Rapid Estimation of Entire Brain Strain Using Deep Learning Models

The relationship between brain injury criteria and brain strain across different types of head impacts can be different

“…Although different types of head impacts were combined to develop BIC in previous studies (table 1), it was only until recently that researchers started to investigate the declining performance of the brain strain regression models when applied to a different type of head impact. Zhan et al [20] developed a deep learning head model for predicting brain strain of the entire brain and showed that the model accuracy deteriorates when the model was trained on a dataset mainly comprising simulated head impacts and applied to MMA head impacts. According to the finding in this study, concerns may arise if the BIC is used to estimate the brain strain if the BIC regression model is fitted on a different type of head impact.…”

“…For the type of head impact in which the head kinematics characteristic is unknown, sufficient impact cases should be collected and analysed by an FE model before using the BIC. Furthermore, deep learning head models were recently developed based on football dataset [56] and football, MMA and laboratory impact datasets [20], and these models have achieved promising accuracy. Although different datasets were used in [20], the ability of the model to predict the brain strain in an unknown type of head impact was not examined.…”

“…To evaluate the generalizability of BIC across different types of head impacts, data from six individual sources were used to construct five datasets: (i) dataset 1 contained 2183 laboratory impacts, among which 2130 were simulated by a validated finite-element analysis model of hybrid III anthropomorphic test dummy (ATD) headform impacted by the impactor for football testing [20,24,25]. The remaining 53 were reconstructed head impacts in National Football League [26] using hybrid III ATD headform.…”

“…The peak values of the magnitudes of the linear acceleration at the brain centre of gravity |a(t)| (lin_acc_CG_max) [12], angular velocity |ω(t)| (ang_vel_max) [13] and angular acceleration |α(t)| (ang_acc_max) [13,20] are the most fundamental BIC definitions. They are calculated by taking the maximum of the magnitude of the respective translational or rotational parameters.…”

“…Because the brain can be injured when head movement deforms brain tissue by the inertial force [6][7][8][14][15][16], brain strain, particularly the maximum principal strain (MPS), is a key parameter in evaluating the brain injury risk [3,[17][18][19] and has been widely used as an indicator for mTBI. To evaluate the accuracy of estimating brain injury risks of the BIC, typically, the Pearson correlation between the BIC and the brain strain ( particularly 95% MPS) and the coefficient of determination (R 2 ) of the linear regression of brain strain on the BIC have been used by researchers [6][7][8]20].…”