Bioengineering最新文献

{"title":"Updates, Applications and Future Directions of Deep Learning for the Images Processing in the Field of Cranio-Maxillo-Facial Surgery.","authors":"Luca Michelutti, Alessandro Tel, Massimo Robiony, Lorenzo Marini, Daniele Tognetto, Edoardo Agosti, Tamara Ius, Caterina Gagliano, Marco Zeppieri","doi":"10.3390/bioengineering12060585","DOIUrl":"10.3390/bioengineering12060585","url":null,"abstract":"<p><p>The entry of artificial intelligence, in particular deep learning models, into the study of medical-clinical processes is revolutionizing the way of conceiving and seeing the future of medicine, offering new and promising perspectives in patient management. These models are proving to be excellent tools for the clinician through their great potential and capacity for processing clinical data, in particular radiological images. The processing and analysis of imaging data, such as CT scans or histological images, by these algorithms offers aid to clinicians for image segmentation and classification and to surgeons in the surgical planning of a delicate and complex operation. This study aims to analyze what the most frequently used models in the segmentation and classification of medical images are, to evaluate what the applications of these algorithms in maxillo-facial surgery are, and to explore what the future perspectives of the use of artificial intelligence in the processing of radiological data are, particularly in oncological fields. Future prospects are promising. Further development of deep learning algorithms capable of analyzing image sequences, integrating multimodal data, i.e., combining information from different sources, and developing human-machine interfaces to facilitate the integration of these tools with clinical reality are expected. In conclusion, these models have proven to be versatile and potentially effective tools on different types of data, from photographs of intraoral lesions to histopathological slides via MRI scans.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12189383/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144493994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Contrast-Enhanced Ultrasound-Guided Microwave Ablation for Iatrogenic Hepatic Hemorrhage: A Feasibility Study on Precision Hemostasis.","authors":"Qing Li, Yi Liu, Zenghui Han, Xuan Zhou, Jianwei Wang, Xiaodong Zhou, Li Yan","doi":"10.3390/bioengineering12060584","DOIUrl":"10.3390/bioengineering12060584","url":null,"abstract":"<p><p><b>Objectives</b>: The aim of this study was to investigate the feasibility of contrast-enhanced ultrasound (CEUS)-guided microwave ablation for managing iatrogenic hepatic hemorrhage following percutaneous liver puncture. <b>Materials and methods</b>: This retrospective study analyzed six patients (5 males, 1 female; mean age 56.8 ± 12.3 years) with CEUS-confirmed active hepatic hemorrhage refractory to 10 min compression and Agkistrodon halflorum hemagglutinase administration after percutaneous liver puncture (2023-2024). Etiologies included portal vein cavernous transformation (n = 4) and therapeutic intervention complications (n = 2). All patients underwent CEUS-guided microwave ablation comprising three phases: bleeding site localization, real-time ultrasound-guided ablation, and immediate postprocedural verification (CEUS: n = 6; DSA: n = 2). The protocol was approved by the institutional ethics committee with written informed consent. <b>Results</b>: All six patients achieved immediate hemostasis (mean 2.8 min) through CEUS-guided microwave ablation with 100% technical/clinical success. Preprocedural localization combined color Doppler and CEUS, while intraoperative real-time guidance ensured precise microwave needle placement. Post-ablation verification relied on CEUS (n = 6) with DSA confirmation in two cases. No major complications occurred; one patient reported transient abdominal pain resolving spontaneously. All patients remained stable during 7-day follow-up with no delayed complications. <b>Conclusions</b>: This study suggests that CEUS-guided microwave ablation is a rapid, minimally invasive, and effective option for iatrogenic hepatic hemorrhage, warranting further validation in larger cohorts.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12189783/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144494012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Expert-AI Collaborative Training for Novice Endoscopists: A Path to Enhanced Efficiency.","authors":"Zhen Zhang, Bai-Sheng Chen, Ling Du, Quan-Lin Li, Yan Zhu, Pei-Yao Fu, Wen-Zheng Qin, Huan-Kai Shou, Ping-Ting Gao, Xin-Yang Liu, Meng-Jiang He, Zi-Han Geng, Shuo Wang, Ping-Hong Zhou","doi":"10.3390/bioengineering12060582","DOIUrl":"10.3390/bioengineering12060582","url":null,"abstract":"<p><strong>Background: </strong>Esophagogastroduodenoscopy (EGD) is essential for diagnosing upper gastrointestinal disorders. Traditional training for novice endoscopists is often inefficient and inconsistent. This study evaluates the effectiveness of an AI-assisted system (EndoAdd) in improving EGD training.