{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T10:40:20Z","timestamp":1777891220383,"version":"3.51.4"},"reference-count":62,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2022,7,12]],"date-time":"2022-07-12T00:00:00Z","timestamp":1657584000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,7,12]],"date-time":"2022-07-12T00:00:00Z","timestamp":1657584000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100006346","name":"Faculty of Medical and Health Sciences, University of Auckland","doi-asserted-by":"publisher","award":["3716749"],"award-info":[{"award-number":["3716749"]}],"id":[{"id":"10.13039\/501100006346","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001537","name":"University of Auckland","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100001537","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Engineering with Computers"],"published-print":{"date-parts":[[2022,10]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Traumatic brain injury (TBI) is a leading cause of death and disability. The way mechanical impact is transferred to the brain has been shown to be a major determinant for structural damage and subsequent pathological sequalae. Although finite element (FE) models have been used extensively in the investigation of various aspects of TBI and have been instrumental in characterising a TBI injury threshold and the pattern of diffuse axonal injuries, subject-specific analysis has been difficult to perform due to the complexity of brain structures and its material properties. We have developed an efficient computational pipeline that can generate subject-specific FE models of the brain made up of conforming hexahedral elements directly from advanced MRI scans. This pipeline was applied and validated in our sheep model of TBI. Our FE model of the sheep brain accurately predicted the damage pattern seen on post-impact MRI scans. Furthermore, our model also showed a complex time-varying strain distribution pattern, which was not present in the homogeneous model without subject-specific material descriptions. To our knowledge, this is the first fully subject-specific FE model of the sheep brain able to predict structural damage after a head impact. The pipeline developed has the potential to augment the analysis of human brain MRI scans to detect changes in brain structures and function after TBI.<\/jats:p>","DOI":"10.1007\/s00366-022-01697-4","type":"journal-article","created":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T15:04:09Z","timestamp":1657724649000},"page":"3925-3937","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Combining advanced magnetic resonance imaging (MRI) with finite element (FE) analysis for characterising subject-specific injury patterns in the brain after traumatic brain injury"],"prefix":"10.1007","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1680-4287","authenticated-orcid":false,"given":"Vickie","family":"Shim","sequence":"first","affiliation":[]},{"given":"Maryam","family":"Tayebi","sequence":"additional","affiliation":[]},{"given":"Eryn","family":"Kwon","sequence":"additional","affiliation":[]},{"given":"Sarah-Jane","family":"Guild","sequence":"additional","affiliation":[]},{"given":"Miriam","family":"Scadeng","sequence":"additional","affiliation":[]},{"given":"David","family":"Dubowitz","sequence":"additional","affiliation":[]},{"given":"Fiona","family":"McBryde","sequence":"additional","affiliation":[]},{"given":"Samuel","family":"Rosset","sequence":"additional","affiliation":[]},{"given":"Alan","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Justin","family":"Fernandez","sequence":"additional","affiliation":[]},{"given":"Shaofan","family":"Li","sequence":"additional","affiliation":[]},{"given":"Samantha","family":"Holdsworth","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,7,12]]},"reference":[{"issue":"11","key":"1697_CR1","doi-asserted-by":"publisher","first-page":"1637","DOI":"10.1016\/j.apmr.2010.05.017","volume":"91","author":"DK