The human head is sometimes subjected to impact loads that lead to skull fracture or other injuries that require the removal of part of the skull, which is called craniectomy. Consequently, the removed portion is replaced using autologous bone or alloplastic material. The aim of this work is to develop a cranial implant to fulfil a defect created on the skull and then study its mechanical performance by integrating it on a human head finite element model. The material chosen for the implant was PEEK, a thermoplastic polymer that has been recently used in cranioplasty. A6 numerical model head coupled with an implant was subjected to analysis to evaluate two parameters: the number of fixation screws that enhance the performance and ensure the structural integrity of the implant, and the implant’s capacity to protect the brain compared to the integral skull. The main findings point to the fact that, among all tested configurations of screws, the model with eight screws presents better performance when considering the von Mises stress field and the displacement field on the interface between the implant and the skull. Additionally, under the specific analyzed conditions, it is observable that the model with the implant offers more efficient brain protection when compared with the model with the integral skull.
The biomechanics of traumatic injuries of the human body as a consequence of road crashes, falling, contact sports, and military environments have been studied for decades. In particular, traumatic brain injury (TBI), the so-called “silent epidemic”, is the traumatic insult responsible for the greatest percentage of death and disability, justifying the relevance of this research topic. Despite its great importance, only recently have research groups started to seriously consider the sex differences regarding the morphology and physiology of women, which differs from men and may result in a specific outcome for a given traumatic event. This work aims to provide a summary of the contributions given in this field so far, from clinical reports to numerical models, covering not only the direct injuries from inertial loading scenarios but also the role sex plays in the conditions that precede an accident, and post-traumatic events, with an emphasis on neuroendocrine dysfunctions and chronic traumatic encephalopathy. A review on finite element head models and finite element neck models for the study of specific traumatic events is also performed, discussing whether sex was a factor in validating them. Based on the information collected, improvement perspectives and future directions are discussed.
Purpose The key problem raised in the paper is the change in the position of the breast tumor due to magnetic resonance imaging examinations in the abdominal position relative to the supine position during the surgical procedure. Changing the position of the patient leads to significant deformation of the breast, which leads to the inability to indicate the location of the neoplastic lesion correctly.Methods This study outlines a methodological process for treating cancer patients. Pre-qualification assessments are conducted for magnetic resonance imaging (MRI), and 3D scans are taken in three positions: supine with arms raised (SU), supine surgical position (SS), and standing (S). MRI and standard ultrasonography (USG) imaging are performed, and breast and cancer tissue are segmented from the MRI images. Finite element analysis is used to simulate tissue behavior in different positions, and an artificial neural network is trained to predict tumor dislocation. Based on the model, a 3D-printed breast with a highlighted tumor is manufactured. This computer-aided analysis is used to create a detailed surgical plan, and lumpectomy surgery is performed in the supine surgical position (SS). In addition, the geometry of the tumor is presented to the medical staff as a 3D-printed element.Results By utilizing a comprehensive range of techniques, including pre-qualification assessment, 3D scanning, MRI and USG imaging, segmentation of breast and cancer tissue, model analysis, image fusion, finite element analysis, artificial neural network training, and additive manufacturing, a detailed surgical plan can be created for performing lumpectomy surgery in the supine surgical position.Conclusion The new approach developed for the pre-operative assessment and surgical planning of breast cancer patients has demonstrated significant potential for improving the accuracy and efficacy of surgical procedures. This procedure may also help the pathomorphological justification. Moreover, transparent 3D-printed breast models can benefit breast cancer operation assistance. The physical and computational models can help surgeons visualize the breast and the tumor more accurately and detailedly, allowing them to plan the surgery with greater precision and accuracy.
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