{
  "abstract": "Rationale Ischemic heart disease is the leading cause of death worldwide, causing a death every four minutes in the UK resulting in a significant annual financial burden. Its main cause is coronary artery disease which is diagnosed and assessed through imaging. In tandem, traditional 2D imaging modalities are being used to reconstruct 3D arterial models used to simulate coronary hemodynamics: invasive x-ray coronary angiography (CA) captures 2D arterial anatomical projections, whereas optical coherence tomography (OCT) provides high-resolution views of the cross-sectional luminal surface and plaque composition.Aim To investigate the clinical potential of integrating CA and OCT, in silico, to enable high-resolution coronary hemodynamic simulation, that models side branches to produce parameters like those based on invasive measurements, which no single system currently performs in clinically tractable time periods.Methodology 20 coronary vessels, from 11 different patients, were segmented from CA and OCT images to extract the vessel centerlines and lumen contours, respectively. The vessels that make up a tree, that are from the same patient, were joined together to create branching models. The centerlines of the main vessel and side branch are merged to create a branching 3D centerline model through bifurcation point identification. OCT lumens are stacked on a straight-line, assuming the centroid for each lumen coincides with its corresponding CA-derived centerline point and are subject to optimization to determine the optimal rotational orientation of each. This involves rotating every successive lumen with respect to its prior to maximize the overlapping area between them. The lumens are then positioned on the torsion-compensated 3D representation of the centerlines. In silico CFD simulations were performed on the reconstructions and the virtual fractional flow reserve (FFR) was computed to be compared with that from CA-only based reconstructions and the clinically measured FFR.Findings and Conclusions Using only primary CA data, it is possible to produce branching 3D models of coronaries. However, such models will lack luminal detail, which is essential when simulating hemodynamic parameters. OCT data provides that level of detail, allowing measures of lumen ellipticity to be used to identify areas of disease/bifurcations. In the future, ‘geometrical’ validation of the 3D reconstructions can be done by comparing 3D reconstructions of physical phantoms representing the coronaries.",
  "authors": [
    {
      "affiliations": [
        "Department of Infection, Immunity and Cardiovascular Disease, The University of Sheffield",
        "INSIGNEO Institute for In Silico Medicine"
      ],
      "name": "Nada Ghorab"
    },
    {
      "affiliations": [
        "Department of Infection, Immunity and Cardiovascular Disease, The University of Sheffield",
        "INSIGNEO Institute for In Silico Medicine"
      ],
      "name": "Krzysztof Czechowicz"
    },
    {
      "affiliations": [
        "Department of Computational Science, University of Amsterdam"
      ],
      "name": "Giulia Pederzani"
    },
    {
      "affiliations": [
        "Department of Infection, Immunity and Cardiovascular Disease, The University of Sheffield",
        "INSIGNEO Institute for In Silico Medicine",
        "Department of Cardiology, Sheffield Teaching Hospitals NHS Foundation Trust"
      ],
      "name": "Dan Taylor"
    },
    {
      "affiliations": [
        "Department of Infection, Immunity and Cardiovascular Disease, The University of Sheffield",
        "INSIGNEO Institute for In Silico Medicine"
      ],
      "name": "Ian Halliday"
    },
    {
      "affiliations": [
        "Department of Infection, Immunity and Cardiovascular Disease, The University of Sheffield",
        "INSIGNEO Institute for In Silico Medicine"
      ],
      "name": "Rod Hose"
    },
    {
      "affiliations": [
        "Department of Infection, Immunity and Cardiovascular Disease, The University of Sheffield",
        "INSIGNEO Institute for In Silico Medicine",
        "Department of Cardiology, Sheffield Teaching Hospitals NHS Foundation Trust"
      ],
      "name": "Paul Morris"
    }
  ],
  "title": "2-014 Using optical coherence tomography and angiography to model coronary branches",
  "uid": "9d17565e-2630-5d66-831e-fb9dc6256663"
}