Menon","year":"2010","unstructured":"Menon DK, Schwab K, Wright DW, Maas AI (2010) Position statement: definition of traumatic brain injury. Arch Phys Med Rehabilit 91(11):1637\u20131640. https:\/\/doi.org\/10.1016\/j.apmr.2010.05.017","journal-title":"Arch Phys Med Rehabilit"},{"issue":"4","key":"1697_CR2","doi-asserted-by":"publisher","first-page":"331","DOI":"10.1016\/S1474-4422(10)70069-7","volume":"9","author":"N. The Lancet","year":"2010","unstructured":"N. The Lancet (2010) Traumatic brain injury: time to end the silence,\". Lancet Neurol 9(4):331. https:\/\/doi.org\/10.1016\/S1474-4422(10)70069-7","journal-title":"Lancet Neurol"},{"key":"1697_CR3","doi-asserted-by":"publisher","DOI":"10.1080\/16501960410023877","author":"LJ Carroll","year":"2004","unstructured":"Carroll LJ, Cassidy JD, Holm L, Kraus J, Coronado VG, W. H. O. C. C. T. F. o. M. T. B. Injury (2004) Methodological issues and research recommendations for mild traumatic brain injury: the WHO Collaborating Centre Task Force on Mild Traumatic Brain Injury. J Rehabil Med. https:\/\/doi.org\/10.1080\/16501960410023877","journal-title":"J Rehabil Med"},{"key":"1697_CR4","volume-title":"Oxford textbook of neurologic and neuropsychiatric epidemiology","author":"A Theadom","year":"2020","unstructured":"Theadom A, Jones K (2020) Traumatic brain and spinal cord injury. In: Brayne C, Feign V, Launer L, Logroscino G (eds) Oxford textbook of neurologic and neuropsychiatric epidemiology. Oxford University Press, Oxford"},{"issue":"8","key":"1697_CR5","doi-asserted-by":"publisher","first-page":"1511","DOI":"10.1089\/neu.2016.4677","volume":"34","author":"C Hiploylee","year":"2016","unstructured":"Hiploylee C et al (2016) Longitudinal study of postconcussion syndrome: not everyone recovers. J Neurotrauma 34(8):1511\u20131523. https:\/\/doi.org\/10.1089\/neu.2016.4677","journal-title":"J Neurotrauma"},{"issue":"5","key":"1697_CR6","doi-asserted-by":"publisher","first-page":"543","DOI":"10.1016\/S1474-4422(10)70065-X","volume":"9","author":"HF Lingsma","year":"2010","unstructured":"Lingsma HF, Roozenbeek B, Steyerberg EW, Murray GD, Maas AIR (2010) Early prognosis in traumatic brain injury: from prophecies to predictions. Lancet Neurol 9(5):543\u2013554. https:\/\/doi.org\/10.1016\/S1474-4422(10)70065-X","journal-title":"Lancet Neurol"},{"issue":"Pt 2","key":"1697_CR7","doi-asserted-by":"publisher","first-page":"333","DOI":"10.1093\/brain\/aww317","volume":"140","author":"M Ghajari","year":"2017","unstructured":"Ghajari M, Hellyer PJ, Sharp DJ (2017) Computational modelling of traumatic brain injury predicts the location of chronic traumatic encephalopathy pathology. Brain 140(Pt 2):333\u2013343. https:\/\/doi.org\/10.1093\/brain\/aww317","journal-title":"Brain"},{"issue":"2","key":"1697_CR8","doi-asserted-by":"publisher","first-page":"422","DOI":"10.1093\/brain\/awx350","volume":"141","author":"CA Tagge","year":"2018","unstructured":"Tagge CA et al (2018) Concussion, microvascular injury, and early tauopathy in young athletes after impact head injury and an impact concussion mouse model. Brain 141(2):422\u2013458. https:\/\/doi.org\/10.1093\/brain\/awx350","journal-title":"Brain"},{"issue":"9","key":"1697_CR9","doi-asserted-by":"publisher","first-page":"557","DOI":"10.1016\/0020-7403(72)90056-2","volume":"14","author":"VH Kenner","year":"1972","unstructured":"Kenner VH, Goldsmith W (1972) Dynamic loading of a fluid-filled spherical shell. Int J Mech Sci 14(9):557\u2013568. https:\/\/doi.org\/10.1016\/0020-7403(72)90056-2","journal-title":"Int J Mech