Annals of Biomedical Engineering

, Volume 44, Issue 4, pp 1085–1096 | Cite as

AView: An Image-based Clinical Computational Tool for Intracranial Aneurysm Flow Visualization and Clinical Management

  • Jianping Xiang
  • Luca Antiga
  • Nicole Varble
  • Kenneth V. Snyder
  • Elad I. Levy
  • Adnan H. Siddiqui
  • Hui Meng
Article

Abstract

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.

Keywords

Intracranial aneurysm Computational fluid dynamics Hemodynamics Morphology Image segmentation Clinical tool 

Notes

Acknowledgments

We thank the participants for the technology feasibility test of AView in the clinical workflow: Dr. Kenichi Kono from Wakayama Rosai Hospital; Dr. Ansaar Rai and Dr. Jeffrey Carpenter from West Virginia University; Dr. Shin-ichiro Sugiyama from Tohoku Kohnan hospital; Dr. Mandy Binning from Capital Health; Dr. Rabih G Tawk from Mayo Clinic (Florida); Dr. Hoon Choi and Dr. Eric Deshaies from SUNY-Upstate Medical University; Dr. Andrew Ringer from University of Cincinnati, and Dr. Adnan H. Siddiqui from University at Buffalo. We also thank Dr. Yiemeng Hoi for stimulating discussions and Nikhil Paliwal for assistance in figure preparation. This work was funded by Toshiba Medical Systems Corp.

Conflict of interest

Dr. Xiang: principal investigator of Dawn Brejcha Chair of Research Grant from Brain Aneurysm Foundation and co-investigator of NIH Grant (R01NS091075-01). Dr. Antiga and Nicole Varble: none. Dr. Snyder: consultant: Toshiba; speakers’ bureau: Toshiba, ev3/Covidien and The Stroke Group; honoraria: Toshiba, ev3/Covidien and The Stroke Group. Dr. Levy: shareholder/ownership interests: Intratech Medical Ltd., Mynx/Access Closure, Blockade Medical LLC. Principal investigator: Covidien US SWIFT PRIME Trials. Other financial support: Abbott for carotid training for physicians. Dr. Siddiqui: research Grants: co-investigator of NIH Grants (R01NS091075-01and 5R01EB002873) and Research Development Award from the University at Buffalo; financial interests: Blockade Medical, Hotspur, Intratech Medical, Lazarus Effect, StimSox, Valor Medical; consultant: Blockade Medical, Codman & Shurtleff, Inc., Concentric Medical, ev3/Covidien Vascular Therapies, GuidePoint Global Consulting, Lazarus Effect, MicroVention, Penumbra, Stryker, Pulsar Vascular; National Steering Committee: 3D Separator Trial (Penumbra, Inc.), SWIFT PRIME Trial (Covidien), FRED Trial (MicroVention); speakers’ bureau: Codman & Shurtleff, Inc.; advisory board: Codman& Shurtleff, Inc., Covidien Neurovascular; honoraria: Abbott Vascularand Codman & Shurtleff, Inc. for training other physicians in carotid stenting and endovascular stenting for aneurysms, and Penumbra, Inc. Dr. Meng: principal investigator of NIH Grant (R01NS091075-01), the Grant from Toshiba Medical Systems and The Carol W. Harvey Memorial Chair of Research Grant from Brain Aneurysm Foundation.