</p><p><strong>Methods: </strong>In a randomized controlled trial, eight novice endoscopists were assigned to either the EndoAdd group or a control group (traditional training). The EndoAdd system provided real-time feedback on blind spots and photodocumentation. Primary outcomes were the number of blind spots, with secondary outcomes including examination time, lesion detection, and photodocumentation completeness.</p><p><strong>Results: </strong>The EndoAdd system exhibited an overall accuracy of 98.0% and a mean area under the curve (AUC) of 0.984. The EndoAdd group had significantly fewer blind spots, improved photodocumentation, and a higher lesion detection rate. Examination time was reduced without compromising diagnostic accuracy.</p><p><strong>Conclusions: </strong>The AI-assisted EndoAdd system improved novice endoscopist performance, reducing blind spots and enhancing lesion detection. AI systems like EndoAdd show potential in accelerating endoscopy training and improving procedural quality.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12189645/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144494034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AdaptRehab VR: Development of an Immersive Virtual Reality System for Upper Limb Stroke Rehabilitation Designed for Low- and Middle-Income Countries Using a Participatory Co-Creation Approach.","authors":"Chala Diriba Kenea, Teklu Gemechu Abessa, Dheeraj Lamba, Bruno Bonnechère","doi":"10.3390/bioengineering12060581","DOIUrl":"10.3390/bioengineering12060581","url":null,"abstract":"<p><p>Stroke remains a significant global health challenge, particularly in low- and middle-income Countries (LMICs), where two-thirds of stroke-related deaths occur, and disability-adjusted life years are seven times higher compared to high-income Countries (HICs). The majority of stroke survivors suffer from upper limb impairment, severely limiting their daily activities and significantly diminishing their overall quality of life. Rehabilitation plays a critical role in restoring function and independence, but it faces challenges such as low engagement, limited customization, difficulty tracking progress, and accessibility barriers, particularly in LMICs. Immersive virtual reality (imVR) has shown promise in addressing these challenges, but most commercial imVR systems lack therapeutic design and cultural adaptation. This study aimed to develop culturally adaptable imVR games for upper limb stroke rehabilitation (ULSR) in the context of LMICs, with a particular focus on Ethiopia. The AdaptRehab VR system was developed including six imVR games (Basket Bloom, Strike Zone, TapQuest, FruitFall Frenzy, Precision Pitch, and Bean Picker Pro) through co-creation approaches involving Ethiopian and Belgian physiotherapists, stakeholders, and patients, incorporating game development mechanics in rehabilitation, such as therapeutic aims, cultural factors, feedback, automatic progression recording, task variety, and personalized rehabilitation. It was designed with the Unity 3D engine and Oculus Quest headsets, supporting controllers and hand tracking. This culturally tailored imVR platform has demonstrated significant potential to enhance ULSR accessibility, patient motivation, and outcomes in resource-constrained settings, addressing critical gaps in stroke rehabilitation solutions. In conclusion, the AdaptRehab VR system was successfully developed as a culturally contextualized imVR platform tailored to tackle ULSR challenges in LMICs, with a specific focus on Ethiopia.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12189672/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144493917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Flexoelectricity in Biological Materials and Its Potential Applications in Biomedical Research.","authors":"Melika Mohammadkhah, Vukasin Slavkovic, Sandra Klinge","doi":"10.3390/bioengineering12060579","DOIUrl":"10.3390/bioengineering12060579","url":null,"abstract":"<p><p>Flexoelectricity arises in materials under strain gradients, which can be particularly significant for situations in which the existence of other electromechanical properties is absent or generating large flexoelectric properties is achievable. This effect has also been observed in some biological materials, whose understanding can hugely help to further enhance our understanding of vital biological processes like mechanotransduction, as well as the development of applications in regenerative medicine and drug delivery. While the field of flexoelectricity as a relevant topic in biological materials is relatively new and still developing, the current study aims to review available results on flexoelectric effects in biological materials such as cells and cell membranes, hearing mechanisms, and bone, and their potential applications in biomedical research. Therefore, we first provide a brief background on two main electromechanical couplings (piezoelectricity and flexoelectricity) and further, how flexoelectricity has been experimentally and theoretically identified. We then review flexoelectricity in different biological materials as the main aim of the current study. Within that, we provide additional emphasis on the influence of this effect on bone and bone remodeling. In particular, the study outlines current limitations and provides potential directions for future work, emphasizing the crucial role in the development of next-generation electromechanical devices and optimizing their function in the area of biomedical research.