ArticleBiomedical engineering online2017
A vessel length-based method to compute coronary fractional flow reserve from optical coherence tomography images.
Article in Biomedical engineering online, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.
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10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 24 citations in OpenAlex.
- Comparison of Coronary Angiographic-Derived and Intracoronary Imaging-Based Fractional Flow Reserve in Assessing Coronary Artery Stenosis Severity: A Systematic Review and Network Meta-Analysis.Journal of evidence-based medicine · 2025Pooled it
- Diagnostic accuracy of optical flow ratio: an individual patient-data meta-analysis.EuroIntervention : journal of EuroPCR in collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology · 2023Pooled it
- Diagnostic accuracy of a novel optical coherence tomography-based fractional flow reserve algorithm for assessment of coronary stenosis significance.Cardiology journal · 2024Article
- Changing the Landscape of Secondary Prevention After Acute Coronary Syndrome: Morphology, Physiology, or Both?JACC. Asia · 2022Article
- Fractional Flow Reserve (FFR) Estimation from OCT-Based CFD Simulations: Role of Side Branches.Applied sciences (Basel, Switzerland) · 2022Article
- Diagnostic performance of deep learning and computational fluid dynamics-based instantaneous wave-free ratio derived from computed tomography angiography.BMC cardiovascular disorders · 2022Observational
- Research Progress of Machine Learning and Deep Learning in Intelligent Diagnosis of the Coronary Atherosclerotic Heart Disease.Computational and mathematical methods in medicine · 2022Review
- Fractional flow reserve for coronary stenosis assessment derived from fusion of intravascular ultrasound and X-ray angiography.Quantitative imaging in medicine and surgery · 2021Article
- A Simple Method for Automatic 3D Reconstruction of Coronary Arteries From X-Ray Angiography.Frontiers in physiology · 2021Article
- Simulation of the Perfusion of Contrast Agent Used in Cardiac Magnetic Resonance: A Step Toward Non-invasive Cardiac Perfusion Quantification.Frontiers in physiology · 2019Article
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Authors and funding
4 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundHemodynamic simulation for quantifying fractional flow reserve (FFR) is often performed in a patient-specific geometry of coronary arteries reconstructed from the images from various imaging modalities. Because optical coherence tomography (OCT) images can provide more precise vascular lumen geometry, regardless of stenotic severity, hemodynamic simulation based on OCT images may be effective. The aim of this study is to perform OCT-FFR simulations by coupling a 3D CFD model from geometrically correct OCT images with a LPM based on vessel lengths extracted from CAG data with clinical validations for the present method.
methodsTo simulate coronary hemodynamics, we developed a fast and accurate method that combined a computational fluid dynamics (CFD) model of an OCT-based region of interest (ROI) with a lumped parameter model (LPM) of the coronary microvasculature and veins. Here, the LPM was based on vessel lengths extracted from coronary X-ray angiography (CAG) images. Based on a vessel length-based approach, we describe a theoretical formulation for the total resistance of the LPM from a three-dimensional (3D) CFD model of the ROI.
resultsTo show the utility of this method, we present calculated examples of FFR from OCT images. To validate the OCT-based FFR calculation (OCT-FFR) clinically, we compared the computed OCT-FFR values for 17 vessels of 13 patients with clinically measured FFR (M-FFR) values.
conclusionA novel formulation for the total resistance of LPM is introduced to accurately simulate a 3D CFD model of the ROI. The simulated FFR values compared well with clinically measured ones, showing the accuracy of the method. Moreover, the present method is fast in terms of computational time, enabling clinicians to provide solutions handled within the hospital.
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