|
[1]
|
Xiang, J., Tutino, V.M., Snyder, K.V., et al. (2014) CFD: Computational Fluid Dynamics or Confounding Factor Dis-semination? The Role of Hemodynamics in Intracranial Aneurysm Rupture Risk Assessment. American Journal of Neu-roradiology, 35, 1849-1857. [Google Scholar] [CrossRef]
|
|
[2]
|
Saqr, K.M., Rashad, S., Tupin, S., et al. (2020) What does Computational Fluid Dynamics Tell Us about Intracranial Aneurysms? A Meta-Analysis and Critical Review. Journal of Cerebral Blood Flow & Metabolism, 40, 1021-1039. [Google Scholar] [CrossRef]
|
|
[3]
|
Cebral, J.R., Mut, F., Weir, J., et al. (2011) Quantitative Charac-terization of the Hemodynamic Environment in Ruptured and Unruptured Brain Aneurysms. American Journal of Neu-roradiology, 32, 145-151. [Google Scholar] [CrossRef]
|
|
[4]
|
Xiang, J., Natarajan, S.K., Tremmel, M., et al. (2011) Hemodynam-ic-Morphologic Discriminants for Intracranial Aneurysm Rupture. Stroke, 42, 144-152. [Google Scholar] [CrossRef]
|
|
[5]
|
Russell, J.H., Kelson, N., Barry, M., et al. (2013) Com-putational Fluid Dynamic Analysis of Intracranial Aneurysmal Bleb Formation. Neurosurgery, 73, 1061-1068. [Google Scholar] [CrossRef]
|
|
[6]
|
Murayama, Y., Fujimura, S., Suzuki, T., et al. (2019) Computational Fluid Dynamics as a Risk Assessment Tool for Aneurysm Rupture. Neurosurgical Focus, 47, E12. [Google Scholar] [CrossRef]
|
|
[7]
|
Skodvin, T.O., Evju, O., Helland, C.A., et al. (2018) Rupture Prediction of Intracranial Aneurysms: A Nationwide Matched Case-Control Study of Hemodynamics at the Time of Di-agnosis. Journal of Neurosurgery, 129, 854-860. [Google Scholar] [CrossRef]
|
|
[8]
|
Can, A. and Du, R. (2016) Association of Hemodynamic Factors with Intracranial Aneurysm Formation and Rupture: Systematic Review and Meta-Analysis. Neurosurgery, 78, 510-519. [Google Scholar] [CrossRef]
|
|
[9]
|
Xiang, J., Damiano, R.J., Lin, N., et al. (2015) High-Fidelity Virtual Stenting: Modeling of Flow Diverter Deployment for Hemodynamic Characterization of Complex Intracranial Aneurysms. Journal of Neurosurgery, 123, 832-840. [Google Scholar] [CrossRef]
|
|
[10]
|
Walcott, B.P., Reinshagen, C., Stapleton, C.J., et al. (2016) Pre-dictive Modeling and in Vivo Assessment of Cerebral Blood Flow in the Management of Complex Cerebral Aneurysms. Journal of Cerebral Blood Flow & Metabolism, 36, 998-1003. [Google Scholar] [CrossRef]
|
|
[11]
|
Valen-Sendstad, K., Piccinelli, M., Krishnankuttyrema, R., et al. (2015) Estimation of Inlet Flow Rates for Image-Based Aneurysm CFD Models: Where and How to Begin? Annals of Biomedical Engineering, 43, 1422-1431. [Google Scholar] [CrossRef] [PubMed]
|
|
[12]
|
Jing, L., Fan, J., Wang, Y., et al. (2015) Morphologic and He-modynamic Analysis in the Patients with Multiple Intracranial Aneurysms: Ruptured versus Unruptured. PLOS ONE, 10, e0132494. [Google Scholar] [CrossRef] [PubMed]
|
|
[13]
|
Baharoglu, M.I., Schirmer, C.M., Hoit, D.A., et al. (2010) An-eurysm Inflow-Angle as a Discriminant for Rupture in Sidewall Cerebral Aneurysms: Morphometric and Computational Fluid Dynamic Analysis. Stroke, 41, 1423-1430. [Google Scholar] [CrossRef]
|
|
[14]
|
Kono, K. and Terada, T. (2014) Treatment Strategy and Follow-Up Evaluation for an Unruptured Anterior Communicating Artery Aneurysm Associated with Pseudo-Occlusion of the Internal Carotid Artery Using Computational Fluid Dynamics Simulations. Turkish Neurosurgery, 24, Article No. 6.
|
|
[15]
|
Omodaka, S., Sugiyama, S., Inoue, T., et al. (2012) Local Hemodynamics at the Rupture Point of Cerebral An-eurysms Determined by Computational Fluid Dynamics Analysis. Cerebrovascular Diseases, 34, 121-129. [Google Scholar] [CrossRef] [PubMed]
|
|
[16]
|
Fukazawa, K., Ishida, F., Umeda, Y., et al. (2015) Using Computational Fluid Dynamics Analysis to Characterize Local Hemodynamic Features of Middle Cerebral Artery Aneurysm Rupture Points. World Neurosurgery, 83, 80-86. [Google Scholar] [CrossRef] [PubMed]
|
|
[17]
|
Xiang, J., Yu, J., Snyder, K.V., et al. (2016) Hemodynam-ic-Morphological Discriminant Models for Intracranial Aneurysm Rupture Remain Stable with Increasing Sample Size. Journal of Neurointerventional Surgery, 8, 104-110. [Google Scholar] [CrossRef] [PubMed]
|
|
[18]
|
Lu, G., Huang, L., Zhang, X.L., et al. (2011) Influence of Hemodynamic Factors on Rupture of Intracranial Aneurysms: Patient-Specific 3D Mirror Aneurysms Model Computa-tional Fluid Dynamics Simulation. American Journal of Neuroradiology, 32, 1255-1261. [Google Scholar] [CrossRef]
|
|
[19]
|
Meng, H., Tutino, V.M., Xiang, J., et al. (2014) High WSS or Low WSS? Complex Interactions of Hemodynamics with Intracranial Aneurysm Initiation, Growth, and Rupture: Toward a Unifying Hypothesis. American Journal of Neuroradiology, 35, 1254-1262. [Google Scholar] [CrossRef]
|
|
[20]
|
Qian, Y., Takao, H., Umezu, M., et al. (2011) Risk Analysis of Unruptured Aneurysms Using Computational Fluid Dynamics Technology: Preliminary Results. American Journal of Neuroradiology, 32, 1948-1955. [Google Scholar] [CrossRef]
|
|
[21]
|
Takao, H., Murayama, Y., Otsuka, S., et al. (2012) Hemodynamic Differ-ences between Unruptured and Ruptured Intracranial Aneurysms during Observation. Stroke, 43, 1436-1439. [Google Scholar] [CrossRef]
|
|
[22]
|
Kadasi, L.M., Dent, W.C. and Malek, A.M. (2013) Colo-calization of Thin-Walled Dome Regions with Low Hemodynamic Wall Shear Stress in Unruptured Cerebral Aneurysms Clinical Article. Journal of Neurosurgery, 119, 172-179. [Google Scholar] [CrossRef]
|
|
[23]
|
Suzuki, T., Takao, H., Suzuki, T., et al. (2017) Variability of He-modynamic Parameters Using the Common Viscosity Assumption in a Computational Fluid Dynamics Analysis of In-tracranial Aneurysms. Technology and Health Care, 25, 37-47. [Google Scholar] [CrossRef]
|