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However, computational models vary in the level of anatomical details, most notably the cortical folds. This study aims to determine the effect of modeling cortical folds on mTBI risk assessment. We compared gyrencephalic (with cortical folds) and lissencephalic (without cortical folds) finite element (FE) head models of 18 subjects aged 9\u201318 years, subjected to a rotational head acceleration of 10 krad\/s\n                    <jats:inline-formula>\n                      <jats:alternatives>\n                        <jats:tex-math>$$^2$$<\/jats:tex-math>\n                        <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                          <mml:mmultiscripts>\n                            <mml:mrow\/>\n                            <mml:mrow\/>\n                            <mml:mn>2<\/mml:mn>\n                          <\/mml:mmultiscripts>\n                        <\/mml:math>\n                      <\/jats:alternatives>\n                    <\/jats:inline-formula>\n                    (10 ms duration) about each principal head axis. We analyzed the effect of cortical folds on different tissue-level mTBI injury metrics, including maximum principal strain (MPS95), maximum principal strain rate (MPSR95), and cumulative strain damage measure (CSDM15). The inclusion of cortical folds consistently yielded higher injury metrics across all individuals and rotational directions, with a bias (mean \u00b1 std. dev. relative to maximum lissencephalic values) of\n                    <jats:inline-formula>\n                      <jats:alternatives>\n                        <jats:tex-math>$$21.7 \\pm 9.1 \\%$$<\/jats:tex-math>\n                        <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                          <mml:mrow>\n                            <mml:mn>21.7<\/mml:mn>\n                            <mml:mo>\u00b1<\/mml:mo>\n                            <mml:mn>9.1<\/mml:mn>\n                            <mml:mo>%<\/mml:mo>\n                          <\/mml:mrow>\n                        <\/mml:math>\n                      <\/jats:alternatives>\n                    <\/jats:inline-formula>\n                    in MPS95,\n                    <jats:inline-formula>\n                      <jats:alternatives>\n                        <jats:tex-math>$$17.1\\pm 7.6\\%$$<\/jats:tex-math>\n                        <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                          <mml:mrow>\n                            <mml:mn>17.1<\/mml:mn>\n                            <mml:mo>\u00b1<\/mml:mo>\n                            <mml:mn>7.6<\/mml:mn>\n                            <mml:mo>%<\/mml:mo>\n                          <\/mml:mrow>\n                        <\/mml:math>\n                      <\/jats:alternatives>\n                    <\/jats:inline-formula>\n                    in MPSR95, and\n                    <jats:inline-formula>\n                      <jats:alternatives>\n                        <jats:tex-math>$$14.4\\pm 11.3\\%$$<\/jats:tex-math>\n                        <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                          <mml:mrow>\n                            <mml:mn>14.4<\/mml:mn>\n                            <mml:mo>\u00b1<\/mml:mo>\n                            <mml:mn>11.3<\/mml:mn>\n                            <mml:mo>%<\/mml:mo>\n                          <\/mml:mrow>\n                        <\/mml:math>\n                      <\/jats:alternatives>\n                    <\/jats:inline-formula>\n                    in CSDM15. Differences in the spatial strain distribution were also found between the models, with the DICE similarity coefficient ranging between\n                    <jats:inline-formula>\n                      <jats:alternatives>\n                        <jats:tex-math>$$0.07-0.43$$<\/jats:tex-math>\n                        <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                          <mml:mrow>\n                            <mml:mn>0.07<\/mml:mn>\n                            <mml:mo>-<\/mml:mo>\n                            <mml:mn>0.43<\/mml:mn>\n                          <\/mml:mrow>\n                        <\/mml:math>\n                      <\/jats:alternatives>\n                    <\/jats:inline-formula>\n                    and\n                    <jats:inline-formula>\n                      <jats:alternatives>\n                        <jats:tex-math>$$0.42-0.70$$<\/jats:tex-math>\n                        <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                          <mml:mrow>\n                            <mml:mn>0.42<\/mml:mn>\n                            <mml:mo>-<\/mml:mo>\n                            <mml:mn>0.70<\/mml:mn>\n                          <\/mml:mrow>\n                        <\/mml:math>\n                      <\/jats:alternatives>\n                    <\/jats:inline-formula>\n                    for the peak MPS and CSDM15, respectively. Increases in peak injury metrics (up to\n                    <jats:inline-formula>\n                      <jats:alternatives>\n                        <jats:tex-math>$$\\sim$$<\/jats:tex-math>\n                        <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                          <mml:mo>\u223c<\/mml:mo>\n                        <\/mml:math>\n                      <\/jats:alternatives>\n                    <\/jats:inline-formula>\n                    50%) were found for brain regions such as the corpus callosum, cerebellum, and brain stem. This study finds that the inclusion of cortical folds significantly alters the pattern of deformation in the brain and results in a prediction of higher mTBI risk.\n                  <\/jats:p>","DOI":"10.1007\/s10237-026-02095-1","type":"journal-article","created":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T17:46:19Z","timestamp":1781891179000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Effect of modeling subject-specific cortical folds on brain injury risk prediction under blunt impact loading"],"prefix":"10.1007","volume":"25","author":[{"given":"Anu","family":"Tripathi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alison","family":"Brooks","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Traci","family":"Snedden","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peter","family":"Ferrazzano","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christian","family":"Franck","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rika Wright","family":"Carlsen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,6,19]]},"reference":[{"issue":"1","key":"2095_CR1","doi-asserted-by":"publisher","first-page":"111","DOI":"10.3171\/jns.2004.100.1.0111","volume":"100","author":"P Aimedieu","year":"2004","unstructured":"Aimedieu P, Grebe R (2004) Tensile strength of cranial pia mater: preliminary results. 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