correlated with the change in FFR after PCI (r=0.65 [95% CI, 0.61-0.69]; P<0.001) and demonstrated excellent predictive capacity for optimal revascularization (area under the receiver operating characteristic curve, 0.82 [95% CI, 0.79-0.84]; P<0.001). FFR alone did not predict revascularization outcomes (area under the receiver operating characteristic curve, 0.54 [95% CI, 0.50-0.57]). PPG influenced treatment decisions in 14% of patients, redirecting them from PCI to alternative treatment modalities. Periprocedural myocardial infarction occurred more frequently in patients with low PPG (<0.62) compared with those with focal disease (odds ratio, 1.71 [95% CI, 1.00-2.97]).

    CONCLUSIONS: Pathophysiologic coronary artery disease patterns distinctly affect the safety and effectiveness of PCI. PPG showed an excellent predictive capacity for optimal revascularization and demonstrated added value compared with an FFR measurement.

    REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT04789317.

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