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3 Acta of Bioengineering and Biomechanics

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The probability of traumatic brain injuries based on tissue-level reliability analysis

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Hazay M. , Bojtár I.

2019

tom Vol. 21, no. 1

141--152

Motor vehicle crashes are one of the leading causes of traumatic brain injuries. Restraint systems of cars are evaluated by crash tests based on human tolerance data, however, the reliability of data currently used has been questioned several times in the literature due to the neglect of certain types of effects, injury types and uncertainties. Our main goal was to re-evaluate the currently applied risk curve by taking the previously neglected effects into account. Methods: In this paper, the probability of traumatic brain injury was determined by reliability analysis where different types of uncertainties are taken into account. The tissue-level response of the human brain in the case of frontal crashes was calculated by finite element analyses and the injury probability is determined by Monte Carlo simulations. Sensitivity analysis was also performed to identify which effects have considerable contribution to the injury risk. Results: Our results indicate a significantly larger injury risk than it is predicted by current safety standards. Accordingly, a new risk curve was constructed which follows a lognormal distribution with the following parameters: μLN = 6.5445 and LN = 1.1993. Sensitivity analysis confirmed that this difference primarily can be attributed to the rotational effects and tissue-level uncertainties. Conclusions: Results of the tissue-level reliability analysis enhance the belief that rotational effects are the primary cause of brain injuries. Accordingly, the use of a solely translational acceleration based injury metric contains several uncertainties which can lead to relatively high injury probabilities even if relatively small translational effects occur.

Contribution of ligaments to intersegmental stability following type II odontoid fracture

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Danka D. , Bojtár I.

Acta of Bioengineering and Biomechanics

2023

tom Vol. 25, no. 4

60--68

Cervical spine fractures pose an increasing burden to society despite accounting for merely 3- 5% of all traumatic injury cases [10,14]. C2 fractures comprise 7,8% of all spinal fracture cases [8] and represent a predominant type within cervical spine fractures. Odontoid fractures form a notable subset of C2 fractures, with Anderson and D'Alonzo type II [1] being the most common odontoid fractures (OFII). Granted their clinical significance and relatively frequent occurrence, controversies continue about whether conservative or surgical treatments are preferable, particularly concerning the geriatric population [23,20,17,6,11,7].

Engineering optimization of decompressive craniectomy based on finite element simulations

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Hazay M. , Nagy E. , Tóth P. , Büki A. , Bojtár I.

Acta of Bioengineering and Biomechanics

2020

tom Vol. 22, no. 4

109--122

The optimal execution of decompressive craniectomy in terms of the size and location of the skull opening is not straightforward. Our main goals are twofold: (1) constructing a design optimization method which can be applied to determine optimal skull opening for individual patient-specific cases and (2) performing a large-scale parametric optimization study to give some guidance in general about the optimal skull opening in case of oedematous brain tissue. Methods: A large number of virtual experiments performed by finite element simulations were applied to determine tendencies of tissue behaviour during surgery. The multiobjective optimization is performed by Goal Programming and Physical Programming methods. Results: Our results show that the postoperative pressure has an approximately linear dependence on the preoperative pressure and the skull opening area, while the damaged brain volume could have a more complex nonlinear dependence on the input data. Based on the averaged results of the parametric optimization study, the optimal skull opening has been determined in the function of the preoperative pressure and the relative importance of the pressure reduction. These results show that the optimal size of the unilateral skull opening is usually between 130–180 cm2 and these openings are more beneficial than the currently analysed bifrontal openings. Conclusions: The optimal skull opening is patient-specific and depends on several input data. The presented methodology can be applied to optimize surgery based on these input parameters for different injury types. Based on the results of large-scale parametric study generally applicable approximate results have been provided.