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Clinical Implications of Hemodynamics in Symptomatic Intracranial Atherosclerotic Stenosis by Computational Fluid Dynamics Modeling: A Systematic Review

Following the PRISMA and MOOSE statement, we searched PubMed and EMBASE database from Jan 2000 to Mar 2024 for studies on using computational fluid dynamics (CFD) technique to investigate the association between hemodynamic metrics and clinical implications in symptomatic intracranial atherosclerotic stenosis (sICAS).

Finally, 19 studies were included in this systematic review, and the article was published on Stroke Vas Neurol.

⚠️ Due to the time sensitivity of systematic review, I will continuously update the included studies when more relevant studies are published.

Included Studies

  1. Leng, X., Scalzo, F., Ip, H. L., Johnson, M., Fong, A. K., Fan, F. S., Chen, X., Soo, Y. O., Miao, Z., Liu, L., Feldmann, E., Leung, T. W., Liebeskind, D. S., & Wong, K. S. (2014). Computational fluid dynamics modeling of symptomatic intracranial atherosclerosis may predict risk of stroke recurrence. PloS one, 9(5), e97531. https://doi.org/10.1371/journal.pone.0097531

  2. Nam, H. S., Scalzo, F., Leng, X., Ip, H. L., Lee, H. S., Fan, F., Chen, X., Soo, Y., Miao, Z., Liu, L., Feldmann, E., Leung, T., Wong, K. S., & Liebeskind, D. S. (2016). Hemodynamic Impact of Systolic Blood Pressure and Hematocrit Calculated by Computational Fluid Dynamics in Patients with Intracranial Atherosclerosis. Journal of neuroimaging : official journal of the American Society of Neuroimaging, 26(3), 331–338. https://doi.org/10.1111/jon.12314

  3. Liu, J., Yan, Z., Pu, Y., Shiu, W. S., Wu, J., Chen, R., Leng, X., Qin, H., Liu, X., Jia, B., Song, L., Wang, Y., Miao, Z., Wang, Y., Liu, L., & Cai, X. C. (2017). Functional assessment of cerebral artery stenosis: A pilot study based on computational fluid dynamics. Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism, 37(7), 2567–2576. https://doi.org/10.1177/0271678X16671321

  4. Leng, X., Lan, L., Ip, H. L., Fan, F., Ma, S. H., Ma, K., Liu, H., Yan, Z., Liu, J., Abrigo, J., Soo, Y. O. Y., Liebeskind, D. S., Wong, K. S., & Leung, T. W. (2018). Translesional pressure gradient and leptomeningeal collateral status in symptomatic middle cerebral artery stenosis. European journal of neurology, 25(2), 404–410. https://doi.org/10.1111/ene.13521

  5. Leng, X., Lan, L., Ip, H. L., Abrigo, J., Scalzo, F., Liu, H., Feng, X., Chan, K. L., Fan, F. S. Y., Ma, S. H., Fang, H., Xu, Y., Li, J., Zhang, B., Xu, Y., Soo, Y. O. Y., Mok, V. C. T., Yu, S. C. H., Liebeskind, D. S., Wong, K. S., … Leung, T. W. (2019). Hemodynamics and stroke risk in intracranial atherosclerotic disease. Annals of neurology, 85(5), 752–764. https://doi.org/10.1002/ana.25456

  6. Lan, L., Leng, X., Ip, V., Soo, Y., Abrigo, J., Liu, H., Fan, F., Ma, S. H., Ma, K., Ip, B. Y., Chan, K. L., Mok, V. C., Liebeskind, D. S., Wong, K. S., & Leung, T. W. (2020). Sustaining cerebral perfusion in intracranial atherosclerotic stenosis: The roles of antegrade residual flow and leptomeningeal collateral flow. Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism, 40(1), 126–134. https://doi.org/10.1177/0271678X18805209