References

  1. 1.
    Antiga, L., B. Ene-Iordache, L. Caverni, G. P. Cornalba, and A. Remuzzi. Geometric reconstruction for computational mesh generation of arterial bifurcations from ct angiography. Comput. Med. Imaging Graph. 26:227–235, 2002.CrossRefPubMedGoogle Scholar
  2. 2.
    Antiga, L., M. Piccinelli, L. Botti, B. Ene-Iordache, A. Remuzzi, and D. A. Steinman. An image-based modeling framework for patient-specific computational hemodynamics. Med. Biol. Eng. Comput. 46:1097–1112, 2008.CrossRefPubMedGoogle Scholar
  3. 3.
    Botti, L., K. V. Canneyt, R. Kaminsky, T. Claessens, R. Planken, P. Verdonck, et al. Numerical evaluation and experimental validation of pressure drops across a patient-specific model of vascular access for hemodialysis. Cardiovasc. Eng. Technol. 4:485–499, 2013.CrossRefGoogle Scholar
  4. 4.
    Botti, L., and D. A. Di Pietro. A pressure-correction scheme for convection-dominated incompressible flows with discontinuous velocity and continuous pressure. J. Comput. Phys. 230:572–585, 2011.CrossRefGoogle Scholar
  5. 5.
    Brassel, F., J. Rademaker, C. Haupt, and H. Becker. Intravascular stent placement for a fusiform aneurysm of the posterior cerebral artery: Case report. Eur. Radiol. 11:1250–1253, 2001.CrossRefPubMedGoogle Scholar
  6. 6.
    Cebral, J. R., and H. Meng. Counterpoint: realizing the clinical utility of computational fluid dynamics–closing the gap. AJNR Am. J. Neuroradiol. 33:396–398, 2012.CrossRefPubMedGoogle Scholar
  7. 7.
    Cebral, J. R., F. Mut, M. Raschi, E. Scrivano, R. Ceratto, P. Lylyk, et al. Aneurysm rupture following treatment with flow-diverting stents: computational hemodynamics analysis of treatment. AJNR Am. J. Neuroradiol. 32:27–33, 2011.CrossRefPubMedGoogle Scholar
  8. 8.
    Cebral, J. R., F. Mut, J. Weir, and C. Putman. Quantitative characterization of the hemodynamic environment in ruptured and unruptured brain aneurysms. AJNR Am. J. Neuroradiol. 32:145–151, 2011.CrossRefPubMedPubMedCentralGoogle Scholar
  9. 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. 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. 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. 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
  13. 13.
    Hoi, Y., S. H. Woodward, M. Kim, D. B. Taulbee, and H. Meng. Validation of cfd simulations of cerebral aneurysms with implication of geometric variations. J. Biomech. Eng. 128:844–851, 2006.CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Kashiwazaki, D., S. Kuroda, and S. A. H. S. G. Sapporo. Size ratio can highly predict rupture risk in intracranial small (<5 mm) aneurysms. Stroke 44:2169–2173, 2013.CrossRefPubMedGoogle Scholar
  15. 15.
    Kelly, P. J., J. Stein, S. Shafqat, C. Eskey, D. Doherty, Y. Chang, et al. Functional recovery after rehabilitation for cerebellar stroke. Stroke 32:530–534, 2001.CrossRefPubMedGoogle Scholar
  16. 16.
    Larrabide, I., M. C. Villa-Uriol, R. Cardenes, V. Barbarito, L. Carotenuto, A. J. Geers, et al. Angiolab—a software tool for morphological analysis and endovascular treatment planning of intracranial aneurysms. Comput. Methods Progr. Biomed. 108:806–819, 2012.CrossRefGoogle Scholar
  17. 17.
    Ma, D., J. Xiang, H. Choi, T. M. Dumont, S. K. Natarajan, A. H. Siddiqui, et al. Enhanced aneurysmal flow diversion using a dynamic push-pull technique: an experimental and modeling study. AJNR Am. J. Neuroradiol. 35:1779–1785, 2014.CrossRefPubMedGoogle Scholar
  18. 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
  19. 19.
    Raghavan, M. L., B. Ma, and R. E. Harbaugh. Quantified aneurysm shape and rupture risk. J. Neurosurg. 102:355–362, 2005.CrossRefPubMedGoogle Scholar
  20. 20.
    Ropper, A. H., and N. T. Zervas. Outcome 1 year after sah from cerebral aneurysm. Management morbidity, mortality, and functional status in 112 consecutive good-risk patients. J. Neurosurg. 60:909–915, 1984.CrossRefPubMedGoogle Scholar
  21. 21.
    Tremmel, M., J. Xiang, S. K. Natarajan, L. N. Hopkins, A. H. Siddiqui, E. I. Levy, et al. Alteration of intra-aneurysmal hemodynamics for flow diversion using enterprise and vision stents. World Neurosurg. 74:306–315, 2010.CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Ujiie, H., H. Tachibana, O. Hiramatsu, A. L. Hazel, T. Matsumoto, Y. Ogasawara, et al. Effects of size and shape (aspect ratio) on the hemodynamics of saccular aneurysms: a possible index for surgical treatment of intracranial aneurysms. Neurosurgery 45:119–130, 1999.CrossRefPubMedGoogle Scholar
  23. 23.
    Villa-Uriol, M. C., G. Berti, D. R. Hose, A. Marzo, A. Chiarini, J. Penrose, et al. @neurist complex information processing toolchain for the integrated management of cerebral aneurysms. Interface Focus 1:308–319, 2011.CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Vlak, M. H., A. Algra, R. Brandenburg, and G. J. Rinkel. Prevalence of unruptured intracranial aneurysms, with emphasis on sex, age, comorbidity, country, and time period: a systematic review and meta-analysis. Lancet Neurol. 10:626–636, 2011.CrossRefPubMedGoogle Scholar
  25. 25.
    Weir, B., L. Disney, and T. Karrison. Sizes of ruptured and unruptured aneurysms in relation to their sites and the ages of patients. J. Neurosurg. 96:64–70, 2002.CrossRefPubMedGoogle Scholar
  26. 26.
    Wiebers, D. O., J. C. Torner, and I. Meissner. Impact of unruptured intracranial aneurysms on public health in the united states. Stroke 23:1416–1419, 1992.CrossRefPubMedGoogle Scholar
  27. 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. 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
  29. 29.
    Xiang, J., S. K. Natarajan, M. Tremmel, D. Ma, J. Mocco, L. N. Hopkins, et al. Hemodynamic-morphologic discriminants for intracranial aneurysm rupture. Stroke 42:144–152, 2011.CrossRefPubMedPubMedCentralGoogle Scholar
  30. 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. 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. 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

Copyright information

© Biomedical Engineering Society 2015

Authors and Affiliations

  • Jianping Xiang
    • 1
    • 2
    • 3
  • Luca Antiga
    • 6
  • Nicole Varble
    • 1
    • 2
  • Kenneth V. Snyder
    • 1
    • 3
    • 4
  • Elad I. Levy
    • 1
    • 3
    • 4
  • Adnan H. Siddiqui
    • 1
    • 3
    • 4
  • Hui Meng
    • 1
    • 2
    • 3
    • 5
  1. 1.Toshiba Stroke and Vascular Research CenterUniversity at Buffalo, The State University of New YorkBuffaloUSA
  2. 2.Department of Mechanical and Aerospace EngineeringUniversity at Buffalo, The State University of New YorkBuffaloUSA
  3. 3.Department of NeurosurgeryUniversity at Buffalo, The State University of New YorkBuffaloUSA
  4. 4.Department of RadiologyUniversity at Buffalo, The State University of New YorkBuffaloUSA
  5. 5.Department of Biomedical EngineeringUniversity at Buffalo, The State University of New YorkBuffaloUSA
  6. 6.Orobix srlBergamoItaly

Personalised recommendations