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12190139/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144494040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Hybrid Convolutional-Transformer Approach for Accurate Electroencephalography (EEG)-Based Parkinson's Disease Detection.","authors":"Chayut Bunterngchit, Laith H Baniata, Hayder Albayati, Mohammad H Baniata, Khalid Alharbi, Fanar Hamad Alshammari, Sangwoo Kang","doi":"10.3390/bioengineering12060583","DOIUrl":"10.3390/bioengineering12060583","url":null,"abstract":"<p><p>Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by motor and cognitive impairments. Early detection is critical for effective intervention, but current diagnostic methods often lack accuracy and generalizability. Electroencephalography (EEG) offers a noninvasive means to monitor neural activity, revealing abnormal brain oscillations linked to PD pathology. However, deep learning models for EEG analysis frequently struggle to balance high accuracy with robust generalization across diverse patient populations. To overcome these challenges, this study proposes a convolutional transformer enhanced sequential model (CTESM), which integrates convolutional neural networks, transformer attention blocks, and long short-term memory layers to capture spatial, temporal, and sequential EEG features. Enhanced by biologically informed feature extraction techniques, including spectral power analysis, frequency band ratios, wavelet transforms, and statistical measures, the model was trained and evaluated on a publicly available EEG dataset comprising 31 participants (15 with PD and 16 healthy controls), recorded using 40 channels at a 500 Hz sampling rate. The CTESM achieved an exceptional classification accuracy of 99.7% and demonstrated strong generalization on independent test datasets. Rigorous evaluation across distinct training, validation, and testing phases confirmed the model's robustness, stability, and predictive precision. These results highlight the CTESM's potential for clinical deployment in early PD diagnosis, enabling timely therapeutic interventions and improved patient outcomes.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12189856/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144493981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PathCare: Integrating Clinical Pathway Information to Enable Healthcare Prediction at the Neuron Level.","authors":"Dehao Sui, Lei Gu, Chaohe Zhang, Kaiwei Yang, Xiaocui Li, Liantao Ma, Ling Wang, Wen Tang","doi":"10.3390/bioengineering12060578","DOIUrl":"10.3390/bioengineering12060578","url":null,"abstract":"<p><p>Electronic Health Records (EHRs) offer valuable insights for healthcare prediction. Existing methods approach EHR analysis through direct imputation techniques in data space or representation learning in feature space. However, these approaches face the following two critical limitations: first, they struggle to model long-term clinical pathways due to their focus on isolated time points rather than continuous health trajectories; second, they lack mechanisms to effectively distinguish between clinically relevant and redundant features when observations are irregular. To address these challenges, we introduce PathCare, a neural framework that integrates clinical pathway information into prediction tasks at the neuron level. PathCare employs an auxiliary sub-network that models future visit patterns to capture temporal health progression, coupled with a neuron-level filtering gate that adaptively selects relevant features while filtering out redundant information. We evaluate PathCare on the following three real-world EHR datasets: CDSL, MIMIC-III, and MIMIC-IV, demonstrating consistent performance improvements in mortality and readmission prediction tasks. Our approach offers a practical solution for enhancing healthcare predictions in real-world clinical settings with varying data completeness.