  7. Feng, X., Chan, K. L., Lan, L., Abrigo, J., Ip, V. H. L., Soo, Y. O. Y., Leung, T. W., & Leng, X. (2020). Translesional Pressure Gradient Alters Relationship Between Blood Pressure and Recurrent Stroke in Intracranial Stenosis. Stroke, 51(6), 1862–1864. https://doi.org/10.1161/STROKEAHA.119.028616

  8. Lan, L., Liu, H., Ip, V., Soo, Y., Abrigo, J., Fan, F., Ma, S. H., Ma, K., Ip, B., Liu, J., Fan, Y., Zeng, J., Mok, V., Wong, L., Liebeskind, D., Leung, T., & Leng, X. (2020). Regional High Wall Shear Stress Associated With Stenosis Regression in Symptomatic Intracranial Atherosclerotic Disease. Stroke, 51(10), 3064–3073. https://doi.org/10.1161/STROKEAHA.120.030615

  9. Zhang, D., Wu, X., Tang, J., Wang, P., Chen, G. Z., & Yin, X. (2021). Hemodynamics is associated with vessel wall remodeling in patients with middle cerebral artery stenosis. European radiology, 31(7), 5234–5242. https://doi.org/10.1007/s00330-020-07607-w

  10. Zhang, K., Ren, W., Li, T. X., Wang, Z. L., Gao, B. L., Xia, J. C., Gao, H. L., Wang, Y. F., & Gu, J. J. (2022). Sub-satisfactory recanalization of severe middle cerebral artery stenoses can significantly improve hemodynamics. Frontiers in cardiovascular medicine, 9, 922616. https://doi.org/10.3389/fcvm.2022.922616

  11. Wu, J., Wang, P., Zhou, L., Zhang, D., Chen, Q., Mao, C., Su, W., Huo, Y., Peng, J., Yin, X., & Chen, G. (2022). Hemodynamics derived from computational fluid dynamics based on magnetic resonance angiography is associated with functional outcomes in atherosclerotic middle cerebral artery stenosis. Quantitative imaging in medicine and surgery, 12(1), 688–698. https://doi.org/10.21037/qims-21-337

  12. Tian, X., Fang, H., Lan, L., Ip, H. L., Abrigo, J., Liu, H., Zheng, L., Fan, F. S. Y., Ma, S. H., Ip, B., Song, B., Xu, Y., Li, J., Zhang, B., Xu, Y., Soo, Y. O. Y., Mok, V., Wong, K. S., Leung, T. W., & Leng, X. (2023). Risk stratification in symptomatic intracranial atherosclerotic disease with conventional vascular risk factors and cerebral haemodynamics. Stroke and vascular neurology, 8(1), 77–85. https://doi.org/10.1136/svn-2022-001606

  13. Wang, M., Leng, X., Mao, B., Zou, R., Lin, D., Gao, Y., Wang, N., Lu, Y., Fiehler, J., Siddiqui, A. H., Wu, J., Xiang, J., & Wan, S. (2023). Functional evaluation of intracranial atherosclerotic stenosis by pressure ratio measurements. Heliyon, 9(2), e13527. https://doi.org/10.1016/j.heliyon.2023.e13527

  14. Raynald, Zhao, X., Meng, L., Tong, X., Xu, X., Wang, W., Miao, Z., & Mo, D. (2023). A novel computational fluid dynamic method and validation for assessing distal cerebrovascular microcirculatory resistance. Computer methods and programs in biomedicine, 230, 107338. https://doi.org/10.1016/j.cmpb.2023.107338

  15. Feng, X., Fang, H., Ip, B. Y. M., Chan, K. L., Li, S., Tian, X., Zheng, L., Liu, Y., Lan, L., Liu, H., Abrigo, J., Ma, S. H., Fan, F. S. Y., Ip, V. H. L., Soo, Y. O. Y., Mok, V. C. T., Song, B., Leung, T. W., Xu, Y., & Leng, X. (2023). Cerebral Hemodynamics Underlying Artery-to-Artery Embolism in Symptomatic Intracranial Atherosclerotic Disease. Translational stroke research, 10.1007/s12975-023-01146-4. Advance online publication. https://doi.org/10.1007/s12975-023-01146-4

