Progress in biomedical engineering (Bristol, England)最新文献

Microwave imaging (MWI) is a promising modality due to its non-invasive nature and lower cost compared to other medical imaging techniques. These characteristics make it a potential alternative to traditional imaging techniques. It has various medical applications, particularly explored in breast and brain imaging. Machine learning (ML) has also been increasingly used for medical applications. This paper provides a scoping review of the role of ML in MWI, focusing on two key areas: image reconstruction and classification. The reconstruction section discusses various ML algorithms used to enhance image quality, highlighting methods such as convolutional neural network and support vector machine. The classification section delves into the application of ML for distinguishing between different tissue types, including applications in breast cancer detection and neurological disorder classification. By analyzing the latest studies and methodologies, this review addresses the current state of ML-enhanced MWI and sheds light on its potential for clinical applications.

Background.Transcatheter pulmonary valve replacement (TPVR) has emerged as a less invasive alternative to surgical pulmonary valve replacement for patients with right ventricular outflow tract dysfunction, such is especially important for those individuals whom had previous cardiac surgical procedures. Recently, three-dimensional (3D) printing and finite element (FE) computational simulation technologies have been employed to enhance preoperative planning processes; however, their effectiveness and clinical significance remain to be fully validated. This systematic review aims to describe the applications and potential impacts of 3D printing and FE simulation technologies for TPVR in clinical practice.Methods.A systematic search of PubMed, Science Direct, Web of Science, and Google Scholar was conducted to identify studies using patient-specific 3D-printed models and FE simulations for preoperative planning and device performance testing.Results.From 289 identified articles, 28 met the inclusion criteria for this review. The quality assessment of the articles showed that the article selection process was adequate. The eligible studies demonstrated that both 3D printing and FE-based simulations have been primarily used to select the appropriate pulmonary valve size as well as predict the optimal placement; i.e. to avoid potential complications such as paravalvular leakage or pulmonary regurgitation. These technologies are generally used in complex congenital and adult-congenital cases. Additionally, these studies provide valuable insights into the mechanical performances of the transcatheter valves using patient-specific anatomies.Conclusion.3D-printed models and FE simulations have both demonstrated utilities in TPVR planning; by accurately reproducing a given patient's anatomy and allowing evaluations of potential device-tissue interactions. These tools thus allow for personalized treatments and also contribute to device innovations and development. Yet, further research in this field is required due to the noted limitations of current studies, including small sample sizes, insufficient standardization, and/or challenges in replicating the biomechanics of cardiac tissue.

Stroke is a leading cause of adult disability worldwide, with approximately 101 million survivors globally. Over 60% of these individuals live with from long-term, often lifelong, movement impairments that significantly hinder their ability to perform essential daily activities and maintain independence. Post-stroke movement disabilities are highly associated with structural and functional changes in motor descending pathways, particularly the corticospinal tract and other indirect motor pathways via the brainstem. For decades, neuroengineers have been working to quantitively evaluate the post-stroke changes of motor descending pathways, aiming to establish a precision prognosis and tailoring treatments to post-stroke motor impairment. However, a clear and practicable technique has not yet been established as a breakthrough to change the standard of care for current clinical practice. In this review, we outline recent progress in neuroimaging, neuromodulation, and electrophysiological approaches for assessing structural and functional changes of motor descending pathways in stroke. We also discuss their limitations and challenges, arguing the need of artificial intelligence and large multi-modal data registry for a groundbreaking advance to this important topic.

Image-guided tumor ablation (IGTA) has revolutionized modern oncological treatments by providing minimally invasive options that ensure precise tumor eradication with minimal patient discomfort. Traditional techniques such as ultrasound (US), computed tomography, and magnetic resonance imaging have been instrumental in the planning, execution, and evaluation of ablation therapies. However, these methods often face limitations, including poor contrast, susceptibility to artifacts, and variability in operator expertise, which can undermine the accuracy of tumor targeting and therapeutic outcomes. Incorporating deep learning (DL) into IGTA represents a significant advancement that addresses these challenges. This review explores the role and potential of DL in different phases of tumor ablation therapy: preoperative, intraoperative, and postoperative. In the preoperative stage, DL excels in advanced image segmentation, enhancement, and synthesis, facilitating precise surgical planning and optimized treatment strategies. During the intraoperative phase, DL supports image registration and fusion, and real-time surgical planning, enhancing navigation accuracy and ensuring precise ablation while safeguarding surrounding healthy tissues. In the postoperative phase, DL is pivotal in automating the monitoring of treatment responses and in the early detection of recurrences through detailed analyses of follow-up imaging. This review highlights the essential role of DL in modernizing IGTA, showcasing its significant implications for procedural safety, efficacy, and patient outcomes in oncology. As DL technologies continue to evolve, they are poised to redefine the standards of care in tumor ablation therapies, making treatments more accurate, personalized, and patient-friendly.

Microfluidic-based sperm selection is an essential tool recently introduced into assisted reproductive technologies. Conventional approaches such as swim-up and density-gradient centrifugation (DGC) are widely used, however, they lack selectivity and limit the necessary sperm amount in the sample. Moreover, the DGC method has been reported to damage the sperm's DNA, whilst the emerging microfluidic devices offer a soft and flexible way to selectively sort various volumes of raw sperm samples. The flexibility of the discussed technology is associated with the channel architectures based on different sorting mechanisms. In particular, motility-based sorting devices are generally applied for rapid sperm selection without cell damaging by reactive oxygen species. Non-motile sperm samples can be separated from non-sperm cells by inertial microfluidics. The most promising approach to sperm selection has been presented by rheotaxis-based chips, shown to closely mimic the female reproductive tract. In this review, we discuss the key aspects of the chip design according to the underlying mechanisms. The microfluidic chips' fabrication issues and challenges have also been highlighted.

