AView: An Image-based Clinical Computational Tool for Intracranial Aneurysm Flow Visualization and Clinical Management
- 453 Downloads
Intracranial aneurysms (IAs) occur in around 3% of the entire population. IA rupture is responsible for the most devastating type of hemorrhagic strokes, with high fatality and disability rates as well as healthcare costs. With increasing detection of unruptured aneurysms, clinicians are routinely faced with the dilemma whether to treat IA patients and how to best treat them. Hemodynamic and morphological characteristics are increasingly considered in aneurysm rupture risk assessment and treatment planning, but currently no computational tools allow routine integration of flow visualization and quantitation of these parameters in clinical workflow. In this paper, we introduce AView, a prototype of a clinician-oriented, integrated computation tool for aneurysm hemodynamics, morphology, and risk and data management to aid in treatment decisions and treatment planning in or near the procedure room. Specifically, we describe how we have designed the AView structure from the end-user’s point of view, performed a pilot study and gathered clinical feedback. The positive results demonstrate AView’s potential clinical value on enhancing aneurysm treatment decision and treatment planning.
KeywordsIntracranial aneurysm Computational fluid dynamics Hemodynamics Morphology Image segmentation Clinical tool
- 9.Chien, A., F. Liang, J. Sayre, N. Salamon, P. Villablanca, and F. Vinuela. Enlargement of small, asymptomatic, unruptured intracranial aneurysms in patients with no history of subarachnoid hemorrhage: the different factors related to the growth of single and multiple aneurysms. J. Neurosurg. 119:190–197, 2013.CrossRefPubMedGoogle Scholar
- 10.Connolly, E. S., A. A. Rabistein, J. R. Carhuapoma, C. P. Derdeyn, J. Dion, R. Higashida, et al. Guidelines for the management of aneurysmal subarachnoid hemorrhage: a guideline for healthcare professionals from the American Heart Association/American Stroke Association. Stroke 43, 2012. doi:10.1161/STR.0b013e3182587839.
- 11.Dhar, S., M. Tremmel, J. Mocco, M. Kim, J. Yamamoto, A. H. Siddiqui, et al. Morphology parameters for intracranial aneurysm rupture risk assessment. Neurosurgery 63:185–196; discussion 196–187, 2008.Google Scholar
- 12.Forget, T. R. Jr., R. Benitez, E. Veznedaroglu, A. Sharan, W. Mitchell, M. Silva, et al. A review of size and location of ruptured intracranial aneurysms. Neurosurgery 49:1322–1325; discussion 1325–1326, 2001.Google Scholar
- 18.Nahed, B. V., M. L. DiLuna, T. Morgan, E. Ocal, A. A. Hawkins, K. Ozduman, et al. Hypertension, age, and location predict rupture of small intracranial aneurysms. Neurosurgery 57:676–683; discussion 676–683, 2005.Google Scholar
- 27.Woodward, K., and D. A. Forsberg. Angiosuite: An accurate method to calculate aneurysm volumes and packing densities. J. Neurointerv. Surg. 5(Suppl 3):iii28–32, 2013.Google Scholar
- 28.Xiang, J., D. Ma, K. V. Snyder, E. I. Levy, A. H. Siddiqui, and H. Meng. Increasing flow diversion for cerebral aneurysm treatment using a single flow diverter. Neurosurgery 75:286–294; discussion 294, 2014.Google Scholar
- 30.Xiang, J., V. M. Tutino, K. V. Snyder, and H. Meng. Cfd: computational fluid dynamics or confounding factor dissemination? The role of hemodynamics in intracranial aneurysm rupture risk assessment. AJNR. Am. J. Neuroradiol. 2013 Sep 12. [Epub ahead of print].Google Scholar
- 31.Xiang, J., N. Varble, A. Siddiqui, L. Antiga, and H. Meng. Aview: flow, geometry, risk-and-data management. Proceedings of the ASME 2013 Summer Bioengineering Conference, SBC2013, June 26–29, Sunriver, Oregon, USA, 2013.Google Scholar
- 32.Xiang, J., J. Yu, H. Choi, J. Fox Dolan, K. V. Snyder, E. I. Levy, et al. Rupture resemblance scale (rrs) - toward risk stratification of unruptured intracranial aneurysms using hemodynamic-morphologic discriminants. J. Neurointerventional Surg. 2014.Google Scholar