Towards Building a Multiscale Mechanical Model for the Prediction of Acute Subdural Hematomas

Abstract

Acute subdural hematoma (ASDH) is a potentially devastating, yet curable, extra axial fluid collection within the subdural space situated between the skull and the cortex. It is often due to rupture of bridging veins crossing this subdural space, caused by the brain-skull relative motion. To be able to predict ASDH, a numerical model reflecting the mechanical properties of vascular walls is attractive. With this in mind, a suitable approach consists in modeling the material microstructure at different scales. In a former work [1, 2], R. Abdel Rahman studied the mechanical properties of the bridging veins – superior sagittal sinus junction when a human head is submitted to shock. This work showed the apparition of ASDH over a given value of head rotational acceleration. But lacks in the knowledge of microstructure and of the constituents mechanical properties were put forward in understanding the relations between material mechanical behavior and the apparition of ASDH. Therefore we chose to adopt a multiscale approach to model ASDH apparition. In the current work, several experimental observations have been set up to obtain a sufficient knowledge of the vein wall microstructure which was imprecisely documented to date. Stained thin slices of human brain were observed by optical microscopy. In addition, microtomography was used to assess the collagen fibers orientations. These observations allowed the identification of the different scales needed for modeling the microstructure. Many authors [3–6] deal with the mechanical behavior of vascular walls and of their various constituents but none of them consider multiple scales for modeling [7]. The next step of this work consists in improving the predictive capabilities of the existing model by going down the scales and taking microstructure into account. This methodology enabled the introduction of only physical parameters into the model, which is essential for future predictive capabilities. Finally, a failure criterion for the bridging veins taking into account the different scales has been created and is still being improved. It allows the evaluation of specific disease influence like collagen damage due to physiology. Besides it provides a prediction tool for ASDH useable for optimization of various shock absorbers.