Large-scale ensemble simulations of biomathematical brain arteriovenous malformation models using graphics processing unit computation

A Computational Framework for Pre-Interventional Planning of Peripheral Arteriovenous Malformations

PURPOSE

Peripheral arteriovenous malformations (pAVMs) are congenital lesions characterised by abnormal high-flow, low-resistance vascular connections-the so-called nidus-between arteries and veins. The mainstay treatment typically involves the embolisation of the nidus, however the complexity of pAVMs often leads to uncertain outcomes. This study aims at developing a simple, yet effective computational framework to aid the clinical decision making around the treatment of pAVMs using routinely acquired clinical data.

METHODS

A computational model was developed to simulate the pre-, intra-, and post-intervention haemodynamics of a patient-specific pAVM. A porous medium of varying permeability was employed to simulate the sclerosant effect on the nidus haemodynamics. Results were compared against clinical data (digital subtraction angiography, DSA, images) and experimental flow-visualization results in a 3D-printed phantom of the same pAVM.

RESULTS

The computational model allowed the simulation of the pAVM haemodynamics and the sclerotherapy-induced changes at different interventional stages. The predicted inlet flow rates closely matched the DSA-derived data, although the post-intervention one was overestimated, probably due to vascular system adaptations not accounted for numerically. The nidus embolization was successfully captured by varying the nidus permeability and increasing its hydraulic resistance from 0.330 to 3970 mmHg s ml-1. The nidus flow rate decreased from 71% of the inlet flow rate pre-intervention to 1%: the flow completely bypassed the nidus post-intervention confirming the success of the procedure.

CONCLUSION

The study demonstrates that the haemodynamic effects of the embolisation procedure can be simulated from routinely acquired clinical data via a porous medium with varying permeability as evidenced by the good qualitative agreement between numerical predictions and both in vivo and in vitro data. It provides a fundamental building block towards a computational treatment-planning framework for AVM embolisation.

Comparison of embolization strategies for mixed plexiform and fistulous brain arteriovenous malformations: a computational model analysis of theoretical risks of nidus rupture

BACKGROUND

High-flow fistulas related to plexiform nidi are found in 40% of large brain arteriovenous malformations (AVMs). Endovascular occlusion of intranidal fistulas before plexiform components is empirically considered safe, but potential ensuing dangerous re-routing of flow through plexiform vessels may in theory raise their rupture risk. It remains unclear whether it is safer to embolize plexiform or fistulous vessels initially. We used a novel biomathematical AVM model to compare theoretical hemodynamic changes and rupture risks on sequential embolizations of both types of nidus vessels.

METHODS

We computationally modeled a theoretical AVM as an electrical circuit containing a nidus consisting of a massive stochastic network ensemble comprising 1000 vessels. We sampled and individually simulated 10 000 different nidus morphologies with a fistula angioarchitecturally isolated from its adjacent plexiform nidus. We used network analysis to calculate mean intravascular pressure (P_mean) and flow rate within each nidus vessel; and Monte Carlo analysis to assess overall risks of nidus rupture when simulating sequential occlusions of vessel types in all 10 000 nidi.

RESULTS

We consistently observed lower nidus rupture risks with initial fistula occlusion in different network morphologies. Intranidal fistula occlusion simultaneously reduced P_mean and flow rate within draining veins.

CONCLUSIONS

Initial occlusion of AVM fistulas theoretically reduces downstream draining vessel hypertension and lowers the risk of rupture of an adjoining plexiform nidus component. This mitigates the theoretical concern that fistula occlusion may cause dangerous redistribution of hemodynamic forces into plexiform nidus vessels, and supports a clinical strategy favoring AVM fistula occlusion before plexiform nidus embolization.

Self-Similar Functional Circuit Models of Arteries and Deterministic Fractal Operators: Theoretical Revelation for Biomimetic Materials

In this paper, the self-similar functional circuit models of arteries are proposed for bioinspired hemodynamic materials design. Based on the mechanical-electrical analogous method, the circuit model can be utilized to mimic the blood flow of arteries. The theoretical mechanism to quantitatively simulate realistic blood flow is developed by establishing a fractal circuit network with an infinite number of electrical components. We have found that the fractal admittance operator obtained from the minimum repeating unit of the fractal circuit can simply and directly determine the blood-flow regulation mechanism. Furthermore, according to the operator algebra, the fractal admittance operator on the aorta can be represented by Gaussian-type convolution kernel function. Similarly, the arteriolar operator can be described by Bessel-type function. Moreover, by the self-similar assembly pattern of the proposed model, biomimetic materials which contain self-similar circuits can be designed to mimic physiological or pathological states of blood flow. Studies show that the self-similar functional circuit model can efficiently describe the blood flow and provide an available and convenient structural theoretical revelation for the preparation of in vitro hemodynamic bionic materials.