Bridging veins drain the venous blood from the cerebral cortex into the superior sagittal sinus (SSS) and doing so they bridge the subdural space. Despite their importance in head impact biomechanics, little is known about their properties with respect to histology, morphology and mechanical behaviour. Knowledge of these characteristics is essential for creating a biofidelic finite element model to study the biomechanics of head impact, ultimately leading to the improved design of protective devices by setting up tolerance criteria. This paper presents a comprehensive review of the state-of-the-art knowledge on bridging veins. Tolerance criteria to prevent head injury through impact have been set by a number of research groups, either directly through impact experiments or by means of finite element (FE) simulations. Current state-of-the-art FE head models still lack a biofidelic representation of the bridging veins. To achieve this, a thorough insight into their nature and behaviour is required. Therefore, an overview of the general morphology and histology is provided here, showing the clearly heterogeneous nature of the bridging vein complex, with its three different layers and distinct morphological and histological changes at the region of outflow into the superior sagittal sinus. Apart from a complex morphology, bridging veins also exhibit complex mechanical behaviour, being nonlinear, viscoelastic and prone to damage. Existing material models capable of capturing these properties, as well as methods for experimental characterisation, are discussed. Future work required in bridging vein research is firstly to achieve consensus on aspects regarding morphology and histology, especially in the outflow cuff segment. Secondly, the advised material models need to be populated with realistic parameters through biaxial mechanical experiments adapted to the dimensions of the bridging vein samples. Finally, updating the existing finite element head models with these parameters will render them truly biofidelic, allowing the establishment of accurate tolerance criteria and, ultimately, better head protection devices.

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Tissue fixation methods are well established for rodents, but not for large animals. We present a simple technique for in situ brain perfusion fixation in a male porcine model, using cervical vessels for inflow and outflow and achieving a closed system. Thirty-four pigs, aged 4.7 ± 0.6 months and weighing 60.7 ± 10.9 kg, were anaesthetised and mechanically ventilated. The ipsilateral common carotid artery and external jugular vein were dissected and constituted the inflow and outflow access, respectively. The brains were perfused and fixed in situ with heparinised saline followed by buffered formaldehyde. Then, specimens (brain, cerebellum and brainstem) were extracted and processed for histology. Fixative fluid leakage was avoided, achieving a closed system. This technique minimises the exposure to toxic chemicals such as formaldehyde and associated hazards (inherent toxicity, eye irritation), thereby increasing operators' safety. Perfusion was performed with a peristaltic pump for 20-30 minutes at an optimum rate of 0.20 l/min and required only 5 litres of the fixative. The specimens were sufficiently hardened to be extracted. High-quality tissues were available for histology analysis. This technique offers a user-friendly closed system for brain perfusion fixation which can be adapted for other tissues of the head, face and neck.

Acute subdural hematoma (ASDH) is one of the most frequent traumatic brain injuries (TBIs) with high mortality rate. Bridging vein (BV) ruptures is a major cause of ASDH. The KTH finite element head model includes bridging veins to predict acute subdural hematoma due to BV rupture. In this model, BVs were positioned according to Oka et al. [10]. The aim of the current study is to investigate whether the location and entry angles of these BVs could be modelled using data from a greater statistical sample, more accurately and what the impact of this improvement would be on the model's predictive capability of BV rupture. From the CT angiogram data of 78 patients, the relative position of the bridging veins and their entry angles along the superior sagittal sinus was determined. The bridging veins were repositioned in the model accordingly. The performance of the model , w.r.t. BV rupture prediction potential was tested on simulations of full body cadaver head impact experiments. The experiments were simulated on the original version of the model and on three other versions which had updated BV positions according to mean, maximum and minimum entry angles. Even though the successful prediction rate between the models stayed the same, the location of the rupture site significantly improved for the model with the mean entry angles. Moreover, the models with maximum and minimum entry angles give an insight of how BV biovariability can influence ASDH. In order to further improve the successful prediction rate, more biofidelic data are needed both with respect to bridging vein material properties and geometry. Furthermore, more experimental data are needed in order to investigate the behaviour of FE head models in depth.