Stratification of a population of intracranial aneurysms using blood flow metrics

Rohini Retarekar, Manasi Ramachandran, Benjamin Berkowitz, Robert E. Harbaugh, David Hasan, Robert H. Rosenwasser, Christopher S. Ogilvy, Madhavan L. Raghavan

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Indices of the intra-aneurysm hemodynamic environment have been proposed as potentially indicative of their longitudinal outcome. To be useful, the indices need to be used to stratify large study populations and tested against known outcomes. The first objective was to compile the diverse hemodynamic indices reported in the literature. Furthermore, as morphology is often the only patient-specific information available in large population studies, the second objective was to assess how the ranking of aneurysms in a population is affected by the use of steady flow simulation as an approximation to pulsatile flow simulation, even though the former is clearly non-physiological. Sixteen indices of aneurysmal hemodynamics reported in the literature were compiled and refined where needed. It was noted that, in the literature, these global indices of flow were always time-averaged over the cardiac cycle. Steady and pulsatile flow simulations were performed on a population of 198 patient-specific and 30 idealised aneurysm models. All proposed hemodynamic indices were estimated and compared between the two simulations. It was found that steady and pulsatile flow simulations had a strong linear dependence (r ≥ 0.99 for 14 indices; r ≥ 0.97 for 2 others) and rank the aneurysms in an almost identical fashion (ρ ≥ 0.99 for 14 indices; ρ ≥ 0.96 for other 2). When geometry is the only measured piece of information available, stratification of aneurysms based on hemodynamic indices reduces to being a physically grounded substitute for stratification of aneurysms based on morphology. Under such circumstances, steady flow simulations may be just as effective as pulsatile flow simulation for estimating most key indices currently reported in the literature.

Original languageEnglish (US)
Pages (from-to)1072-1082
Number of pages11
JournalComputer Methods in Biomechanics and Biomedical Engineering
Volume18
Issue number10
DOIs
StatePublished - Jul 27 2015

All Science Journal Classification (ASJC) codes

  • Bioengineering
  • Biomedical Engineering
  • Human-Computer Interaction
  • Computer Science Applications

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