Atlas of Acceleration-Induced Brain Deformation from Measurements In Vivo
- 348 Downloads
In traumatic brain injury (TBI), rapid head acceleration resulting from a blow or fall results in detrimental brain tissue deformation. These types of injuries are frequent and can have devastating effects. Understanding the relationship between acceleration and deformation is a challenging and essential step towards designing effective preventive strategies. This study describes patterns of acceleration-induced brain deformation in a group of human volunteers (n = 7). Unlike previous research, the analysis herein involved spatiotemporal analysis of 3D kinematics. In each subject, tagged magnetic resonance imaging (MRI) was acquired during a mild acceleration event, and displacements were extracted using a mechanically regularized motion estimation algorithm. This technique involved registering an anatomical template (a finite-element mesh) to all of the subjects allowing translation of scalar strain projections back to the template to be averaged. Our results show that, in individuals, weighting acceleration measurements by the subject’s brain volume improves the correlation between acceleration magnitude and deformation (R2 of 0.66 in the weighted comparison, compared to 0.34). In individuals, and the group, brain deformation peaked after the peak acceleration, and near the interface between the brain and the skull. However, some deformation was also observed near medial brain structures, which supports the idea that the falx plays a role in transferring mechanical power to the middle of the brain.
KeywordsMagnetic resonance Finite strain Brain Atlas TBI Statistical analysis
This research was funded by NIH Grant R01-NS055951, supplement PA12-149, and support by the Center for Neuroscience and Regenerative Medicine.
- 11.Gomez AD, Xing F, Chan D, Pham D, Prince J (2017) Motion estimation with finite-element biomechanical models and tracking constraints from tagged MRI. In: Wittek A, Joldes G, Nielsen PMF, Doyle BJ, Miller K (eds) Computational biomechanics for medicine. Springer, Cham, pp 81–90CrossRefGoogle Scholar
- 14.Kroon D-J (2011) Segmentation of the mandibular canal in cone-beam CT data. Doctoral Dissertation, University of Twente, Enschede, Netherlands. isbn:978-90-365-3280-8Google Scholar
- 15.Tobon-Gomez C, De Craene M, McLeod K, Tautz L, Shi W, Hennemuth A, Prakosa A, Wang H, Carr-White G, Kapetanakis S, Lutz A, Rasche V, Schaeffter T, Butakoff C, Friman O, Mansi T, Sermesant M, Zhuang X, Ourselin S, Peitgen HO, Pennec X, Razavi R, Rueckert D, Frangi AF, Rhode KS (2013) Benchmarking framework for myocardial tracking and deformation algorithms: an open access database. Med Image Anal 17:632–648CrossRefGoogle Scholar