Sci"},{"issue":"2","key":"1697_CR10","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1016\/0021-9290(77)90075-6","volume":"10","author":"TB Khalil","year":"1977","unstructured":"Khalil TB, Hubbard RP (1977) Parametric study of head response by finite element modeling. J Biomech 10(2):119\u2013132. https:\/\/doi.org\/10.1016\/0021-9290(77)90075-6","journal-title":"J Biomech"},{"key":"1697_CR11","doi-asserted-by":"crossref","unstructured":"Nahum AM (1977) Intracranial pressure dynamics during head impact. In: Proceedings of Stapp Car Crash Conference. https:\/\/ci.nii.ac.jp\/naid\/80015010321\/en\/.","DOI":"10.4271\/770922"},{"key":"1697_CR12","first-page":"337","volume":"45","author":"WN Hardy","year":"2001","unstructured":"Hardy WN, Foster CD, Mason MJ, Yang KH, King AI, Tashman S (2001) Investigation of head injury mechanisms using neutral density technology and high-speed biplanar X-ray. Stapp Car Crash J 45:337\u2013368","journal-title":"Stapp Car Crash J"},{"key":"1697_CR13","doi-asserted-by":"publisher","DOI":"10.1115\/1.4025101","author":"H Mao","year":"2013","unstructured":"Mao H et al (2013) Development of a finite element human head model partially validated with thirty five experimental cases. J Biomech Eng. https:\/\/doi.org\/10.1115\/1.4025101","journal-title":"J Biomech Eng"},{"issue":"1","key":"1697_CR14","first-page":"81","volume":"51","author":"S Kleiven","year":"2007","unstructured":"Kleiven S (2007) Predictors for traumatic brain injuries evaluated through accident reconstructions. Stapp Car Crash J 51(1):81\u2013114","journal-title":"Stapp Car Crash J"},{"issue":"2","key":"1697_CR15","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1016\/S0021-9290(01)00202-0","volume":"35","author":"S Kleiven","year":"2002","unstructured":"Kleiven S, von Holst H (2002) Consequences of head size following trauma to the human head. J Biomech 35(2):153\u2013160. https:\/\/doi.org\/10.1016\/S0021-9290(01)00202-0","journal-title":"J Biomech"},{"issue":"10","key":"1697_CR16","doi-asserted-by":"publisher","first-page":"2814","DOI":"10.1007\/s10439-021-02853-5","volume":"49","author":"NJ Cecchi","year":"2021","unstructured":"Cecchi NJ et al (2021) Identifying factors associated with head impact kinematics and brain strain in high school american football via instrumented mouthguards. Ann Biomed Eng 49(10):2814\u20132826. https:\/\/doi.org\/10.1007\/s10439-021-02853-5","journal-title":"Ann Biomed Eng"},{"issue":"1","key":"1697_CR17","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1007\/s10237-012-0387-6","volume":"12","author":"RJH Cloots","year":"2012","unstructured":"Cloots RJH, Dommelen JAWV, Kleiven S, Geers MGD (2012) Multi-scale mechanics of traumatic brain injury: predicting axonal strains from head loads. Biomech Model Mechanobiol 12(1):137\u2013150. https:\/\/doi.org\/10.1007\/s10237-012-0387-6 (in English)","journal-title":"Biomech Model Mechanobiol"},{"issue":"12","key":"1697_CR18","doi-asserted-by":"publisher","first-page":"1730","DOI":"10.1089\/neu.2020.7412","volume":"38","author":"Z Zhou","year":"2021","unstructured":"Zhou Z et al (2021) White matter tract-oriented deformation is dependent on real-time axonal fiber orientation. J Neurotrauma 38(12):1730\u20131745. https:\/\/doi.org\/10.1089\/neu.2020.7412","journal-title":"J Neurotrauma"},{"issue":"7","key":"1697_CR19","doi-asserted-by":"publisher","first-page":"441","DOI":"10.1089\/neu.2013.3268","volume":"32","author":"S Ji","year":"2014","unstructured":"Ji S et al (2014) Group-wise evaluation and comparison of white matter fiber strain and maximum principal strain in sports-related concussion. J Neurotrauma 32(7):441\u2013454. https:\/\/doi.org\/10.1089\/neu.2013.3268","journal-title":"J Neurotrauma"},{"issue":"5","key":"1697_CR20","doi-asserted-by":"publisher","first-page":"1121","DOI":"10.1007\/s10237-014-0562-z","volume":"13","author":"S