Xianghao Zhan, Zhou Zhou, Yuzhe Liu, Nicholas J. Cecchi, Marzieh Hajiahamemar, Michael M. Zeineh, Gerald A. Grant, David Camarillo, Svein Kleiven
{"title":"Differences between Two Maximal Principal Strain Rate Calculation Schemes in Traumatic Brain Analysis with in-vivo and in-silico Datasets","authors":"Xianghao Zhan, Zhou Zhou, Yuzhe Liu, Nicholas J. Cecchi, Marzieh Hajiahamemar, Michael M. Zeineh, Gerald A. Grant, David Camarillo, Svein Kleiven","doi":"arxiv-2409.08164","DOIUrl":null,"url":null,"abstract":"Brain deformation caused by a head impact leads to traumatic brain injury\n(TBI). The maximum principal strain (MPS) was used to measure the extent of\nbrain deformation and predict injury, and the recent evidence has indicated\nthat incorporating the maximum principal strain rate (MPSR) and the product of\nMPS and MPSR, denoted as MPSxSR, enhances the accuracy of TBI prediction.\nHowever, ambiguities have arisen about the calculation of MPSR. Two schemes\nhave been utilized: one (MPSR1) is to use the time derivative of MPS, and\nanother (MPSR2) is to use the first eigenvalue of the strain rate tensor. Both\nMPSR1 and MPSR2 have been applied in previous studies to predict TBI. To\nquantify the discrepancies between these two methodologies, we conducted a\ncomparison of these two MPSR methodologies across nine in-vivo and in-silico\nhead impact datasets and found that 95MPSR1 was 5.87% larger than 95MPSR2, and\n95MPSxSR1 was 2.55% larger than 95MPSxSR2. Across every element in all head\nimpacts, MPSR1 was 8.28% smaller than MPSR2, and MPSxSR1 was 8.11% smaller than\nMPSxSR2. Furthermore, logistic regression models were trained to predict TBI\nbased on the MPSR (or MPSxSR), and no significant difference was observed in\nthe predictability across different variables. The consequence of misuse of\nMPSR and MPSxSR thresholds (i.e. compare threshold of 95MPSR1 with value from\n95MPSR2 to determine if the impact is injurious) was investigated, and the\nresulting false rates were found to be around 1%. The evidence suggested that\nthese two methodologies were not significantly different in detecting TBI.","PeriodicalId":501034,"journal":{"name":"arXiv - EE - Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - EE - Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.08164","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Brain deformation caused by a head impact leads to traumatic brain injury
(TBI). The maximum principal strain (MPS) was used to measure the extent of
brain deformation and predict injury, and the recent evidence has indicated
that incorporating the maximum principal strain rate (MPSR) and the product of
MPS and MPSR, denoted as MPSxSR, enhances the accuracy of TBI prediction.
However, ambiguities have arisen about the calculation of MPSR. Two schemes
have been utilized: one (MPSR1) is to use the time derivative of MPS, and
another (MPSR2) is to use the first eigenvalue of the strain rate tensor. Both
MPSR1 and MPSR2 have been applied in previous studies to predict TBI. To
quantify the discrepancies between these two methodologies, we conducted a
comparison of these two MPSR methodologies across nine in-vivo and in-silico
head impact datasets and found that 95MPSR1 was 5.87% larger than 95MPSR2, and
95MPSxSR1 was 2.55% larger than 95MPSxSR2. Across every element in all head
impacts, MPSR1 was 8.28% smaller than MPSR2, and MPSxSR1 was 8.11% smaller than
MPSxSR2. Furthermore, logistic regression models were trained to predict TBI
based on the MPSR (or MPSxSR), and no significant difference was observed in
the predictability across different variables. The consequence of misuse of
MPSR and MPSxSR thresholds (i.e. compare threshold of 95MPSR1 with value from
95MPSR2 to determine if the impact is injurious) was investigated, and the
resulting false rates were found to be around 1%. The evidence suggested that
these two methodologies were not significantly different in detecting TBI.