Abstract
PurposePeripheral 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.MethodsA 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.ResultsThe 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.ConclusionThe 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.
Highlights
Arteriovenous Malformations (AVMs) are rare vascular developmental abnormalities, characterised by a high flow rate and low resistance shunt between arteries and veins without an intervening network of capillaries.[1]
This study aims at developing a simple, yet effective computational framework to aid the clinical decision making around the treatment of Peripheral AVMs (pAVMs)
The computational model allowed the simulation of the blood flow within the AVM and the haemodynamic changes induced by the sclerotherapy in a simplified, but effective way
Summary
Arteriovenous Malformations (AVMs) are rare vascular developmental abnormalities, characterised by a high flow rate and low resistance shunt between arteries and veins without an intervening network of capillaries.[1]. PAVMs can increase cardiac load leading to left ventricular failure, arterial insufficiency (steal) and chronic venous hypertension. Bleeding, nonhealing and painful ulcerations cause profound psychological and physical disturbances.[1] Besides physical symptoms, AVMs is a debilitating chronic condition that affects all age groups mentally and socially including their quality of life; improvement in their management will have significant benefits to the socioeconomics and healthcare costs despite being rare.[3] Diagnosis of AVM is based on clinical history and physical examination, supported by Doppler ultrasound, magnetic resonance imaging (MRI), computed tomography (CT) scans and intra-arterial digital subtraction angiography (DSA).[4] DSA is a fluoroscopic technique used for visualising blood vessels in which radiopaque structures, such as bones, are ‘‘subtracted’’ digitally from the image, allowing for an accurate visualisation of the blood vessels. To image an AVM, a contrast agent (CA) is usually injected in the blood stream proximally to the AVM and its flow is imaged via X-rays
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