Ji","year":"2014","unstructured":"Ji S, Zhao W, Li Z, McAllister TW (2014) Head impact accelerations for brain strain-related responses in contact sports: a model-based investigation. Biomech Model Mechanobiol 13(5):1121\u20131136. https:\/\/doi.org\/10.1007\/s10237-014-0562-z","journal-title":"Biomech Model Mechanobiol"},{"issue":"3","key":"1697_CR21","doi-asserted-by":"publisher","first-page":"927","DOI":"10.1007\/s10237-019-01261-y","volume":"19","author":"S Wu","year":"2020","unstructured":"Wu S, Zhao W, Rowson B, Rowson S, Ji S (2020) A network-based response\u00a0feature matrix as a brain injury metric. Biomech Model Mechanobiol 19(3):927\u2013942. https:\/\/doi.org\/10.1007\/s10237-019-01261-y","journal-title":"Biomech Model Mechanobiol"},{"key":"1697_CR22","doi-asserted-by":"publisher","first-page":"4967","DOI":"10.1016\/j.jmbbm.2021.104967","volume":"126","author":"W Zhao","year":"2022","unstructured":"Zhao W, Ji S (2022) \"Cerebral vascular strains in dynamic head impact using an upgraded model with brain material property heterogeneity. J Mech Behav Biomed Mater 126:4967. https:\/\/doi.org\/10.1016\/j.jmbbm.2021.104967","journal-title":"J Mech Behav Biomed Mater"},{"key":"1697_CR23","doi-asserted-by":"publisher","first-page":"179457","DOI":"10.1109\/ACCESS.2020.3026350","volume":"8","author":"VB Shim","year":"2020","unstructured":"Shim VB et al (2020) Rapid prediction of brain injury pattern in mTBI by combining FE analysis with a machine-learning based approach. IEEE Access 8:179457\u2013179465. https:\/\/doi.org\/10.1109\/ACCESS.2020.3026350","journal-title":"IEEE Access"},{"issue":"7","key":"1697_CR24","doi-asserted-by":"publisher","first-page":"879","DOI":"10.3109\/02699052.2014.888478","volume":"28","author":"PA Taylor","year":"2014","unstructured":"Taylor PA, Ludwigsen JS, Ford CC (2014) Investigation of blast-induced traumatic brain injury. Brain Inj 28(7):879\u2013895. https:\/\/doi.org\/10.3109\/02699052.2014.888478","journal-title":"Brain Inj"},{"issue":"3","key":"1697_CR25","doi-asserted-by":"publisher","first-page":"1109","DOI":"10.1007\/s10237-019-01273-8PMID-31811417","volume":"19","author":"M Hajiaghamemar","year":"2020","unstructured":"Hajiaghamemar M, Wu T, Panzer MB, Margulies SS (2020) Embedded axonal fiber tracts improve finite element model predictions of traumatic brain injury. Biomech Model Mechanobiol 19(3):1109\u20131130. https:\/\/doi.org\/10.1007\/s10237-019-01273-8PMID-31811417","journal-title":"Biomech Model Mechanobiol"},{"issue":"1","key":"1697_CR26","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1093\/brain\/awaa336PMID-33454735","volume":"144","author":"CK Donat","year":"2021","unstructured":"Donat CK et al (2021) From biomechanics to pathology: predicting axonal injury from patterns of strain after traumatic brain injury. Brain 144(1):70\u201391. https:\/\/doi.org\/10.1093\/brain\/awaa336PMID-33454735","journal-title":"Brain"},{"key":"1697_CR27","doi-asserted-by":"publisher","DOI":"10.1115\/1.4000956","author":"NG Ibrahim","year":"2010","unstructured":"Ibrahim NG et al (2010) In situ deformations in the immature brain during rapid rotations. J Biomech Eng. https:\/\/doi.org\/10.1115\/1.4000956","journal-title":"J Biomech Eng"},{"issue":"4","key":"1697_CR28","doi-asserted-by":"publisher","first-page":"877","DOI":"10.1007\/s10237-014-0643-z","volume":"14","author":"S Sullivan","year":"2015","unstructured":"Sullivan S et al (2015) White matter tract-oriented deformation predicts traumatic axonal brain injury and reveals rotational direction-specific vulnerabilities. Biomech Model Mechanobiol 14(4):877\u2013896. https:\/\/doi.org\/10.1007\/s10237-014-0643-z","journal-title":"Biomech Model