Towards the Clinical utility of CFD for assessment of intracranial aneurysm rupture – a systematic review and novel parameter-ranking tool

Background Intracranial aneurysms (IAs) are vascular dilations on cerebral vessels that affect between 1%–5% of the general population, and can cause life-threatening intracranial hemorrhage when ruptured. Computational fluid dynamics (CFD) has emerged as a promising tool to study IAs in recent years, particularly for rupture risk assessment. However, despite dozens of studies, CFD is still far from clinical use due to large variations and frequent contradictions in hemodynamic results between studies. Purpose To identify key gaps in the field of CFD for the study of IA rupture, and to devise a novel tool to rank parameters based on potential clinical utility. Methods A Pubmed search identified 231 CFD studies for IAs. Forty-six studies fit our inclusion criteria, with a total of 2791 aneurysms. For included studies, study type, boundary conditions, solver resolutions, parameter definitions, geometric and hemodynamic parameters used, and results found were recorded. Data synthesis Aspect ratio, aneurysm size, low wall shear stress area, average wall shear stress, and size ratio were the parameters that correlate most strongly with IA rupture. Limitations Significant differences in parameter definitions, solver spatial and temporal resolutions, number of cycles between studies as well as frequently missing information such as inlet flow rates were identified. A greater emphasis on prospective studies is also needed. Conclusions Our recommendations will help increase standardization and bridge the gaps in the CFD community, and expedite the process of making CFD clinically useful in guiding the treatment of IAs.

[1]  Anil Can,et al.  Association of Hemodynamic Factors With Intracranial Aneurysm Formation and Rupture: Systematic Review and Meta-analysis. , 2016, Neurosurgery.

[2]  D. Ku,et al.  Pulsatile flow in the human left coronary artery bifurcation: average conditions. , 1996, Journal of biomechanical engineering.

[3]  K. Takayama,et al.  A proposed parent vessel geometry-based categorization of saccular intracranial aneurysms: computational flow dynamics analysis of the risk factors for lesion rupture. , 2005, Journal of neurosurgery.

[4]  L. Jou,et al.  Wall Shear Stress on Ruptured and Unruptured Intracranial Aneurysms at the Internal Carotid Artery , 2008, American Journal of Neuroradiology.

[5]  J. Mocco,et al.  Hemodynamic–Morphologic Discriminants for Intracranial Aneurysm Rupture , 2011, Stroke.

[6]  Olivier Brina,et al.  Biology and hemodynamics of aneurismal vasculopathies. , 2013, European journal of radiology.

[7]  J. Xiang,et al.  Morphologic and hemodynamic analysis of paraclinoid aneurysms: ruptured versus unruptured , 2013, Journal of NeuroInterventional Surgery.

[8]  Bu-Lang Gao,et al.  Aneurysm Inflow-Angle as a Discriminant for Rupture in Sidewall Cerebral Aneurysms: Morphometric and Computational Fluid Dynamic Analysis , 2010, Stroke.

[9]  Alexandra Lauric,et al.  Ruptured status discrimination performance of aspect ratio, height/width, and bottleneck factor is highly dependent on aneurysm sizing methodology. , 2012, Neurosurgery.

[10]  C. Putman,et al.  Hemodynamics of Cerebral Aneurysms. , 2009, Annual review of fluid mechanics.

[11]  David A. Steinman,et al.  Automatic Neck Plane Detection and 3D Geometric Characterization of Aneurysmal Sacs , 2012, Annals of Biomedical Engineering.

[12]  A. Algra,et al.  Prevalence and risk of rupture of intracranial aneurysms: a systematic review. , 1998, Stroke.

[13]  A. Malek,et al.  Wall shear stress association with rupture status in volume matched sidewall aneurysms , 2013, Journal of NeuroInterventional Surgery.

[14]  D F Kallmes,et al.  Point: CFD—Computational Fluid Dynamics or Confounding Factor Dissemination , 2012, American Journal of Neuroradiology.

[15]  D. Wiebers,et al.  Cerebral aneurysms. , 2006, The New England journal of medicine.

[16]  W Mitchell,et al.  A Review of Size and Location of Ruptured Intracranial Aneurysms , 2001, Neurosurgery.

[17]  Ying Zhang,et al.  Influence of morphology and hemodynamic factors on rupture of multiple intracranial aneurysms: matched-pairs of ruptured-unruptured aneurysms located unilaterally on the anterior circulation , 2014, BMC Neurology.

[18]  S. Soyal,et al.  A single nucleotide polymorphism in the coding region of PGC-1α is a male-specific modifier of Huntington disease age-at-onset in a large European cohort , 2014, BMC Neurology.

[19]  Ivo G. H. Jansen,et al.  Generalized versus Patient-Specific Inflow Boundary Conditions in Computational Fluid Dynamics Simulations of Cerebral Aneurysmal Hemodynamics , 2014, American Journal of Neuroradiology.

[20]  H. Marquering,et al.  Rupture-Associated Changes of Cerebral Aneurysm Geometry: High-Resolution 3D Imaging before and after Rupture , 2014, American Journal of Neuroradiology.

[21]  V. Pereira,et al.  Application of PHASES and ELAPSS scores to ruptured cerebral aneurysms: how many would have been conservatively managed? , 2018, Journal of neurosurgical sciences.

[22]  Alexandra Lauric,et al.  Critical role of angiographic acquisition modality and reconstruction on morphometric and haemodynamic analysis of intracranial aneurysms , 2018, Journal of NeuroInterventional Surgery.

[23]  C M Putman,et al.  Hemodynamics and Bleb Formation in Intracranial Aneurysms , 2010, American Journal of Neuroradiology.

[24]  D. Wiebers,et al.  Impact of Unruptured Intracranial Aneurysms on Public Health in the United States , 1992, Stroke.

[25]  Alejandro F Frangi,et al.  Hemodynamics and rupture of terminal cerebral aneurysms. , 2009, Academic radiology.

[26]  S Saalfeld,et al.  Does the DSA reconstruction kernel affect hemodynamic predictions in intracranial aneurysms? An analysis of geometry and blood flow variations , 2017, Journal of NeuroInterventional Surgery.

[27]  V. Pereira,et al.  PHASES and ELAPSS Scores Are Associated with Aneurysm Growth: A Study of 431 Unruptured Intracranial Aneurysms. , 2018, World Neurosurgery.

[28]  Jason M. Davies,et al.  Computer-assisted adjuncts for aneurysmal morphologic assessment: toward more precise and accurate approaches , 2017, Medical Imaging.

[29]  D. Nichols,et al.  Unruptured intracranial aneurysms: natural history, clinical outcome, and risks of surgical and endovascular treatment , 2003, The Lancet.

[30]  C. Putman,et al.  Quantitative Characterization of the Hemodynamic Environment in Ruptured and Unruptured Brain Aneurysms , 2010, American Journal of Neuroradiology.

[31]  Karl-Olof Lovblad,et al.  Diagnostic approach to cerebral aneurysms. , 2013, European journal of radiology.

[32]  D. Steinman,et al.  Mind the Gap: Impact of Computational Fluid Dynamics Solution Strategy on Prediction of Intracranial Aneurysm Hemodynamics and Rupture Status Indicators , 2014, American Journal of Neuroradiology.

[33]  C. Putman,et al.  Characterization of cerebral aneurysms for assessing risk of rupture by using patient-specific computational hemodynamics models. , 2005, AJNR. American journal of neuroradiology.