Biofidelity of finite element head model (FEHM) includes geometric and material aspects. A FEHM with inhomogeneous material properties was proposed to improve material biofidelity. The proposed FEHM was validated against experimental data and good agreements were observed. The capability of the proposed model in simulating large tissue deformation was also demonstrated. Influences of inhomogeneous material properties on the mechanical responses of head were investigated by comparing with homogeneous material model. The inhomogeneous material properties induce large peak strains in head constituents, which are probably the cause of various brain injuries. Helmets are effective in preventing head injuries. Parametric studies were conducted to investigate how changes in helmet shell stiffness, foam density and pad thickness influence the performance of a helmet in protecting the brain. Results showed that strain energy absorbed by foam component, contact stress on the interfaces and intracranial responses are significantly affected by foam density and pad thickness.

Biofidelity of finite element head model (FEHM) includes geometric and material aspects. A FEHM with inhomogeneous material properties was proposed to improve material biofidelity. The proposed FEHM was validated against experimental data and good agreements were observed. The capability of the proposed model in simulating large tissue deformation was also demonstrated. Influences of inhomogeneous material properties on the mechanical responses of head were investigated by comparing with homogeneous material model. The inhomogeneous material properties induce large peak strains in head constituents, which are probably the cause of various brain injuries. Helmets are effective in preventing head injuries. Parametric studies were conducted to investigate how changes in helmet shell stiffness, foam density and pad thickness influence the performance of a helmet in protecting the brain. Results showed that strain energy absorbed by foam component, contact stress on the interfaces and intracranial responses are significantly affected by foam density and pad thickness.

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The purpose of this project was to explore the performance of methods for estimating stopping power ratio (SPR) from Hounsfield units (HU) using dual energy CT scans, rather than the standard single energy CT scans, with the aim of finding a method which could outperform the current single energy stoichiometric method. Such a method could reduce the margin currently added to the target volume during treatment which is defined as 3.5 % of the range to the target volume + 1 mm . Three such methods, by Taasti, Zhu, and, Lalonde and Bouchard, were chosen and implemented in MATLAB. A phantom containing 10 tissue-like inserts was scanned and used as a basis for the SPR estimation. To investigate the variation of the SPR from day-to-day the phantom was scanned once a day for 12 days. The resulting SPR of all methods, including the stoichiometric method, were compared with theoretical SPR values which were calculated using known elemental weight fractions of the inserts and mean excitation energies from the National Institute of Standards and Technology (NIST). It was found that the best performing method was the Taasti method which had, at best, an average percentage difference from the theoretical values of only 2.5 %. The Zhu method had, at best, 4.8 % and Lalonde-Bouchard 15.6% including bone tissue or 6.3 % excluding bone. The best average percentage difference of the stoichiometric method was 3.1 %. As the Taasti method was the best performing method and shows much promise, future work should focus on further improving its performance by testing more scanning protocols and kernels to find the ones yielding the best performance. This should then be supplemented with testing different pairs of energies for the dual energy scans. The fact that the Zhu and Lalonde-Bouchard method performed poorly could indicate problems with the implementation of those methods in this project. Investigating and solving those problems is also an important goal for future projects. Lastly the Lalonde-Bouchard method should be tested with more than two energy spectra.