Mechanobiol"},{"issue":"8","key":"1697_CR29","doi-asserted-by":"publisher","first-page":"1023","DOI":"10.1089\/neu.2020.7281","volume":"38","author":"K Ghazi","year":"2020","unstructured":"Ghazi K, Wu S, Zhao W, Ji S (2020) Instantaneous whole-brain strain estimation in dynamic head impact. J Neurotrauma 38(8):1023\u20131035. https:\/\/doi.org\/10.1089\/neu.2020.7281","journal-title":"J Neurotrauma"},{"issue":"7","key":"1697_CR30","doi-asserted-by":"publisher","first-page":"441","DOI":"10.1089\/neu.2013.3268","volume":"32","author":"S Ji","year":"2015","unstructured":"Ji S et al (2015) Group-wise evaluation and comparison of white matter fiber strain and maximum principal strain in sports-related concussion. J Neurotrauma 32(7):441\u2013454. https:\/\/doi.org\/10.1089\/neu.2013.3268 (in English)","journal-title":"J Neurotrauma"},{"issue":"4","key":"1697_CR31","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10237-020-01391-8","volume":"100","author":"X Li","year":"2020","unstructured":"Li X, Zhou Z, Kleiven S (2020) \"An anatomically detailed and personalizable head injury model: significance of brain and white matter tract morphological variability on strain. Biomech Model Mechanobiol 100(4):1\u201329. https:\/\/doi.org\/10.1007\/s10237-020-01391-8 (in English)","journal-title":"Biomech Model Mechanobiol"},{"issue":"9","key":"1697_CR32","doi-asserted-by":"publisher","first-page":"1908","DOI":"10.1007\/s10439-019-02239-8","volume":"47","author":"T Wu","year":"2019","unstructured":"Wu T, Alshareef A, Giudice JS, Panzer MB (2019) Explicit modeling of white matter axonal fiber tracts in a finite element brain model. Ann Biomed Eng 47(9):1908\u20131922. https:\/\/doi.org\/10.1007\/s10439-019-02239-8","journal-title":"Ann Biomed Eng"},{"issue":"22","key":"1697_CR33","doi-asserted-by":"publisher","first-page":"1693","DOI":"10.1089\/neu.2013.3306","volume":"32","author":"F Amyot","year":"2015","unstructured":"Amyot F et al (2015) A review of the effectiveness of neuroimaging modalities for the detection of traumatic brain injury. J Neurotrauma 32(22):1693\u20131721. https:\/\/doi.org\/10.1089\/neu.2013.3306","journal-title":"J Neurotrauma"},{"issue":"4","key":"1697_CR34","doi-asserted-by":"publisher","first-page":"4056","DOI":"10.1002\/nbm.4056","volume":"32","author":"SJ Holdsworth","year":"2019","unstructured":"Holdsworth SJ, O\u2019Halloran R, Setsompop K (2019) The quest for high spatial resolution diffusion-weighted imaging of the human brain in vivo. NMR Biomed 32(4):4056. https:\/\/doi.org\/10.1002\/nbm.4056","journal-title":"NMR Biomed"},{"issue":"6","key":"1697_CR35","doi-asserted-by":"publisher","first-page":"621","DOI":"10.1080\/02699052.2021.1895313","volume":"35","author":"M Tayebi","year":"2021","unstructured":"Tayebi M et al (2021) The role of diffusion tensor imaging in characterizing injury patterns on athletes with concussion and subconcussive injury: a systematic review. Brain Inj 35(6):621\u2013644. https:\/\/doi.org\/10.1080\/02699052.2021.1895313","journal-title":"Brain Inj"},{"issue":"5","key":"1697_CR36","doi-asserted-by":"publisher","first-page":"e12332","DOI":"10.1002\/eng2.12332","volume":"3","author":"E Kwon","year":"2021","unstructured":"Kwon E et al (2021) Analyzing the changes in the brain material properties after a mild traumatic brain injury: a pilot study. Eng Rep 3(5):e12332. https:\/\/doi.org\/10.1002\/eng2.12332","journal-title":"Eng Rep"},{"issue":"3","key":"1697_CR37","doi-asserted-by":"publisher","first-page":"410","DOI":"10.1602\/neurorx.2.3.410","volume":"2","author":"I Cernak","year":"2005","unstructured":"Cernak I (2005) Animal models of head trauma. NeuroRx 2(3):410\u2013422. https:\/\/doi.org\/10.1602\/neurorx.2.3.410","journal-title":"NeuroRx"},{"issue":"9","key":"1697_CR38","doi-asserted-by":"publisher","first-page":"505","DOI":"10.1089\/neu.1996.13.505","volume":"13","author":"SB