AN ELECTRICAL NETWORK MODEL OF INTRACRANIAL ARTERIOVENOUS-MALFORMATIONS - ANALYSIS OF VARIATIONS IN HEMODYNAMIC AND BIOPHYSICAL PARAMETERS

The propensity of intracranial arteriovenous malformations (AVMs) to h emorrhage is correlated significantly with their hemodynamic features. Biomathematical models offer a theoretical approach to analyse comple x AVM hemodynamics, which otherwise are difficult to quantify, particu larly within or in close proximity to the nidus. Our purpose was to in vestigate a newly developed biomathematical AVM model based on electri cal network analysis in which morphological, biophysical, and hemodyna mic characteristics of intracranial AVMs were replicated accurately. S everal factors implemented into the model were altered systematically to study the effects of a possible wide range of normal variations in AVM hemodynamic and biophysical parameters on the behavior of this mod el and its fidelity to physiological reality. The model represented a complex, noncompartmentalized AVM with four arterial feeders, two drai ning veins, and a nidus consisting of 28 interconnected plexiform and fistulous components. Various clinically-determined, experimentally-ob served, or hypothetically-assumed values for the nidus vessel radii (p lexiform: 0.01 cm-0.1 cm; fistulous: 0.1 cm-0.2 cm), mean systemic art erial pressure (71 mm Hg-125 mm Hg) mean arterial feeder pressures (21 mm Hg-80 mm Hg), mean draining vein pressures 15 mm Hg-23 mm Hg), wal l thickness of nidus vessels (20 mu m-70 mu m), and elastic modulus of nidus vessels (1 x 10(4) dyn/cm(2) to 1 x 10(5) dyn/cm(2)) were used as normal or realistic ranges of parameters implemented in the model. Using an electrical analogy of Ohm's law, flow was determined based on Poiseuille's law given the aforementioned pressures and resistance of each nidus vessel. Circuit analysis of the AVM vasculature based on t he conservation of flow and voltage revealed the flow rate through eac h vessel in the AVM network. An expression for the risk of AVM nidus r upture was derived based on the functional distribution of the critica l radii of component vessels. The two characteristics which were used to judge the fidelity of the theoretical performance of the AVM model against the physiological one of human AVMs were total volumetric flow through the AVM (less than or equal to 900 ml/min), and its risk of r upture (< 100%). Applying these criteria, a series of 216 (out of 260) AVM models using different combinations of these hemodynamic and biop hysical parameters resulted in a physiologically-realistic conduct of the model (yielding a total flow through the AVM model varying from 44 9.9 ml/min to 888.6 ml/min, and a maximum risk of rupture varying from 26.4 to 99.9%). The described novel biomathematical model characteriz es the transnidal and intranidal hemodynamics of an intracranial AVM m ore accurately than previously possible. A wide range of hemodynamic a nd biophysical parameters can be implemented in this AVM model to resu lt in simulation of human AVMs with differing characteristics (e.g. lo w-flow and high-now AVMs). This experimental model should serve as a u seful research tool for further theoretical investigations of a variet y of intracranial AVMs and their hemodynamic sequelae.