Advances in Medical Image Segmentation: A Comprehensive Review of Traditional, Deep Learning and Hybrid Approaches.

Medical image segmentation plays a critical role in accurate diagnosis and treatment planning, enabling precise analysis across a wide range of clinical tasks. This review begins by offering a comprehensive overview of traditional segmentation techniques, including thresholding, edge-based methods, region-based approaches, clustering, and graph-based segmentation. While these methods are computationally efficient and interpretable, they often face significant challenges when applied to complex, noisy, or variable medical images. The central focus of this review is the transformative impact of deep learning on medical image segmentation. We delve into prominent deep learning architectures such as Convolutional Neural Networks (CNNs), Fully Convolutional Networks (FCNs), U-Net, Recurrent Neural Networks (RNNs), Adversarial Networks (GANs), and Autoencoders (AEs). Each architecture is analyzed in terms of its structural foundation and specific application to medical image segmentation, illustrating how these models have enhanced segmentation accuracy across various clinical contexts. Finally, the review examines the integration of deep learning with traditional segmentation methods, addressing the limitations of both approaches. These hybrid strategies offer improved segmentation performance, particularly in challenging scenarios involving weak edges, noise, or inconsistent intensities. By synthesizing recent advancements, this review provides a detailed resource for researchers and practitioners, offering valuable insights into the current landscape and future directions of medical image segmentation.

Leveraging Machine Learning for Optimized Mechanical Properties and 3D Printing of PLA/cHAP for Bone Implant.

This study explores the fabrication and characterisation of 3D-printed polylactic acid (PLA) scaffolds reinforced with calcium hydroxyapatite (cHAP) for bone tissue engineering applications. By varying the cHAP content, we aimed to enhance PLA scaffolds' mechanical and thermal properties, making them suitable for load-bearing biomedical applications. The results indicate that increasing cHAP content improves the tensile and compressive strength of the scaffolds, although it also increases brittleness. Notably, incorporating cHAP at 7.5% and 10% significantly enhances thermal stability and mechanical performance, with properties comparable to or exceeding those of human cancellous bone. Furthermore, this study integrates machine learning techniques to predict the mechanical properties of these composites, employing algorithms such as XGBoost and AdaBoost. The models demonstrated high predictive accuracy, with R2 scores of 0.9173 and 0.8772 for compressive and tensile strength, respectively. These findings highlight the potential of using data-driven approaches to optimise material properties autonomously, offering significant implications for developing custom-tailored scaffolds in bone tissue engineering and regenerative medicine. The study underscores the promise of PLA/cHAP composites as viable candidates for advanced biomedical applications, particularly in creating patient-specific implants with improved mechanical and thermal characteristics.

Biological Scaffolds in 3D Cell Models: Driving Innovation in Drug Discovery.

The discipline of 3D cell modeling is currently undergoing a surge of captivating developments that are enhancing the realism and utility of tissue simulations. Using bioinks which represent cells, scaffolds, and growth factors scientists can construct intricate tissue architectures layer by layer using innovations like 3D bioprinting. Drug testing can be accelerated and organ functions more precisely replicated owing to the precise control that microfluidic technologies and organ-on-chip devices offer over the cellular environment. Tissue engineering is becoming more dynamic with materials that can modify their surroundings with the advent of hydrogels and smart biomaterials. Advances in spheroids and organoids are not only bringing us towards more effective and customized therapies, but they are also improving their ability to resemble actual human tissues. Confocal and two-photon microscopy are examples of advanced imaging methods that provide precise images of the functioning and interaction of cells. Artificial Intelligence models have applications for enhanced scaffold designs and for predicting the response of tissues to medications. Furthermore, via strengthening predictive models, optimizing data analysis, and simplifying 3D cell culture design, artificial intelligence is revolutionizing this field. When combined, these technologies are improving our ability to conduct research and moving us toward more individualized and effective medical interventions.

An efficient approach for EMG controlled pattern recognition system based on MUAP identification and segregation.

An Electromyography (EMG) based pattern recognition system constitutes various steps of signal processing and control engineering from signal acquisition to real-time control. Efficient control of external devices largely depends on the signal processing steps executed before the final output. This work presents a new approach to signal processing using Motor Unit Action Potential (MUAP) based signal decomposition and segmentation. An MUAP is a neurological response during muscle contraction. Due to the higher contact area of surface electrodes, MUAPs from multiple muscles are captured. An MUAP generated from a single muscle usually has identical waveshapes and similar discharging rates and usually lasts for 8-15 ms. These are known as primary MUAPs. The proposed algorithm identifies and uses the primary observed MUAPs for feature extraction and classification. Firstly, noise signals are eliminated by a determined noise margin, which also separates the active muscle movement signals. Next, a novel MUAP identification algorithm is implemented to detect the MUAP trains. Then, identified primary MUAPs are used to make segments with variable widths to extract feature vectors. Based on the correlation score of all the primary MUAPs, the segmentation is performed, which results in segmentation width varying from 110-200 ms. The achieved segmentation width is lesser than the conventional overlapping and non-overlapping methods - the proposed approach results in a 20 to 50% reduction in the segmentation width. Four different classifiers are tested during the machine learning stage to investigate the performance of the proposed approach. The obtained feature sets are then used to train the Linear Discriminant Analysis (LDA), K-Nearest Neighbor (kNN), Decision Tree (DT), and Random Forest (RF) classifiers. The classifiers are tested with precision, recall, F1 score, and accuracy. The kNN and DT classifiers performed better than the LDA and RF classifiers. The maximum precision and recall are 100% while the maximum achieved accuracy is 98.56%. The comparative results show higher accuracy even at lower segmentation widths than the conventional constant window scheme. The kNN and DT classifiers provide a 5% to 15% increment in accuracy compared to the constant window segmentation-based approach.