Lewis","year":"1996","unstructured":"Lewis SB et al (1996) A head impact model of early axonal injury in the sheep. J Neurotrauma 13(9):505\u2013514. https:\/\/doi.org\/10.1089\/neu.1996.13.505","journal-title":"J Neurotrauma"},{"key":"1697_CR39","doi-asserted-by":"publisher","DOI":"10.1201\/b19466","volume-title":"Geometric modelling and mesh generation from scanned images","author":"YJ Zhang","year":"2016","unstructured":"Zhang YJ (2016) Geometric modelling and mesh generation from scanned images, 1st edn. Chapman and Hall\/CRC, New York","edition":"1"},{"issue":"3","key":"1697_CR40","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1002\/hbm.10062","volume":"17","author":"SM Smith","year":"2002","unstructured":"Smith SM (2002) Fast robust automated brain extraction. Hum Brain Mapp 17(3):143\u2013155. https:\/\/doi.org\/10.1002\/hbm.10062 (in English)","journal-title":"Hum Brain Mapp"},{"issue":"1","key":"1697_CR41","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1109\/42.906424","volume":"20","author":"Y Zhang","year":"2001","unstructured":"Zhang Y, Brady M, Smith S (2001) Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE Trans Med Imaging 20(1):45\u201357. https:\/\/doi.org\/10.1109\/42.906424","journal-title":"IEEE Trans Med Imaging"},{"issue":"1","key":"1697_CR42","first-page":"13","volume":"4","author":"K Kazemi","year":"2014","unstructured":"Kazemi K, Noorizadeh N (2014) Quantitative comparison of SPM, FSL, and brainsuite for brain MR image segmentation. J Biomed Phys Eng 4(1):13\u201326 (in English)","journal-title":"J Biomed Phys Eng"},{"key":"1697_CR43","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1007\/978-3-319-58845-2_3","volume":"578","author":"J Fernandez","year":"2017","unstructured":"Fernandez J et al (2017) Musculoskeletal modelling and the physiome project. Multiscale Mechanobiol Bone Remodel Adapt 578:123","journal-title":"Multiscale Mechanobiol Bone Remodel Adapt"},{"issue":"15","key":"1697_CR44","doi-asserted-by":"publisher","first-page":"3598","DOI":"10.1016\/j.jbiomech.2014.10.001","volume":"47","author":"VB Shim","year":"2014","unstructured":"Shim VB et al (2014) Subject-specific finite element analysis to characterize the influence of geometry and material properties in Achilles tendon rupture. J Biomech 47(15):3598\u20133604. https:\/\/doi.org\/10.1016\/j.jbiomech.2014.10.001","journal-title":"J Biomech"},{"issue":"1","key":"1697_CR45","doi-asserted-by":"publisher","first-page":"1356","DOI":"10.1038\/s41598-018-31587-z","volume":"8","author":"VB Shim","year":"2018","unstructured":"Shim VB, Handsfield GG, Fernandez JW, Lloyd DG, Besier TF (2018) Combining in silico and in vitro experiments to characterize the role of fascicle twist in the Achilles tendon. Sci Rep 8(1):1356. https:\/\/doi.org\/10.1038\/s41598-018-31587-z","journal-title":"Sci Rep"},{"issue":"11","key":"1697_CR46","doi-asserted-by":"publisher","first-page":"1455","DOI":"10.1302\/0301-620X.100B11.BJJ-2018-0092.R2","volume":"100","author":"JT Munro","year":"2018","unstructured":"Munro JT, Millar JS, Fernandez JW, Walker CG, Howie DW, Shim VB (2018) Risk analysis of patients with an osteolytic acetabular defect after total hip arthroplasty using subject-specific finite-element modelling. Bone Jt J 100(11):1455\u20131462. https:\/\/doi.org\/10.1302\/0301-620X.100B11.BJJ-2018-0092.R2","journal-title":"Bone Jt J"},{"issue":"2","key":"1697_CR47","doi-asserted-by":"publisher","first-page":"333","DOI":"10.1093\/brain\/aww317","volume":"140","author":"M Ghajari","year":"2017","unstructured":"Ghajari M, Hellyer PJ, Sharp DJ (2017) \"Computational modelling of traumatic brain injury predicts the location of chronic traumatic encephalopathy pathology. Brain 