Dynamic monitoring of morphological and hemodynamic evolution of small cerebral aneurysms

Highlights. Small cerebral aneurysms (<3 mm), which make up the majority of aneurysms, rupture more frequently, although medium (>3 mm) and giant (>15 mm) aneurysms and have a higher risk of rupture. This article proves for the first time that the rupture risk criteria developed for giant cerebral aneurysms do not work for small aneurysms. The development of small aneurysms in patients was analyzed and measured morphological features of aneurysms were compared with their calculated hydrodynamic characteristics.

Aim. To study the dynamics of development of small cerebral aneurysms, to assess the applicability of existing methods for calculating the risk of rupture, to formulate new clarifying hypotheses for calculating the risk of rupture of small cerebral aneurysms.

Methods. Patient data were provided by the Federal Center for Neurosurgery, Novosibirsk. CT angiography was performed using a Philips Ingenuite CT scanner (Philips Medical Systems, USA, 128 slices). Aneurysm size dynamics was assessed by measuring three main sizes with an accuracy of 0.1 mm using the IntelliSpace Portal Philips software environment. Numerical calculations were carried out using ANSYS CFX 2020R2.

Results. Hemodynamic characteristics change according to the changes of the aneurysm dome. In the case when morphological characteristics of the aneurysm have not changed, a change in the geometry of the patient's circle of Willis (coW) is observed: the curvature of the arteries, the angles of bifurcations (the structure of coW remained unchanged). The PHASES score (absolute risks of rupture for aneurysms) was found to be unusable for the considered aneurysms.

Conclusion. This work formulates and morphologically and hydrodynamically confirms for the first time in the volunteers that the change in risk estimates for such aneurysms is fundamentally affected, even insignificantly, by the change in the circle of Willis: a change in the curvature of individual segments of the cerebral arteries, as well as the angles of their bifurcations. The results obtained are aimed at modifying the existing risk criteria for rupture of cerebral aneurysms.

1. Rinkel G.J., Djibuti M., Algra A., van Gijn J. Prevalence and risk of rupture of intracranial aneurysms: a systematic review. Stroke. 1998;29(1):251-6. doi: 10.1161/01.str.29.1.251.

2. International Study of Unruptured Intracranial Aneurysms Investigators. Unruptured intracranial Aneurysms Risk of Rupture and Risk of surgical intervention. N. Engl. J. Med. 1998; 339:1725–1733. doi: 10.1056/NEJM199812103392401.

3. Salvadori E., Papi G., Insalata G., Rinnoci V., Donnini I., Martini M., Falsini C., Hakiki B., Romoli A., Barbato C., Polcaro P., Casamorata F., Macchi C., Cecchi F., Poggesi A. Comparison between Ischemic and Hemorrhagic Strokes in Functional Outcome at Discharge from an Intensive Rehabilitation Hospital. Diagnostics (Basel). 2020;11(1):38. doi: 10.3390/diagnostics11010038.

4. Hoh B.L.. Putman C.M., Budzik R.F., Carter B.S., Ogilvy C.S. Combined surgical and endovascular techniques of flow alteration to treat fusiform and complex wide-necked intracranial aneurysms that are unsuitable for clipping or coil embolization. J Neurosurg. 2001;95(1):24-35. doi: 10.3171/jns.2001.95.1.0024.

5. Andaluz N., Zuccarello M. Treatment strategies for complex intracranial aneurysms: review of a 12-year experience at the university of cincinnati. Skull Base. 2011;21(4):233-42. doi: 10.1055/s-0031-1280685.

6. Khe A.K., Chupakhin A.P., Cherevko A.A., Eliava S.S., Pilipenko Y.V. Viscous dissipation energy as a risk factor in multiple cerebral aneurysms. Russ. J. Numer. Anal. Math. Model. 2015; 30(5): 277–287. doi: 10.1515/rnam-2015-0025

7. Dhar S., Tremmel M., Mocco J., Kim M., Yamamoto J., Siddiqui A.H., Hopkins L.N., Meng H. Morphology parameters for intracranial aneurysm rupture risk assessment. Neurosurgery. 2008;63(2):185-96; discussion 196-7. doi: 10.1227/01.NEU.0000316847.64140.81.