  16. Zhou, Z. L., Zhu, L. F., Li, T. X., Wu, L. H., Guan, M., Ma, Z. K., Liu, Y. H., Qin, J., & Gao, B. L. (2023). Sub-satisfactory stenting recanalization of severe vascular stenosis of the posterior circulation can significantly improve cerebral hemodynamic perfusion. European journal of radiology, 169, 111135. https://doi.org/10.1016/j.ejrad.2023.111135

  17. Yin, Z., Zhou, C., Guo, J., Wei, Y., Ma, Y., Zhou, F., Zhu, W., & Zhang, L. J. (2024). CT-derived fractional flow reserve in intracranial arterial stenosis: A pilot study based on computational fluid dynamics. European journal of radiology, 171, 111285. https://doi.org/10.1016/j.ejrad.2024.111285

  18. Zheng, L., Tian, X., Abrigo, J., Fang, H., Ip, B. Y., Liu, Y., Li, S., Liu, Y., Lan, L., Liu, H., Ip, H. L., Fan, F. S., Ma, S. H., Ma, K., Lau, A. Y., Soo, Y. O., Leung, H., Mok, V. C., Wong, L. K., Xu, Y., … Leung, T. W. (2024). Hemodynamic significance of intracranial atherosclerotic disease and ipsilateral imaging markers of cerebral small vessel disease. European stroke journal, 9(1), 144–153. https://doi.org/10.1177/23969873231205669

  19. Li, S., Tian, X., Ip, B., Feng, X., Ip, H. L., Abrigo, J., Lan, L., Liu, H., Zheng, L., Liu, Y., Liu, Y., Ma, K. K., Fan, F. S., Ma, S. H., Fang, H., Xu, Y., Lau, A. Y., Leung, H., Soo, Y. O., Mok, V. C., … Leung, T. W. (2024). Cerebral hemodynamics and stroke risks in symptomatic intracranial atherosclerotic stenosis with internal versus cortical borderzone infarcts: A computational fluid dynamics study. Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism, 44(4), 516–526. https://doi.org/10.1177/0271678X231211449

  20. Chen, Z., Liu, J., Wang, A., Wu, B., Cheng, Z., Jiang, Y., Gu, H., Ding, L., Mo, J., Jiang, Y., Liu, L., Jing, L., Jing, J., Wang, Y., Zhao, X., Wang, Y., Qin, H., & Li, Z. (2024). Hemodynamic Impairment of Blood Pressure and Stroke Mechanisms in Symptomatic Intracranial Atherosclerotic Stenosis. Stroke, 10.1161/STROKEAHA.123.046051. Advance online publication. https://doi.org/10.1161/STROKEAHA.123.046051

  21. Huang, K., Yao, W., Song, Z., Jia, X., Gao, J., Liu, R., Han, Y., Liu, X., Du, J., Tu, S., & Zhu, W. (2024). Prognostic value of angiographic based quantitative flow ratio and anatomic features in intracranial atherosclerotic stenosis. Journal of neurointerventional surgery, jnis-2024-022007. Advance online publication. https://doi.org/10.1136/jnis-2024-022007

  22. Li, J., Wang, L., Zhang, Y., Zhu, X., Zhang, X., Hua, W., Chen, R., Liu, H., Yin, W., Xiang, J., Xing, P., Li, Z., Zhao, R., Zhang, Y., Liu, J., Dai, D., Zhang, L., & Yang, P. (2025). Hemodynamic evaluation of symptomatic and asymptomatic intracranial atherosclerotic stenosis using cerebral angiographic images: an exploratory study. Journal of neurointerventional surgery, jnis-2024-022455. Advance online publication. https://doi.org/10.1136/jnis-2024-022455

