Annual Review of Biomedical Engineering最新文献

Artificial Intelligence-Based Analysis of Laparoscopic Imaging for Intraoperative Surgical Decision Support. 基于人工智能的腹腔镜影像分析对术中手术决策的支持。

IF 11.5 1区工程技术

Annual Review of Biomedical Engineering Pub Date : 2026-05-01 DOI: 10.1146/annurev-bioeng-110824-114236

Zheyuan Zhang, Pietro Mascagni, Annika Reinke, Pieter De Backer, Wouter Bogaert, Marco Mezzina, Daniel A Donoho, Fiona R Kolbinger

{"title":"Artificial Intelligence-Based Analysis of Laparoscopic Imaging for Intraoperative Surgical Decision Support.","authors":"Zheyuan Zhang, Pietro Mascagni, Annika Reinke, Pieter De Backer, Wouter Bogaert, Marco Mezzina, Daniel A Donoho, Fiona R Kolbinger","doi":"10.1146/annurev-bioeng-110824-114236","DOIUrl":"10.1146/annurev-bioeng-110824-114236","url":null,"abstract":"Across surgical specialties, minimally invasive (laparoscopic) surgery has become a standard technique, as it is associated with less trauma, reduced postoperative complication rates, and quicker recovery for patients as compared with open surgery. Due to the limited field of view and limited haptic feedback, the surgical decision-making process in laparoscopic surgery is currently guided solely by surgeons' visual interpretation of the laparoscopic video stream. Modern artificial intelligence (AI) methods excel at the interpretation of visual data and find applications in clinical routine in fields such as radiology and endoscopy. AI methods could help augment laparoscopic surgery through objective real-time analysis of the laparoscopic video stream. Research studies have demonstrated the feasibility of AI-based surgical scene and process understanding. This review provides an overview of these AI applications, focusing on approaches that could, in the next decade, be translated into intraoperative surgical decision support tools for increased surgical quality and patient safety.","PeriodicalId":50757,"journal":{"name":"Annual Review of Biomedical Engineering","volume":"28 1","pages":"135-162"},"PeriodicalIF":11.5,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147823177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Physics-Informed Machine Learning in Biomedical Science and Engineering. 生物医学科学与工程中的物理信息机器学习。

IF 11.5 1区工程技术

Annual Review of Biomedical Engineering Pub Date : 2026-05-01 DOI: 10.1146/annurev-bioeng-110824-124907

Nazanin Ahmadi, Qianying Cao, Jay D Humphrey, George Em Karniadakis

{"title":"Physics-Informed Machine Learning in Biomedical Science and Engineering.","authors":"Nazanin Ahmadi, Qianying Cao, Jay D Humphrey, George Em Karniadakis","doi":"10.1146/annurev-bioeng-110824-124907","DOIUrl":"10.1146/annurev-bioeng-110824-124907","url":null,"abstract":"Physics-informed machine learning (PIML) is emerging as a potentially transformative paradigm for modeling complex biomedical systems by integrating parameterized physical laws with data-driven methods. Here, we review three main classes of PIML frameworks: physics-informed neural networks (PINNs), neural ordinary differential equations (NODEs), and neural operators (NOs), highlighting their growing role in biomedical science and engineering. We begin with PINNs, which embed governing equations into deep learning models and have been successfully applied to biosolid and biofluid mechanics, mechanobiology, and medical imaging, among other areas. We then review NODEs, which offer continuous-time modeling, especially suited to dynamic physiological systems, pharmacokinetics, and cell signaling. Finally, we discuss deep NOs as powerful tools for learning mappings between function spaces, enabling efficient simulations across multiscale and spatially heterogeneous biological domains. Throughout, we emphasize applications where physical interpretability, data scarcity, or system complexity make conventional black-box learning insufficient. We conclude by identifying open challenges and future directions for advancing PIML in biomedical science and engineering, including issues of uncertainty quantification, generalization, and integration of PIML and large language models.","PeriodicalId":50757,"journal":{"name":"Annual Review of Biomedical Engineering","volume":"28 1","pages":"309-336"},"PeriodicalIF":11.5,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13455127/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147823191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Smart Polymeric Biomaterials for Clinical Use. 用于临床的智能高分子生物材料。

IF 11.5 1区工程技术

Annual Review of Biomedical Engineering Pub Date : 2026-05-01 Epub Date: 2026-02-25 DOI: 10.1146/annurev-bioeng-110824-125943