8. Greving J.P., Wermer M.J., Brown R.D.Jr., Morita A., Juvela S., Yonekura M., Ishibashi T., Torner J.C., Nakayama T., Rinkel G.J., Algra A. Development of the PHASES score for prediction of risk of rupture of intracranial aneurysms: a pooled analysis of six prospective cohort studies. Lancet Neurol. 2014;13(1):59-66. doi: 10.1016/S1474-4422(13)70263-1.

9. Neyazi B., Swiatek V.M., Skalej M., Beuing O., Stein K.P., Hattingen J., Preim B., Berg P., Saalfeld S., Sandalcioglu I.E. Rupture risk assessment for multiple intracranial aneurysms: why there is no need for dozens of clinical, morphological and hemodynamic parameters. Ther Adv Neurol Disord. 2020;13:1756286420966159. doi: 10.1177/1756286420966159.

10. Gombolevskij V. A., Morozov S. P., Chernina V. Yu., editors. Rukovodstvo dlya rentgenolaborantov po vypolneniyu protokolov issledovanij na komp'yuternom tomografe: uchebnometodicheskoe posobie. Moscow: GBUZ «NPKC DiT DZM»; 2020. (In Russian)

11. Krylov V.V., Grin' A.A., Prirodov A.V., editors. Cerebral'nye anevrizmy. Netravmaticheskoe subarahnoidal'noe krovoizliyanie. Metodicheskie rekomendacii. Moscow: GBUZ NII SP im. N.V. Sklifosovskogo DZM; 2021 (In Russian)

12. Backes D., Vergouwen M.D., Tiel Groenestege A.T., Bor A.S., Velthuis B.K., Greving J.P., Algra A., Wermer M.J., van Walderveen M.A., terBrugge K.G., Agid R., Rinkel G.J. PHASES Score for Prediction of Intracranial Aneurysm Growth. Stroke. 2015;46(5):1221-6. doi: 10.1161/STROKEAHA.114.008198.

13. Yushkevich P.A., Piven J., Hazlett H.C., Smith R.G., Ho S., Gee J.C., Gerig G. User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. Neuroimage. 2006;31(3):1116-28. doi: 10.1016/j.neuroimage.2006.01.015.

14. ANSYS. ANSYS Documentation, ANSYS CFX-Solver Theory Guide. http://www.ansys.com/2006 .

15. Kuyanova Y.O., Chupakhin A.P., Parshin D.V., Presnyakov S.S., Dubovoi A.V. Numerical Study of the Tee Hydrodynamics in the Model Problem of Optimizing the LowFlow Vascular Bypass Angle. Journal of Applied Mechanics and Technical Physics. 2019;60 (6): 1038–1045. doi: 10.1134/S0021894419060087

16. Kuianova Iu.O., Dubovoy A.V., Parshin D V . Towards the numerical assessment in solving the problem of the effectiveness of vascular anastomosis in neurosurgical operations. Journal of Physics: Conference Series. 2019; 1359:012085. doi 10.1088/1742-6596/1359/1/012085

17. Tikhvinskii D., Kuianova J., Kislitsin D., Orlov K., Gorbatykh A., Parshin D. Numerical Assessment of the Risk of Abnormal Endothelialization for Diverter Devices: Clinical Data Driven Numerical Study. J Pers Med. 2022;12(4):652. doi: 10.3390/jpm12040652.

18. Zarrinkoob L., Ambarki K., Wåhlin A., Birgander R., Eklund A., Malm J. Blood flow distribution in cerebral arteries. J Cereb Blood Flow Metab. 2015;35(4):648-54. doi: 10.1038/jcbfm.2014.241.

19. Etminan N., Rinkel G.J. Unruptured intracranial aneurysms: development, rupture and preventive management. Nat Rev Neurol. 2016;12(12):699-713. doi: 10.1038/nrneurol.2016.150.

20. Oliveira I., Gasche J. L., Militzer Ju., Baccin C. Hemodynamic and morphological case study of an intracranial aneurysm inception and evolution. 25th International Congress of Mechanical Engineering - COBEM 2019. 20-25 October. 2019. doi: 10.26678/ABCM.COBEM2019.COB2019-0516