Scientific Reports (Jan 2023)

Reproducibility of the computational fluid dynamic analysis of a cerebral aneurysm monitored over a decade

  • Phani Kumari Paritala,
  • Haveena Anbananthan,
  • Jacob Hautaniemi,
  • Macauley Smith,
  • Antony George,
  • Mark Allenby,
  • Jessica Benitez Mendieta,
  • Jiaqiu Wang,
  • Liam Maclachlan,
  • EeShern Liang,
  • Marita Prior,
  • Prasad K. D. V. Yarlagadda,
  • Craig Winter,
  • Zhiyong Li

DOI
https://doi.org/10.1038/s41598-022-27354-w
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 12

Abstract

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Abstract Computational fluid dynamics (CFD) simulations are increasingly utilised to evaluate intracranial aneurysm (IA) haemodynamics to aid in the prediction of morphological changes and rupture risk. However, these models vary and differences in published results warrant the investigation of IA-CFD reproducibility. This study aims to explore sources of intra-team variability and determine its impact on the aneurysm morphology and CFD parameters. A team of four operators were given six sets of magnetic resonance angiography data spanning a decade from one patient with a middle cerebral aneurysm. All operators were given the same protocol and software for model reconstruction and numerical analysis. The morphology and haemodynamics of the operator models were then compared. The segmentation, smoothing factor, inlet and outflow branch lengths were found to cause intra-team variability. There was 80% reproducibility in the time-averaged wall shear stress distribution among operators with the major difference attributed to the level of smoothing. Based on these findings, it was concluded that the clinical applicability of CFD simulations may be feasible if a standardised segmentation protocol is developed. Moreover, when analysing the aneurysm shape change over a decade, it was noted that the co-existence of positive and negative values of the wall shear stress divergence (WSSD) contributed to the growth of a daughter sac.