140(2):333\u2013343. https:\/\/doi.org\/10.1093\/brain\/aww317 (in English)","journal-title":"Brain"},{"issue":"6","key":"1697_CR48","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1098\/rsif.2005.0073","volume":"3","author":"TC Gasser","year":"2006","unstructured":"Gasser TC, Ogden RW, Holzapfel GA (2006) Hyperelastic modelling of arterial layers with distributed collagen fibre orientations. J R Soc Interface 3(6):15\u201335. https:\/\/doi.org\/10.1098\/rsif.2005.0073","journal-title":"J R Soc Interface"},{"issue":"13","key":"1697_CR49","doi-asserted-by":"publisher","first-page":"2154","DOI":"10.1089\/neu.2016.4744","volume":"34","author":"S Ganpule","year":"2017","unstructured":"Ganpule S et al (2017) A three-dimensional computational human head model that captures live human brain dynamics. J Neurotrauma 34(13):2154\u20132166. https:\/\/doi.org\/10.1089\/neu.2016.4744","journal-title":"J Neurotrauma"},{"issue":"91","key":"1697_CR50","doi-asserted-by":"publisher","first-page":"20130914","DOI":"10.1098\/rsif.2013.0914PMID-24258158","volume":"11","author":"C Giordano","year":"2014","unstructured":"Giordano C, Kleiven S (2014) Connecting fractional anisotropy from medical images with mechanical anisotropy of a hyperviscoelastic fibre-reinforced constitutive model for brain tissue. J R Soc Interface 11(91):20130914. https:\/\/doi.org\/10.1098\/rsif.2013.0914PMID-24258158","journal-title":"J R Soc Interface"},{"issue":"2","key":"1697_CR51","doi-asserted-by":"publisher","first-page":"250","DOI":"10.1089\/neu.2018.5634PMID-29681212","volume":"36","author":"W Zhao","year":"2019","unstructured":"Zhao W, Ji S (2019) White matter anisotropy for impact simulation and response sampling in traumatic brain injury. J Neurotrauma 36(2):250\u2013263. https:\/\/doi.org\/10.1089\/neu.2018.5634PMID-29681212","journal-title":"J Neurotrauma"},{"issue":"5","key":"1697_CR52","doi-asserted-by":"publisher","first-page":"1052","DOI":"10.1016\/j.jbiomech.2013.12.036","volume":"47","author":"C Giordano","year":"2014","unstructured":"Giordano C, Cloots RJH, Dommelen JAWV, Kleiven S (2014) The influence of anisotropy on brain injury prediction. J Biomech 47(5):1052\u20131059. https:\/\/doi.org\/10.1016\/j.jbiomech.2013.12.036 (in English)","journal-title":"J Biomech"},{"issue":"14","key":"1697_CR53","doi-asserted-by":"publisher","first-page":"1495","DOI":"10.1080\/10255842.2014.920831","volume":"18","author":"VB Shim","year":"2015","unstructured":"Shim VB, Battley M, Anderson IA, Munro JT (2015) Validation of an efficient method of assigning material properties in finite element analysis of pelvic bone. Comput Methods Biomech Biomed Eng 18(14):1495\u20131499. https:\/\/doi.org\/10.1080\/10255842.2014.920831","journal-title":"Comput Methods Biomech Biomed Eng"},{"issue":"3","key":"1697_CR54","first-page":"279","volume":"98","author":"V Shim","year":"2014","unstructured":"Shim V, Mithraratne K (2014) Activation pattern of nuclear factor-kb in skin after mechanical stretch\u2013a multiscale modeling approach. Comput Model Eng Sci 98(3):279\u2013294","journal-title":"Comput Model Eng Sci"},{"issue":"1","key":"1697_CR55","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1007\/s10237-015-0668-y","volume":"15","author":"VB Shim","year":"2016","unstructured":"Shim VB, Besier TF, Lloyd DG, Mithraratne K, Fernandez JF (2016) The influence and biomechanical role of cartilage split line pattern on tibiofemoral cartilage stress distribution during the stance phase of gait. Biomech Model Mechanobiol 15(1):195\u2013204. https:\/\/doi.org\/10.1007\/s10237-015-0668-y","journal-title":"Biomech Model Mechanobiol"},{"issue":"3","key":"1697_CR56","doi-asserted-by":"publisher","first-page":"1116","DOI":"10.1016\/j.neuroimage.2006.01.015","volume":"31","author":"PA Yushkevich","year":"2006","unstructured":"Yushkevich