  23. Hattori, Y., Imada, S., Usui, R., Yamamoto, A., Nakamura, M., & Ihara, M. (2025). High Middle Cerebral Artery Wall Shear Stress in Branch Atheromatous Disease: A Computational Fluid Dynamics Analysis. Journal of atherosclerosis and thrombosis, 10.5551/jat.65439. Advance online publication. https://doi.org/10.5551/jat.65439

  24. Wang, M., Zheng, W., Zou, R., Tang, J., Chen, R., Gao, Y., Wang, N., Lu, Y., Fiehler, J., Siddiqui, A. H., Xiang, J., & Wan, S. (2025). Correlation of computed fractional flow and in-stent restenosis in patients with intracranial atherosclerotic stenosis. Journal of neurointerventional surgery, jnis-2025-023079. Advance online publication. https://doi.org/10.1136/jnis-2025-023079

  25. Liu, Y., Tian, X., Abrigo, J., Li, S., Liu, Y., Lan, L., Liu, H., Ip, B. Y. M., Ma, S. H., Ma, K., Fan, F. S. Y., Ip, H. L., Soo, Y. O. Y., Leung, H., Mok, V. C. T., Leung, T. W., & Leng, X. (2025). Enlarged translesional pressure gradient drives recruitment of leptomeningeal collaterals in medically treated patients with symptomatic middle cerebral artery stenosis. Cerebrovascular diseases (Basel, Switzerland), 1–17. Advance online publication. https://doi.org/10.1159/000547147

  26. Zhu, L., Li, Z., Li, X., Wang, M., Li, S., Lu, Z., Wang, Z., Sun, H., Zhou, J., Su, M., Chen, Y., Chen, G., & Deng, Q. (2025). Magnetic Resonance-Based Hemodynamic Model in Symptomatic Intracranial Atherosclerotic Disease. World neurosurgery, 204, 124570. https://doi.org/10.1016/j.wneu.2025.124570

  27. Wang, L., Xiao, X., Tan, Y., Qian, L., Zhang, X., Zhang, Y., Zhu, X., Xiang, J., Xing, P., Li, Z., Zhao, R., Zhang, Y., Zhang, L., Yang, P., & Liu, J. (2025). Hemodynamic assessment of intracranial atherosclerotic stenosis using angiographic images: correlation with in-stent restenosis. AJNR. American journal of neuroradiology, ajnr.A9050. Advance online publication. https://doi.org/10.3174/ajnr.A9050

  28. Lan, L., Li, S., Liu, H., H L Ip, V., Abrigo, J., Tian, X., Liu, Y., Liu, Y., Li, Z., Liang, T., Fan, F. S. Y., Ma, S. H., Ma, K., Y M Ip, B., Soo, Y. O. Y., Leung, H., Mok, V. C. T., Fang, H., Song, B., Xu, Y., … Leng, X. (2026). Wall Shear Stress Distribution in Intracranial Atherosclerotic Disease and Associations With Vessel and Plaque Morphology. CNS neuroscience & therapeutics, 32(1), e70690. https://doi.org/10.1002/cns.70690

  29. Liu, Y., Zhang, F., Shao, G., Liu, Y., Liu, Y., Ge, P., & Wang, F. (2026). Diagnostic performance of Angio-Based fractional flow for hemodynamic assessment in intracranial Atherosclerosis. European journal of radiology, 195, 112635. https://doi.org/10.1016/j.ejrad.2025.112635

  30. Yang, R., Yin, X., Li, G., Xiang, J., Fang, Q., Wang, H., & Li, B. (2025). CTA and DSA based computational fluid dynamics models for morphological and hemodynamic assessment of intracranial atherosclerotic stenosis. Frontiers in neurology, 16, 1686189. https://doi.org/10.3389/fneur.2025.1686189