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12189817/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144494062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hip Fractures: Clinical, Biomaterial and Biomechanical Insights into a Common Health Challenge.","authors":"Yunhua Luo","doi":"10.3390/bioengineering12060580","DOIUrl":"10.3390/bioengineering12060580","url":null,"abstract":"<p><p>Hip fractures represent a significant public health challenge, particularly among the elderly, due to their high incidence, morbidity, and mortality rates. This review provides a comprehensive understanding of hip fractures through clinical, biomaterial, and biomechanical perspectives. Clinically, we examined key risk factors, including age, bone mineral density, and the high prevalence of falls, which account for over 95% of hip fractures. However, current clinical tools, such as FRAX, have notable limitations in accurately assessing fracture risk in individuals due to their reliance on statistical models, the treatment of interdependent risk factors as independent, and the omission of key variables like diabetes. From a biomaterial perspective, we analyzed bone composition-specifically the balance of inorganic minerals, organic proteins, and water-and its role in determining bone strength and fracture susceptibility. Various risk factors ultimately influence this composition balance, thereby affecting bone strength. Therefore, accurately measuring bone composition may provide a more reliable assessment of hip fracture risk. Although emerging imaging technologies such as dual-energy CT and MRI show promise for in vivo assessments of bone composition, these techniques still face significant challenges and remain an active area of research. Biomechanically, we explored the forces generated during falls, noting that impact forces can vastly exceed normal physiological loads and may exploit the anisotropic properties of bone, leading to fractures even in healthy individuals with strong bones. This understanding emphasizes the critical role of fall prevention in reducing fracture risk and highlights the limitations of using fall-induced fracture incidence as a validation metric for clinical assessment tools. Lastly, we discuss preventive strategies, including passive measures like environmental modifications for individuals diagnosed with low bone strength and proactive measures such as muscle strengthening and cognitive training. While passive measures are necessary for immediate protection, proactive strategies are more effective in the long term by addressing underlying risk factors for falls and promoting sustained bone health. This interdisciplinary review underscores the need to integrate clinical, biomaterial, and biomechanical factors to improve diagnostic accuracy, prevention, and treatment strategies for hip fractures, ultimately advancing public health outcomes in aging populations.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12189134/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144494046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial: Biomechanics, Health, Disease and Rehabilitation.","authors":"Redha Taiar","doi":"10.3390/bioengineering12060573","DOIUrl":"10.3390/bioengineering12060573","url":null,"abstract":"<p><p>The purpose of this Special Issue is to specify and understand the impact of bioengineering in carrying data permitting the comprehension of human behavior in daily life tasks [...].</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12189670/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144494022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards Extracellular Vesicles in the Treatment of Epidermolysis Bullosa.","authors":"Aaron Gabriel W Sandoval, Evangelos V Badiavas","doi":"10.3390/bioengineering12060574","DOIUrl":"10.3390/bioengineering12060574","url":null,"abstract":"<p><p>Epidermolysis bullosa (EB) is a debilitating genetic skin disorder characterized by extreme fragility, chronic wounds, and severe complications, particularly in its most severe form, recessive dystrophic EB (RDEB). Current treatments focus on symptomatic relief through wound care and pain management, with recent FDA approvals of Vyjuvek and Filsuvez providing new but limited therapeutic options. However, emerging research highlights the potential of extracellular vesicles (EVs) derived from mesenchymal stem cells as a promising approach to address both the symptoms and underlying pathology of EB. EVs function as carriers of bioactive molecules, modulating inflammation, promoting tissue regeneration, and even delivering functional type VII collagen to RDEB patient cells. Unlike whole-cell therapies, EVs are non-immunogenic, have greater stability, and avoid risks such as graft-versus-host disease or tumorigenic transformation. Additionally, EVs offer diverse administration routes, including topical application, local injection, and intravenous delivery, which could extend their therapeutic reach beyond skin lesions to systemic manifestations of EB. However, challenges remain, including standardization of EV production, scalability, and ensuring consistent therapeutic potency. Despite these hurdles, EV-based therapies represent a transformative step toward addressing the complex pathology of EB, with the potential to improve wound healing, reduce fibrosis, and enhance patient quality of life.</p>","PeriodicalId":8874,"journal":{"name":"Bioengineering","volume":"12 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12189515/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144494080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}