Prediction of skull fractures in blunt force head traumas using finite element head models

Traumatic head injuries remain a leading cause of death and disability worldwide. Although skull fractures are one of the most common head injuries, the fundamental mechanics of cranial bone and its impact tolerance are still uncertain. In the present study, a strain-rate-dependent material model for cranial bone has been proposed and implemented in subject-specific Finite Element (FE) head models in order to predict skull fractures in five real-world fall accidents. The subject-specific head models were developed following an established image-registration-based personalization pipeline. Head impact boundary conditions were derived from accident reconstructions using personalized human body models. The simulated fracture lines were compared to those visible in post-mortem CT scans of each subject. In result, the FE models did predict the actual occurrence and extent of skull fractures in all cases. In at least four out of five cases, predicted fracture patterns were comparable to ones from CT scans and autopsy reports. The tensile material model, which was tuned to represent rate-dependent tensile data of cortical skull bone from literature, was able to capture observed linear fractures in blunt indentation loading of a skullcap specimen. The FE model showed to be sensitive to modeling parameters, in particular to the constitutive parameters of the cortical tables. Nevertheless, this study provides a currently lacking strain-rate dependent material model of cranial bone that has the capacity to accurately predict linear fracture patterns. For the first time, a procedure to reconstruct occurrences of skull fractures using computational engineering techniques, capturing the all-in-all fracture initiation, propagation and final pattern, is presented.

Establishment and external validation of a nomogram for predicting 28-day mortality in patients with skull fracture

Background

Skull fracture can lead to significant morbidity and mortality, yet the development of effective predictive tools has remained a challenge. This study aimed to establish and validate a nomogram to evaluate the 28-day mortality risk among patients with skull fracture.

Materials and methods

Data extracted from the Medical Information Mart for Intensive Care (MIMIC) database were utilized as the training set, while data from the eICU Collaborative Research Database were employed as the external validation set. This nomogram was developed using univariate Cox regression, best subset regression (BSR), and the least absolute shrinkage and selection operator (LASSO) methods. Subsequently, backward stepwise multivariable Cox regression was employed to refine predictor selection. Variance inflation factor (VIF), akaike information criterion (AIC), area under the receiver operating characteristic curve (AUC), concordance index (C-index), calibration curve, and decision curve analysis (DCA) were used to assess the model's performance.

Results

A total of 1,527 adult patients with skull fracture were enrolled for this analysis. The predictive factors in the final nomogram included age, temperature, serum sodium, mechanical ventilation, vasoactive agent, mannitol, extradural hematoma, loss of consciousness and Glasgow Coma Scale score. The AUC of our nomogram was 0.857, and C-index value was 0.832. After external validation, the model maintained an AUC of 0.853 and a C-index of 0.829. Furthermore, it showed good calibration with a low Brier score of 0.091 in the training set and 0.093 in the external validation set. DCA in both sets revealed that our model was clinically useful.

Conclusion

A nomogram incorporating nine features was constructed, with a good ability in predicting 28-day mortality in patients with skull fracture.

Bone Density Micro-CT Assessment during Embedding of the Innovative Multi-Spiked Connecting Scaffold in Periarticular Bone to Elaborate a Validated Numerical Model for Designing Biomimetic Fixation of Resurfacing Endoprostheses

Our team has been working for some time on designing a new kind of biomimetic fixation of resurfacing endoprostheses, in which the innovative multi-spiked connecting scaffold (MSC-Scaffold) that mimics the natural interface between articular cartilage and periarticular trabecular bone in human joints is the crucial element. This work aimed to develop a numerical model enabling the design of the considered joint replacement implant that would reflect the mechanics of interacting biomaterials. Thus, quantitative micro-CT analysis of density distribution in bone material during the embedding of MSC-Scaffold in periarticular bone was applied. The performed numerical studies and corresponding mechanical tests revealed, under the embedded MSC-Scaffold, the bone material densification affecting its mechanical properties. On the basis of these findings, the built numerical model was modified by applying a simulated insert of densified bone material. This modification led to a strong correlation between the re-simulation and experimental results (FVU = 0.02). The biomimetism of the MSC-Scaffold prototype that provided physiological load transfer from implant to bone was confirmed based on the Huber–von Mises–Hencky (HMH) stress maps obtained with the validated finite element (FE) model of the problem. The micro-CT bone density assessment performed during the embedding of the MSC-Scaffold prototype in periarticular bone provides insight into the mechanical behaviour of the investigated implant-bone system and validates the numerical model that can be used for the design of material and geometric features of a new kind of resurfacing endoprostheses fixation.

Association of skull fracture with in-hospital mortality in severe traumatic brain injury patients

INTRODUCTION

To identify the association between skull fracture (SF) and in-hospital mortality in patients with severe traumatic brain injury (TBI).

MATERIALS AND METHODS

This multicenter cohort study included a retrospective analysis of data from the Japan Trauma Data Bank (JTDB). JTDB is a nationwide, prospective, observational trauma registry with data from 235 hospitals. Adult patients with severe TBI (Glasgow Coma Scale <9, head Abbreviated Injury Scale (AIS) ≥ 3, and any other AIS < 3) who were registered in the JTDB between January 2004 and December 2017 were included in the study. Patients who (a) were < 16 years old, (b) developed cardiac arrest before or at hospital arrival, and (c) had burns and penetrating injuries were excluded from the study. In-hospital mortality was the primary outcome assessed. Multivariable logistic regression analyses were performed to calculate the adjusted odds ratios (ORs) of SF and their 95% confidence intervals (CIs) for in-hospital mortality.

RESULTS

A total of 9607 patients were enrolled [median age: 67 (interquartile range: 50-78) years] in the study. Among those patients, 3574 (37.2%) and 6033 (62.8%) were included in the SF and non-SF groups, respectively. The overall in-hospital mortality rate was 44.1% (4238/9607). A multivariate analysis of the association between SF and in-hospital mortality yielded a crude OR of 1.63 (95% CI: 1.47-1.80). A subgroup analysis of the association of skull vault fractures, skull base fractures, and both fractures together with in-hospital mortality yielded adjusted ORs of 1.60 (95% CI: 1.42-1.98), 1.40 (95% CI: 1.16-1.70), and 2.14 (95% CI: 1.74-2.64), respectively, relative to the non-SF group.

CONCLUSIONS

This observational study showed that SF is associated with in-hospital mortality among patients with severe TBI. Furthermore, patients with both skull base and skull vault fractures were associated with higher in-hospital mortality than those with only one of these injuries.

Tissue-specific changes in size and shape of the ligaments and tendons of the porcine knee during post-natal growth

Prior studies have analyzed growth of musculoskeletal tissues between species or across body segments; however, little research has assessed the differences in similar tissues within a single joint. Here we studied changes in the length and cross-sectional area of four ligaments and tendons, (anterior cruciate ligament, patellar tendon, medial collateral ligament, lateral collateral ligament) in the tibiofemoral joint of female Yorkshire pigs through high-field magnetic resonance imaging throughout growth. Tissue lengths increased by 4- to 5-fold from birth to late adolescence across the tissues while tissue cross-sectional area increased by 10–20-fold. The anterior cruciate ligament and lateral collateral ligament showed allometric growth favoring change in length over change in cross-sectional area while the patellar tendon and medial collateral ligament grow in an isometric manner. Additionally, changes in the length and cross-sectional area of the anterior cruciate ligament did not increase as much as in the other ligaments and tendon of interest. Overall, these findings suggest that musculoskeletal soft tissue morphometry can vary within tissues of similar structure and within a single joint during post-natal growth.