Computer modeling of different shaped patches in classical carotid endarterectomy

Objective: to construct geometric models of carotid bifurcation and build a computer modeling for carotid endarterectomy (CEA) operations with patches of various configurations.

Materials and methods. The method uses reconstructed models of a healthy blood vessel obtained from a preoperative computed tomography (CT) study of the affected blood vessel of a particular patient. Flow in the vessel is simulated by computational fluid dynamics using data from the patient's ultrasonic Doppler velocimetry and CT angiography. Risk factors are assessed by hemodynamic indices at the vessel wall associated with Wall Shear Stress (WSS).

Results. We used the proposed method to study the hemodynamic results of 10 virtual CEA operations with patches of various shapes on a reconstructed healthy artery of a particular patient. The reason for patch implantation was to ensure that the vessel lumen is not narrowed as a result of the surgery, since closing the incision without a patch can reduce the vessel lumen circumference by 4–5 mm, which adversely affects blood flow. On the other hand, too wide a patch creates aneurysmorphic deformation of the internal carotid artery (ICA) mouth, which is not optimal due to formation of a large recirculation zone. In this case, it was found that the implanted patch width of about 3 mm provides an optimal hemodynamic outcome. Deviations from this median value, both upward and downward, impair hemodynamics. The absence of a patch gives the worst of the results considered.

Conclusion: The proposed computer modeling technique is able to provide a personalized patch selection for classical CEA with low risk of restenosis in the long-term follow-up.

1. Kazantsev AN, Tarasov RS, Burkov NN, Shabaev AR, Leader RYu, Mironov AV. Carotid endarterectomy: three-year follow-up in a single-center registry. Angiology and vascular surgery. 2018; 24 (3): 101–108. [In Russ, English abstract].

2. Kazantsev AN, Tarasov RS, Burkov NN, Volkov AN, Grachev KI, Yakhnis EYa et al. Hospital results of percutaneous coronary intervention and carotid endarterectomy in hybrid and phased modes. Angiology and vascular surgery. 2019; 25 (1): 101–107. [In Russ, English abstract]. doi: 10.33529/angio2019114.

3. Zhong L, Zhang JM, Su B et al. Application of Patient- Specific Computational Fluid Dynamics in Coronary and Intra-Cardiac Flow Simulations: Challenges and Opportunities. Front Physiol. 2018; 9: 742. doi: 10.3389/fphys.2018.00742.

4. Gijsen F, Katagiri Y, Barlis P et al. Expert recommendations on the assessment of wall shear stress in human coronary arteries: existing methodologies, technical considerations, and clinical applications. Eur Heart J. 2019; 40 (41): 3421–3433. doi: 10.1093/eurheartj/ehz551.

5. Borisov VG, Zakharov YN, Shokin YI et al. Numerical Method for Predicting Hemodynamic Effects in Vascular Prostheses. Numer Analys. 2019; 12: 326–337. doi: 10.1134/S1995423919040025.

6. Harrison GJ, How TV, Poole RJ, Brennan JA, Naik JB, Vallabhaneni SR, Fisher RK. Closure technique after carotid endarterectomy influences local hemodynamics. J Vasc Surg. 2014; 60 (2): 418–427. doi: 10.1016/j.jvs.2014.01.069.

7. Geers AJ, Morales HG, Larrabide I, Butakoff C, Bijlenga P, Frangi AF. Wall shear stress at the initiation site of cerebral aneurysms. Biomech Model Mechanobiol. 2017; 16 (1): 97–115. doi: 10.1007/s10237-016-0804-3.

8. Steinman DA. Image-based computational fluid dynamics modeling in realistic arterial geometries. Ann Biomed Eng. 2002; 30 (4): 483–497. doi: 10.1114/1.1467679.

9. Hoskins PR, Hardman D. Three-dimensional imaging and computational modelling for estimation of wall stresses in arteries. Br J Radiol. 2009 Jan; 82 Spec No 1: S3–17. doi: 10.1259/bjr/96847348.

10. Avrahami I, Raz D, Bash O. Biomechanical Aspects of Closing Approaches in Postcarotid Endarterectomy. Comput Math Methods Med. 2018; 2018: 4517652. doi: 10.1155/2018/4517652.

11. Kazantsev AN, Burkov NN, Zakharov YuN, Borisov VG, Lider RYu, Bayandin MS, Anufriev AI. Personalized brain revascularization: a method of computer modeling of the reconstruction area for carotid endarterectomy. Surgery. 2020; (6): 71–75. [In Russ, English abstract]. doi: 10.17116/hirurgia202006171.

12. Kazantsev AN, Burkov NN, Borisov VG, Zakharov YN, Sergeeva Tyu, Shabaev AR et al. Computer modeling of hemodynamic parameters in the bifurcation of the carotid arteries after carotid endarterectomy. Angiology and Vascular Surgery. 2019; 25 (3): 107–112. [In Russ, English abstract]. doi: 10.33529/ANGIO2019311.

13. Kazantsev AN, Vinogradov RA, Zakharov YN, Borisov VG, Chernyavsky MA, Kravchuk VN et al. Prediction of restenosis after carotid endarterectomy by computer simulation. Emergency medical care. Journal them. N.V. Sklifosovsky. 2021; 10 (2): 401–407.doi: 10.23934/2223-9022-2021-10-2-401-407.