Natalie M Petryk, Nghia L B Thai, Anita Shukla, Mary Beth B Monroe

{"title":"Smart Polymeric Biomaterials for Clinical Use.","authors":"Natalie M Petryk, Nghia L B Thai, Anita Shukla, Mary Beth B Monroe","doi":"10.1146/annurev-bioeng-110824-125943","DOIUrl":"10.1146/annurev-bioeng-110824-125943","url":null,"abstract":"As biomaterials transition from static, inert objects into dynamic scaffolds that augment the healing process, the ability to design large-scale changes in architecture in response to environmental changes is increasingly valuable. To address this need, stimuli-responsive, or \"smart,\" biomaterials are employed in clinical applications more frequently. These materials are capable of undergoing large and abrupt changes in shape in response to small changes in the environment, such as temperature, pH, mechanical forces, light, magnetic fields, or enzymes. Smart polymeric biomaterials include shape memory polymers, stimuli-responsive hydrogels, and liquid crystal elastomers. These materials are used in a vast range of biomedical applications, including embolic/hemostatic devices, orthopedics, cosmetics, wound healing, drug delivery, neural scaffolds, and infection control, among others. While smart materials can be employed in vitro for biomedical uses, we focus here on materials that have been designed for use in or on the human body. The signals that these materials respond to include those that occur endogenously in vivo and externally applied signals that are controlled by clinicians and/or patients. This review highlights current clinically available devices based on smart materials, smart polymeric biomaterial technologies that are in current clinical trials, and novel materials that are under development for future clinical use.","PeriodicalId":50757,"journal":{"name":"Annual Review of Biomedical Engineering","volume":" ","pages":"567-590"},"PeriodicalIF":11.5,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147291904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Type 1 Diabetes and Islet Encapsulation: From Historical Milestones to Cutting-Edge Advances. 1型糖尿病和胰岛封装：从历史里程碑到前沿进展。

IF 11.5 1区工程技术

Annual Review of Biomedical Engineering Pub Date : 2026-05-01 Epub Date: 2026-01-29 DOI: 10.1146/annurev-bioeng-110824-024435

Sudip Mukherjee, Snehasish Mandal, José Oberholzer, Omid Veiseh

{"title":"Type 1 Diabetes and Islet Encapsulation: From Historical Milestones to Cutting-Edge Advances.","authors":"Sudip Mukherjee, Snehasish Mandal, José Oberholzer, Omid Veiseh","doi":"10.1146/annurev-bioeng-110824-024435","DOIUrl":"10.1146/annurev-bioeng-110824-024435","url":null,"abstract":"Type 1 diabetes (T1D) is a chronic condition in which patients suffer from high blood glucose levels due to the body's inability to produce sufficient insulin. Continuous insulin administration and T1D management are difficult, often leading to hypoglycemic events, insulin resistance, and lower quality of life. Major advancements have been made in recent years, including clinical islet transplantation, but their application is limited by rapid immune rejection and islet destruction. Thus, a necessary paradigm shift has been observed in recent times toward biomaterial-based islet transplantation therapy. The use of biomaterial-based encapsulation addresses major limitations, including immune rejection and hypoxia, and provides a proper cell microenvironment offering greater islet viability. Presently, researchers are more focused on developing a clinically translatable therapy for T1D with the existing knowledge of advanced biomaterial technology. In this review article, we provide a historical perspective, highlighting the developments in the field of islet encapsulation and transplantation, and focus on cutting-edge advancements with modern bioengineering from a clinical perspective.","PeriodicalId":50757,"journal":{"name":"Annual Review of Biomedical Engineering","volume":" ","pages":"187-217"},"PeriodicalIF":11.5,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146087970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Clinically Feasible Approaches to the Real-Time Measurement of Drugs, Metabolites, and Biomarkers in the Living Body. 实时测量活体药物、代谢物和生物标志物的临床可行方法。

IF 11.5 1区工程技术

Annual Review of Biomedical Engineering Pub Date : 2026-05-01 Epub Date: 2026-02-10 DOI: 10.1146/annurev-bioeng-110824-011256

