4.6 Article

Prediction of subdural haematoma based on a detailed numerical model of the cerebral bridging veins

出版社

ELSEVIER
DOI: 10.1016/j.jmbbm.2020.103976

关键词

subdural Haematoma bridging veins; Finite element model; Brain injury; Tubular structure

资金

  1. FCT - Fundacao para a Ciencia e a Tecnologia [UIDB/00481/2020, UIDP/00481/2020]
  2. Centro Portugal Regional Operational Programme (Centro2020), under the PORTUGAL 2020 Partnership Agreement [CENTRO-01-0145-FEDER-022083]
  3. Fundacao para a Ciencia e a Tecnologia (FCT) [CEECIND/01192/2017]
  4. Centro Portugal Regional Operational Programme (Centro2020) through the European Regional Development Fund [CENTRO-01-0145-FEDER-022083]

向作者/读者索取更多资源

Traumatic brain injury is one of the major causes of death and disability in the world. One of the most frequent and deadly injury resulted from a head trauma is acute subdural haematoma (ASDH), which consists on the rupture of a bridging vein (BV). Given the importance of this type of injury, it is necessary to correctly assess thresholds and damage criteria, which is difficult to perform on human cadavers or animals, due to ethical and economical issues. Finite element (FE) models are a very good and cost-effective alternative. Once properly validated, a finite element head model (FEHM) becomes a valuable tool, that can be used in the development of head protective gear as a design tool and in the reconstruction of head traumas by predicting brain injuries under impact conditions. The YEt Another Head Model (YEAHM) is one example of a FE model that can be used to assist/replace the experimental tests. In this study, the bridging veins model from YEAHM was improved and validated by comparing its results with others reported in literature and estimating the success rate. At the end, it was developed a pressurised tubular shaped FE model of BVs, considering the blood pressure in cerebral veins. Results showed a maximum success rate of 90%, which in comparison with other FE models available in the literature, presents an equal or even better ASDH prediction success rate.

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