  31. Sun, H., Li, B., Wang, Z., Zhang, L., Zhao, J., Zhang, Y., Li, G., Ding, J., Gong, Y., Leo, H. L., & Liu, Y. (2026). Non-Invasive functional assessment of severity in cerebral arterial stenosis using cerebral flow fraction: A hemodynamic study. Medical & biological engineering & computing, 10.1007/s11517-026-03531-1. Advance online publication. https://doi.org/10.1007/s11517-026-03531-1

Qualified Studies in Other Databases

  1. Chen, Yuwen, et al. Non-invasive Assessment of Intracranial Wall Shear Stress Using High-resolution Magnetic Resonance Imaging in Combination with Computational Fluid Dynamics Technique. KeAi Communications Co. Ltd.

Studies verifying the CFD-based hemodynamic parameters with invasively/non-invasively measured counterparts

  1. Yang, P., Wan, S., Wang, J., Hu, Y., Ma, N., Wang, X., Zhang, Y., Zhang, L., Zhu, X., Shen, F., Zheng, Q., Wang, M., Leng, X., Fiehler, J., Siddiqui, A. H., Miao, Z., Xiang, J., & Liu, J. (2024). Hemodynamic assessment for intracranial atherosclerosis from angiographic images: a clinical validation study. Journal of neurointerventional surgery, 16(2), 204–208. https://doi.org/10.1136/jnis-2023-020073

  2. Xiang, J., Zhang, L., Rong, C., Zou, R., Hu, Y., Zhang, Y., Wang, M., Fiehler, J., Siddiqui, A. H., Wang, J., Miao, Z., Yang, P., Wan, S., & Liu, J. (2024). Diagnostic accuracy of hemodynamic assessment of intracranial atherosclerotic stenosis from a single angiographic view: a validation study. Journal of neurointerventional surgery, jnis-2024-022114. Advance online publication. https://doi.org/10.1136/jnis-2024-022114

  3. Wang, X., Bian, Y., Zhang, R., Zhu, H., Yang, J., Wang, R., Liu, X., Lv, B., Cao, X., Dai, W., Sun, Z., Jing, J., Du, Z., Yu, S., & Wang, J. (2024). Hemodynamic assessment of intracranial atherosclerotic stenosis: comparison between invasive non-hyperemic pressure ratio and angiography-derived quantitative flow ratio. Frontiers in neurology, 15, 1466864. https://doi.org/10.3389/fneur.2024.1466864

  4. Zhao, X., Bai, L., Raynald, He, J., Han, B., Xu, X., Miao, Z., & Mo, D. (2025). A computational method to predict cerebral perfusion flow after endovascular treatment based on invasive pressure and resistance. Computer methods and programs in biomedicine, 258, 108510. https://doi.org/10.1016/j.cmpb.2024.108510

Studies with small sample size

  1. Liu, H., Liu, Y., Ip, B. Y. M., Ma, S. H., Abrigo, J., Soo, Y. O. Y., Leung, T. W., & Leng, X. (2022). Effects of stent shape on focal hemodynamics in intracranial atherosclerotic stenosis: A simulation study with computational fluid dynamics modeling. Frontiers in neurology, 13, 1067566. https://doi.org/10.3389/fneur.2022.1067566

  2. Liu, Y., Yan, Z., Li, Z., Liu, Y., Ma, S. H., Ip, B. Y. M., Leung, T. W. H., Liu, J., & Leng, X. (2025). Is invasive fractional flow measurement accurate in intracranial stenosis? A computational simulation study. Journal of neurointerventional surgery, jnis-2025-023342. Advance online publication. https://doi.org/10.1136/jnis-2025-023342

Studies leveraging advanced technique (machine learning...) combined with CFD

  1. Yin, X., Zhao, Y., Huang, F., Wang, H., & Fang, Q. (2025). Machine Learning-Based Classification of Anterior Circulation Cerebral Infarction Using Computational Fluid Dynamics and CT Perfusion Metrics. Brain sciences, 15(4), 399. https://doi.org/10.3390/brainsci15040399

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