Kristine Y Ma, Heather A Clark, Kevin W Plaxco

{"title":"Clinically Feasible Approaches to the Real-Time Measurement of Drugs, Metabolites, and Biomarkers in the Living Body.","authors":"Kristine Y Ma, Heather A Clark, Kevin W Plaxco","doi":"10.1146/annurev-bioeng-110824-011256","DOIUrl":"10.1146/annurev-bioeng-110824-011256","url":null,"abstract":"The continuous, real-time measurement of specific molecules in situ in the body promises to revolutionize the precision of drug dosing, the reach of physiological research, and the accuracy and timeliness of clinical diagnostics. Motivated by these prospects, here we critically review the set of molecular sensing technologies that (a) have been demonstrated to support seconds-resolved measurements in mammalian subjects and (b) appear translatable to the clinic. The relevant technologies employ four readout modalities: (a) direct or enzymatic electrochemical detection, (b) indirect electrochemical detection, (c) optical strategies, and (d) photoacoustic sensing. For each, we analyze the engineering requirements to support real-time, in vivo operation-which include reversibility, reagentless interrogation, and selectivity-and the remaining barriers to clinical adoption, including sensitivity and long-term in vivo stability and biocompatibility. Collectively, the advances surveyed here suggest that seconds-resolved molecular monitoring in humans is within reach and will herald a new era of precision diagnostics and closed-loop therapeutics.","PeriodicalId":50757,"journal":{"name":"Annual Review of Biomedical Engineering","volume":" ","pages":"445-462"},"PeriodicalIF":11.5,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146159209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Teravoxel Microscopy Image Analysis for Neurological Diseases. 神经系统疾病的三像素显微图像分析。

IF 11.5 1区工程技术

Annual Review of Biomedical Engineering Pub Date : 2026-05-01 Epub Date: 2026-02-10 DOI: 10.1146/annurev-bioeng-110824-012128

Ziquan Wei, Guorong Wu

{"title":"Teravoxel Microscopy Image Analysis for Neurological Diseases.","authors":"Ziquan Wei, Guorong Wu","doi":"10.1146/annurev-bioeng-110824-012128","DOIUrl":"10.1146/annurev-bioeng-110824-012128","url":null,"abstract":"Light-sheet fluorescence microscopy (LSFM) has emerged as a revolutionary imaging modality for investigating intact three-dimensional brain structures at the teravoxel scale. In parallel, high-throughput computational methods, especially deep learning approaches, have opened new avenues for uncovering the pathophysiological mechanisms of neurological diseases through LSFM technology. Recent advances in optics and tissue clearing methods have allowed whole-brain imaging at cellular resolution in three dimensions, and the integration of artificial intelligence has facilitated the identification of disease-related cellular profiles and morphological markers. Machine learning techniques for stitching, segmentation, classification, super-resolution, and registration, therefore, are promoted to uncover biological patterns that are not visible to human eyes yet are related to neuroinflammatory and neurodegenerative diseases. However, analytic pipelines have been designed differently for various animal models and brain structures, leading to challenges in feasibility and compatibility within this emerging field of data-driven LSFM image analysis. Here, we present an overview of current pipelines, examine existing and forthcoming challenges as the LSFM community advances, demonstrate their implications for neurological disease applications, and propose potential solutions.","PeriodicalId":50757,"journal":{"name":"Annual Review of Biomedical Engineering","volume":" ","pages":"361-84"},"PeriodicalIF":11.5,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146159167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Silicon Photonic Biosensors in Clinical Diagnostics: Emerging Opportunities and Challenges. 硅光子生物传感器在临床诊断：新兴的机遇和挑战。

IF 11.5 1区工程技术

Annual Review of Biomedical Engineering Pub Date : 2026-05-01 Epub Date: 2026-01-13 DOI: 10.1146/annurev-bioeng-103023-030143

Patricia Ramirez-Priego, Andrés Alonso-Fernández, Maria Soler, Laura M Lechuga

{"title":"Silicon Photonic Biosensors in Clinical Diagnostics: Emerging Opportunities and Challenges.","authors":"Patricia Ramirez-Priego, Andrés Alonso-Fernández, Maria Soler, Laura M Lechuga","doi":"10.1146/annurev-bioeng-103023-030143","DOIUrl":"10.1146/annurev-bioeng-103023-030143","url":null,"abstract":"As health care systems worldwide seek to decentralize diagnostics and expand precision medicine, silicon photonic biosensors have become a compelling solution. Their development over the past decade, especially in the last 5 years, marks a significant convergence of photonics, nanotechnology, and biomedical engineering that aims to reshape the diagnostic landscape. This review presents a comprehensive analysis of advances in silicon photonic biosensors, focusing on key configurations including microring resonators, photonic crystals, interferometers, and other emerging transduction mechanisms. We discuss the integration of advanced surface functionalization strategies for efficient and robust bioreceptor immobilization, which is critical for reliable biomedical applications. We emphasize the translation of these devices into clinical settings, primarily in infectious diseases and cancer diagnostics. Finally, we address current limitations, such as fabrication complexity, microfluidic integration, and data interpretation, and outline future directions to enhance scalability and clinical adoption in personalized medicine and decentralized health care.","PeriodicalId":50757,"journal":{"name":"Annual Review of Biomedical Engineering","volume":" ","pages":"25-51"},"PeriodicalIF":11.5,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145967755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Therapeutic Applications of Engineered Cell Death, Arrest, and Persistence. 工程细胞死亡、阻滞和持久性的治疗应用。

