Biomedical engineering advances最新文献

Modern neurosurgery strives to maximize tumor removal while preserving healthy tissue integrity. Accurate intraoperative differentiation between tumor and healthy tissue is crucial yet challenging. Often neurosurgeons rely on their experience and haptic feedback during palpation to distinguish between tumor and healthy tissue. A commonly used hand-held tool for tissue removal during neurosurgery is the ultrasonic aspirator, which changes its electrical properties as it interacts with tissue. The goal is to equip the ultrasonic aspirator with the ability to differentiate between different types of tissue while at the same time not interfering with the surgical workflow and providing comprehensible outcomes. To this end, a hierarchical classification approach is employed as a proof of concept, enabling precise identification of tissue stiffness during resection.

The hierarchical approach is compared with the standard flat classification, commonly used in machine learning. Within the hierarchical approach, two strategies are employed: mandatory leaf-node predictions (MLNP) and non-mandatory leaf-node predictions (NMLNP). The NMLNP allows prediction to revert to a parent node when certainty is low. Data are acquired on three artificial tissue models – differing in stiffness – with an ultrasonic aspirator in a hand-held manner. The dataset comprises 1,821 data points for training and 186 for testing after balancing.

The results indicate a slight performance advantage for the hierarchical classification MLNP approach over the flat classification approach in the absence of confidence thresholds, with weighted F2-scores of 0.781 and 0.762, respectively. However, the application of confidence thresholds results in both approaches exhibiting comparable performance, with the hierarchical NMLNP approach achieving a weighted F1-score of 0.920, thereby demonstrating superior overall performance. The effects of enforcing these thresholds and excluding data with low certainty are thoroughly investigated. This work emphasizes the feasibility of tissue differentiation using a hand-held ultrasound aspirator while resecting tissue. Moreover, it highlights the capability of hierarchical classification in advancing tissue differentiation accuracy during neurosurgical procedures, which could ultimately aid surgeons and enhance the safety of intraoperative workflows.

Tissue engineering approaches have revolutionized the treatment of neural nerve injuries caused by disruption to axonal route or tract. Neurodegenerative diseases, traumatic brain injury (TBI), spinal cord injury (SCI), and peripheral nerve injury (PNI) change the intricate architecture, resulting in growth inhibition and loss of guidance over long distances. Neural tissue engineering aims to overcome limitations of cell-based therapeutics. Efforts are being made to create an optimal scaffold using natural, synthetic, and conductive polymers that match the biological, mechanical, and electrical properties of the native neural tissue. Combining biomaterials, cells, and biochemicals promotes axonal regrowth, facilitating functional recovery from neural nerve disorders. This review focuses on the recent advancements in neural tissue engineering technologies and their applications.

Cardiovascular disorders primarily harm and shorten the lives of countless individuals worldwide. Even while surgical heart transplants and other medical procedures can help people with cardiovascular disease live longer, finding the right donor and the expense of therapy are obstacles that force patients to look for less intrusive and less expensive therapies. The use of synthetic biomaterials, such as titanium-based implants, offers an alternate path with the potential to heal and regenerate the heart. However, in most biomedical cases titanium-based implants are accompanied by surface related limitations which deter them from fulfilling their potential. Over the years, surface related shortfalls are usually addressed by fabrication of coatings exhibiting better properties using different sorts of surface modification techniques. These techniques include physical vapor depositions, plasma spraying, sol-gel and laser cladding etc. However, the exploration of employing lasers to alter the surface of cardiac based implants remains a subject that needs further research. In this work, the developments of functional coatings exhibiting good corrosion resistance and better biocompatibility are reviewed with the aim to deduce the possibility of applying such coatings on titanium based cardiovascular implants thereby alleviating burdens of this disease.