Impact of spatial characteristics in the left stenotic coronary artery on the hemodynamics and visualization of 3D replica models

Sci Rep. 2017 Nov 13;7(1):15452. doi: 10.1038/s41598-017-15620-1.


Cardiovascular disease has been the major cause of death worldwide. Although the initiation and progression mechanism of the atherosclerosis are similar, the stenotic characteristics and the corresponding medical decisions are different between individuals. In the present study, we performed anatomic and hemodynamic analysis on 8 left coronary arterial trees with 10 identified stenoses. A novel boundary condition method had been implemented for fast computational fluid dynamics simulations and patient-specific three-dimensional printed models had been built for visualizations. Our results suggested that the multiple spatial characteristics (curvature of the culprit vessel multiplied by an angle of the culprit's vessel to the upstream parent branch) could be an index of hemodynamics significance (r = -0.673, P-value = 0.033). and reduction of the maximum velocity from stenosis to downstream was found correlated to the FFRCT (r = 0.480, p = 0.160). In addition, 3D printed models could provide accurate replicas of the patient-specific left coronary arterial trees compare to virtual 3D models (r = 0.987, P-value < 0.001). Therefore, the visualization of the 3D printed models could help understand the spatial distribution of the stenoses and the hand-held experience could potentially benefit the educating and preparing of medical strategies.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Computed Tomography Angiography
  • Coronary Angiography
  • Coronary Stenosis / diagnostic imaging
  • Coronary Stenosis / physiopathology*
  • Coronary Stenosis / therapy
  • Coronary Vessels / diagnostic imaging
  • Coronary Vessels / physiopathology*
  • Hemorheology / physiology*
  • Humans
  • Middle Aged
  • Models, Anatomic
  • Models, Cardiovascular*
  • Patient Care Planning
  • Printing, Three-Dimensional*
  • Retrospective Studies