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Bridging veins (BV) rupture is a major cause of Acute Subdural Hematoma. This study aims to quantify their biovariability to better understand their properties and increase the biofidelity of finite element (FE) head models. The number of BV and their measured diameters were manually counted in CT angiograms from 67 patients. A mixed linear model was used for the statistical analysis and the results were implemented in the KTH FE head model. LS-DYNA simulations were used to evaluate the amount of successful BV rupture predictions. The false positive and false negative predictions were also counted. The human brain has a mean of 23,18 BV, with diameters ranging between 0,37 and 3,24 mm. In the initial version of the KTH model two BV mechanical properties datasets gave a 6/8 successful prediction rate with one false positive and one false negative and one dataset gave a 7/8 successful prediction rate with one false negative. For the updated version all sets gave a 7/8 successful prediction rate with one false negative. The number of BV and BV diameter size is segment dependent, but not hemisphere dependent. The implementation of these findings in the FE head model is a good preliminary attempt to increase BV rupture predictability., Not duplicate with DiVA 1686627QC 20221222

Bridging veins (BV) rupture is a major cause of Acute Subdural Hematoma. This study aims to quantify their biovariability to better understand their properties and increase the biofidelity of finite element (FE) head models. The number of BV and their measured diameters were manually counted in CT angiograms from 67 patients. A mixed linear model was used for the statistical analysis and the results were implemented in the KTH FE head model. LS-DYNA simulations were used to evaluate the amount of successful BV rupture predictions. The false positive and false negative predictions were also counted. The human brain has a mean of 23,18 BV, with diameters ranging between 0,37 and 3,24 mm. In the initial version of the KTH model two BV mechanical properties datasets gave a 6/8 successful prediction rate with one false positive and one false negative and one dataset gave a 7/8 successful prediction rate with one false negative. For the updated version all sets gave a 7/8 successful prediction rate with one false negative. The number of BV and BV diameter size is segment dependent, but not hemisphere dependent. The implementation of these findings in the FE head model is a good preliminary attempt to increase BV rupture predictability., QC 20220810