Peripheral nerve injury (PNI) presents a major neurological challenge, with symptoms varying depending on the extent of axonal damage. Although we have some understanding of pathophysiology and regeneration mechanisms of PNI, achieving complete and accurate functional restoration remains elusive. Current regenerative treatments are often slow, and full recovery is still largely aspirational despite various therapeutic approaches. This review evaluates the advantages and limitations of new bioadhesives and electrical stimulation (ES) therapies, whether used alone or in combination, for promoting healing of PNI. Despite significant progress in nerve repair and regenerationin vitro, clinical validation of these methods is limited, and further research is needed. The strong preclinical evidence supporting the effectiveness of ES and bioadhesives in treating PNI now calls for advancement beyond experimental models to clinical testing.

Peripheral nerve injury (PNI) is a common problem worldwide. PNI can lead to loss of sensory and motor functions, chronic neuropathic pain, and mental health issues, significantly impacting the patients' quality of life. Recent studies revealed that, beyond the topical injury site at peripheral nerves, PNIs can also induce dysfunctions in the central nervous system by causing maladaptive plasticity, which will result in exaggeration and exacerbation of the pathological condition caused by the primary injuries. The typical therapy strategies for traumatic PNI treatment are using sutures, nerve autografts, or conduits in cases requiring surgical intervention as well as applying physical-based rehabilitation to facilitate functional recovery. However, the functional restoration is generally unsatisfactory due to insufficient regeneration and long-lasting maladaptive neuroplasticity in the nervous system. In this review, we summarized various neurotrophic factors and neuroprotective agents that have been extensively studied as adjuvant therapies to enhance recovery efficiency after PNIs in the last two decades. Particularly, with the rapid development of biomaterials and bioengineering, controllable drug delivery techniques have shown great potential to maintain the drug bioactivity and, consequently, prolonging the therapeutic effects. Additionally, we explored the virus-based gene delivery technique, which has been used to transduce neural cells for enhancing nerve regeneration. Finally, we discussed current challenges, including inadequate motor function restoration, poorly defined rehabilitation protocols, unresolved chronic inflammation, and limited understanding of macrophage dynamics. We also offered perspectives on integrating various approaches to develop effective and comprehensive treatment strategies for PNIs.

Melt electrowriting (MEW) is an advanced additive manufacturing technique that offers unprecedented microscale control over polymer fiber deposition for tissue engineering applications. This review focuses on recent advancements in MEW technology beyond flat collectors to non-planar, anatomically relevant structures. Such non-planar MEW is enabled by maintaining stable electric field control through a consistent nozzle-to-collector distance, using custom 3D-printed insulating collectors, and multi-axis MEW setup. These advancements allow accurate fiber patterning on curved surfaces and make non-planar MEW feasible for complex scaffold geometries. In parallel, the integration of MEW with complementary fabrication methods (such as fused deposition modeling, electrospinning, and bioprinting) has emerged, permitting the fabrication of intricate, multi-functional scaffolds that closely mimic natural tissue architectures. Automated, multi-parameter process control strategies, through real-time feedback systems incorporating machine vision and artificial intelligence, further improve fiber deposition accuracy and scaffold reproducibility. This review highlights both the key breakthroughs and remaining challenges in non-planar MEW, underscoring the technology's transformative potential in tissue engineering to create highly customized, biomimetic, and physiologically relevant tissue structures.

Stroke, a vascular disorder affecting the nervous system, is the third-leading cause of death and disability combined worldwide. One in every four people aged 25 and older will face the consequences of this condition, which typically causes loss of limb function, among other disabilities. The proposed review analyzes the mechanisms of stroke and their influence on the disease outcome, highlighting the critical role of rehabilitation in promoting recovery of the upper limb (UL) and enhancing the quality of life of stroke survivors. Common outcome measures and the specific targeted UL features are described, along with emerging supplementary therapies found in the literature. Stroke survivors often develop compensatory strategies to cope with limitations in UL function, which must be detected and corrected during rehabilitation to facilitate long-term recovery. Recent research on the automated detection of compensatory movements has explored pressure, wearable, marker-based motion capture systems, and vision sensors. Although current approaches have certain limitations, they establish a strong foundation for future innovations in post-stroke UL rehabilitation, promoting a more effective recovery.

Transcranial stimulation has emerged as a non-invasive treatment that applies electrical currents and magnetic fields to regulate brain functions. Previous studies have shown that magnetic stimulation modulates the dynamics of charged molecules in biological systems. In some pathologies, once the electrical or magnetic field is applied directly to subjects, it can interact with, and alter, abnormally folded proteins, including amyloid-βpeptides and their aggregates, reducing cognitive impairments. While our understanding of the molecular mechanisms underlying the interaction between amyloid-βpeptide and the physical forces generated by electrical or magnetic stimulation remains unclear, observations show that these stimuli exert attractive and repulsive forces while interacting with the charged groups of peptide side chains as well as lipids. These interactions influence hydrophobic packing and secondary structure, ultimately inducing alterations in aggregation kinetics. The study of structural models of amyloidogenic proteins aids in understanding the mechanisms involved in the protein aggregation process and suggests possible therapeutic applications. This review examines proposed molecular mechanisms to explain the modulatory effects of external electromagnetic fields on the dynamics of proteins and their complexes that regulate pathological processes associated with amyloid-βpeptide fibrillation.