PA et al (2006) User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. Neuroimage 31(3):1116\u20131128. https:\/\/doi.org\/10.1016\/j.neuroimage.2006.01.015","journal-title":"Neuroimage"},{"issue":"3","key":"1697_CR57","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1007\/s10237-003-0036-1","volume":"2","author":"JW Fernandez","year":"2004","unstructured":"Fernandez JW, Mithraratne P, Thrupp SF, Tawhai MH, Hunter PJ (2004) Anatomically based geometric modelling of the musculo-skeletal system and other organs. Biomech Model Mechanobiol 2(3):139\u2013155. https:\/\/doi.org\/10.1007\/s10237-003-0036-1","journal-title":"Biomech Model Mechanobiol"},{"issue":"3","key":"1697_CR58","doi-asserted-by":"publisher","first-page":"237","DOI":"10.1038\/nrm1054","volume":"4","author":"PJ Hunter","year":"2003","unstructured":"Hunter PJ, Borg TK (2003) Integration from proteins to organs: the Physiome Project. Nat Rev Mol Cell Biol 4(3):237\u2013243. https:\/\/doi.org\/10.1038\/nrm1054","journal-title":"Nat Rev Mol Cell Biol"},{"issue":"11","key":"1697_CR59","doi-asserted-by":"publisher","first-page":"2389","DOI":"10.1113\/jphysiol.2014.273235","volume":"592","author":"PJ Hunter","year":"2014","unstructured":"Hunter PJ, de Bono B (2014) Biophysical constraints on the evolution of tissue structure and function. J Physiol 592(11):2389\u20132401. https:\/\/doi.org\/10.1113\/jphysiol.2014.273235","journal-title":"J Physiol"},{"key":"1697_CR60","volume-title":"Musculoskeletal atlas project: statistical model-based model generation","author":"J Zhang","year":"2015","unstructured":"Zhang J, Sorby H, Besier T (2015) Musculoskeletal atlas project: statistical model-based model generation. PMHA, New Cumberland"},{"issue":"2","key":"1697_CR61","doi-asserted-by":"publisher","first-page":"R165","DOI":"10.1152\/ajpregu.00163.2017","volume":"315","author":"AJ Sorby-Adams","year":"2018","unstructured":"Sorby-Adams AJ, Vink R, Turner RJ (2018) Large animal models of stroke and traumatic brain injury as translational tools. Am J Physiol-Regul Integr Comp Physiol 315(2):R165\u2013R190. https:\/\/doi.org\/10.1152\/ajpregu.00163.2017","journal-title":"Am J Physiol-Regul Integr Comp Physiol"},{"issue":"5","key":"1697_CR62","doi-asserted-by":"publisher","first-page":"405","DOI":"10.1016\/j.cma.2009.06.007","volume":"199","author":"Y Zhang","year":"2010","unstructured":"Zhang Y, Hughes TJR, Bajaj CL (2010) An automatic 3D mesh generation method for domains with multiple materials. Comput Methods Appl Mech Eng 199(5):405\u2013415. https:\/\/doi.org\/10.1016\/j.cma.2009.06.007","journal-title":"Comput Methods Appl Mech Eng"}],"container-title":["Engineering with Computers"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00366-022-01697-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00366-022-01697-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00366-022-01697-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,12]],"date-time":"2022-11-12T12:10:59Z","timestamp":1668255059000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00366-022-01697-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,12]]},"references-count":62,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2022,10]]}},"alternative-id":["1697"],"URL":"https:\/\/doi.org\/10.1007\/s00366-022-01697-4","relation":{},"ISSN":["0177-0667","1435-5663"],"issn-type":[{"value":"0177-0667","type":"print"},{"value":"1435-5663","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,7,12]]},"assertion":[{"value":"24 March 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 June 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 July 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"All authors declare that they have no conflicts of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}