IF 11.5 1区工程技术

Annual Review of Biomedical Engineering Pub Date : 2026-05-01 Epub Date: 2026-02-10 DOI: 10.1146/annurev-bioeng-110824-021221

Jared W Lee-Kin, Ofelya Baghdasaryan, Luis E Contreras-Llano, Aijun Wang, Cheemeng Tan

引用次数: 0

Multimodal Toxicity of Acrolein and Associated Therapeutic Strategies in Central Nervous System Trauma and Disease. 丙烯醛在中枢神经系统创伤和疾病中的多模态毒性及相关治疗策略。

IF 11.5 1区工程技术

Annual Review of Biomedical Engineering Pub Date : 2026-05-01 Epub Date: 2026-01-21 DOI: 10.1146/annurev-bioeng-103023-035352

Nicholas S Race, Koji Uchida, Philip C Burcham, Riyi Shi

{"title":"Multimodal Toxicity of Acrolein and Associated Therapeutic Strategies in Central Nervous System Trauma and Disease.","authors":"Nicholas S Race, Koji Uchida, Philip C Burcham, Riyi Shi","doi":"10.1146/annurev-bioeng-103023-035352","DOIUrl":"10.1146/annurev-bioeng-103023-035352","url":null,"abstract":"Acrolein is a highly reactive α,β-unsaturated aldehyde produced endogenously through lipid peroxidation and enzymatic metabolism and exogenously via environmental exposures. Acrolein covalently adducts to DNA and proteins, leading to oxidative stress, mitochondrial dysfunction, and inflammation, including innate immune response activation via natural antibodies. Acrolein is difficult to measure in biological systems, but its covalent products can be measured reliably. Therapeutically, nucleophilic small molecules that scavenge acrolein such as hydralazine, phenelzine, dimercaprol, carnosine, and N-acetylcysteine (NAC) have shown neuroprotective effects in animal models of multiple sclerosis, Parkinson's disease, spinal cord injury, and traumatic brain injury. These effects include preserved membrane and mitochondrial integrity, reduced inflammation, reduced pain, and improved motor, sensory, and cognitive outcomes. Alternative strategies that enhance clearance or inhibit production of acrolein show promise but face limitations. Acrolein is a key pathophysiological mediator and a viable therapeutic target in central nervous system trauma and neurodegenerative diseases.","PeriodicalId":50757,"journal":{"name":"Annual Review of Biomedical Engineering","volume":" ","pages":"107-133"},"PeriodicalIF":11.5,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146020450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Advancing Drug Delivery Through Complex Physiological Barriers in the Brain, Lymph Node, and Placenta. 通过脑、淋巴结和胎盘的复杂生理屏障推进药物递送。

IF 11.5 1区工程技术

Annual Review of Biomedical Engineering Pub Date : 2026-05-01 Epub Date: 2026-02-10 DOI: 10.1146/annurev-bioeng-102723-021307

Katherine M Nelson, Michael J Donzanti, Omkar S Mhatre, Jason P Gleghorn

{"title":"Advancing Drug Delivery Through Complex Physiological Barriers in the Brain, Lymph Node, and Placenta.","authors":"Katherine M Nelson, Michael J Donzanti, Omkar S Mhatre, Jason P Gleghorn","doi":"10.1146/annurev-bioeng-102723-021307","DOIUrl":"10.1146/annurev-bioeng-102723-021307","url":null,"abstract":"More than 90% of central nervous system-directed drug candidates fail because they never reach the brain, and similarly formidable physiological tissue barriers protect the placenta and lymph node. These tissues are walled off by tight junctions, efflux pumps, and immune sentinels that thwart both endogenous and exogenous agents, complicating disease treatment. Here, we detail the microanatomy, transport mechanisms, and pathological shifts of the blood-brain, blood-lymph node, and maternal-fetal barriers. We then benchmark emerging solutions, from receptor-targeted nanoparticles and stimulus-responsive carriers to cell-mediated and bioderived vehicles, against the current landscape of US Food and Drug Administration-approved and experimental therapeutics. By comparing the relatively advanced blood-brain barrier delivery techniques to the immature landscape of lymph node and placental drug delivery, we can advance investigation of these tissues quicker. Leveraging tissue-specific physiology promises higher therapeutic indices, lower systemic toxicity, and faster clinical success and illuminates the priority questions that must be answered over the next decade.","PeriodicalId":50757,"journal":{"name":"Annual Review of Biomedical Engineering","volume":" ","pages":"337-359"},"PeriodicalIF":11.5,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146159184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0