THEORETICAL MODELING OF ARTERIOVENOUS MALFORMATION RUPTURE RISK - A FEASIBILITY AND VALIDATION-STUDY

Purpose: To explore the feasibility of using a theoretical computation al model to simulate the risk of spontaneous arteriovenous malformatio n (AVM) haemorrhage. Methods: Data from 12 patients were collected fro m a prospective databank which documented the angioarchitecture and mo rphological characteristics of the AVM and the feeding mean arterial p ressure (FMAP) measured during initial superselective angiography prio r to any treatment. Using the data, a computational model of the cereb ral circulation and the AVM was constructed for each patient (patient- specific model). Two model risk (Risk(model)) calculations (haemodynam ic- and structural-weighted estimates) were performed by using the pat ient-specific models. In our previously developed method of haemodynam ic-weighted estimate, Risk(model) was calculated with the simulated in tranidal pressures related to its maximal and minimal values. In the m ethod of structural-weighted estimate developed and described in this paper, the vessel mechanical properties and probability calculation we re considered in more detail than in the haemodynamic-weighted estimat e. Risk(model) was then compared to experimentally determined risk whi ch was calculated using a statistical method for determining the relat ive risk of having initially presented with AVM haemorrhage, termed Ri sk(exp). Results: The Risk(model) calculated by both haemodynamic- and structural-weighted estimates correlated with experimental risks with chi(2) = 6.0 and 0.64, respectively. The risks of the structural-weig hted estimate were more correlated to experimental risks. Conclusions: Using two different approaches to the calculation of AVM haemorrhage risk, we found a general agreement with independent statistical estima tes of haemorrhagic risk based on patient data. Computational approach es are feasible; future work can focus on specific pathomechanistic qu estions. Detailed patient-specific computational models can also be de veloped as an adjunct to individual patient risk assessment for risk-s tratification purposes. (C) 1998 IPEM. Published by Elsevier Science L td. All rights reserved.