Influence of different parameters on the corneal asphericity (Q value) assessed with progress in biomedical optics and imaging - A review.

The corneal eye diseases such as Keratoconus cause weakening of the cornea, with this disease the cornea can change in shape. This condition affects between 1 in 3,000 to 1 in 10,000 people. The main reason for the development of such conditions is unknown and can have significant impacts. Over the last decade, with advancements in computerized corneal topography assessments, researchers have increasingly expressed interest in corneal topography for research as well as clinical activities. Up till now, several aspheric numerical models have been developed as well as proposed to define the complex shape of the cornea. A commonly used term for characterizing the asphericity in an eye is the Q value, a common indicator of the aspherical degree of the cornea. It is one of the critical parameters in the mathematical description model of the cornea as it represents the cornea's shape and the eye's characteristics. Due to the utmost importance of this Q value of the cornea, a couple of studies have attempted to explore this parameter and its distribution, merely in terms of its influence on the human eye's optical properties. The corneal Q value is an important factor that needs to be determined to treat for any refractive errors as corneal degeneration are disease that can lead to potential problems with the structure of the cornea. This study aims to highlight the need to understand Q value of the cornea as this can essentially assist with personalising corneal refractive surgeries and implantation of intraocular lenses. Therefore, the relevance of corneal Q value must be studied in association with different patients, especially ones who have been diagnosed with cataracts, brain tumours, or even COVID-19. To address this issue, this paper first carries out a literature review on the optics of the cornea, the relevance of corneal Q value in ophthalmic practice and studies corneal degenerations and its causes. Thereafter, a detailed review of several noteworthy relevant research studies examining the Q value of the cornea is performed. To do so, an elaborate database is created, which presents a list of different research works examined in this study and provides key evidence derived from these studies. This includes listing details on the age, gender, ethnicity of the eyes assessed, the control variables, the technology used in the study, and even more. The database also delivers important findings and conclusions noted in each study assessed. Next, this paper analyses and discusses the magnitude of corneal Q value in various scenarios and the influence of different parameters on corneal Q value. To design visual optical products as well as to enhance the understanding of the optical properties of an eye, future studies could consider the database and work presented in this study as useful references. In addition, the work can be used to make informed decisions in clinical practice for designing visual optical products as well as to enhance the understanding of the optical properties of an Eye.

Konjac glucomannan exerts regulatory effects on macrophages and its applications in biomedical engineering.

Konjac glucomannan (KGM) molecular chains contain a small amount of acetyl groups and a large number of hydroxyl groups, thereby exhibiting exceptional water retention and gel-forming properties. To meet diverse requirements, KGM undergoes modification processes such as oxidation, acetylation, grafting, and cationization, which reduce its viscosity, enhance its mechanical strength, and improve its water solubility. Researchers have found that KGM and its derivatives can regulate the polarization of macrophages, inducing their transformation into classically activated M1-type macrophages or alternatively activated M2-type macrophages, and even facilitating the interconversion between M1 and M2 phenotypes. Concurrently, the modulation of macrophage polarization states holds significant importance for chronic wound healing, inflammatory bowel disease (IBD), antitumor therapy, tissue engineering scaffolds, oral vaccines, pulmonary delivery, and probiotics. Therefore, KGM has the advantages of both immunomodulatory effects (biological activity) and gel-forming properties (physicochemical properties), giving it significant advantages in a variety of biomedical engineering applications.

Advances in agar-based composites: A comprehensive review.

This review article explores the developments and applications in agar-based composites (ABCs), emphasizing various constituents such as metals, clay/ceramic, graphene, and polymers across diversified fields like wastewater treatment, drug delivery, food packaging, the energy sector, biomedical engineering, bioplastics, agriculture, and cosmetics. The focus is on agar as a sustainable and versatile biodegradable polysaccharide, highlighting research that has advanced the technology of ABCs. A bibliometric analysis is conducted using the Web of Science database, covering publications from January 2020 to March 2024, processed through VOSviewer Software Version 1.6.2. This analysis assesses evolving trends and scopes in the literature, visualizing co-words and themes that underscore the growing importance and potential of ABCs in various applications. This review paper contributes by showcasing the existing state-of-the-art knowledge and motivating further development in this promising field.

Eggshell derived scaffold of hydroxyapatite-ammonium bicarbonate nano-composite: Bioactivity and cytotoxicity studies.

This work investigated the facile synthesis of porous scaffold eggshell derived hydroxylapatite (ESHAp) as a composite with ammonium bicarbonate (AMB) for potential biomaterial in tissue engineering application. The phase purity, composition, size, functional groups and morphology of the apatite were elucidated using high resolution transmission electron microscopy (HTEM), X-Ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FT-IR) and scanning electron microscopy (SEM). The results showed that hydroxylapatite (HAp) nanoparticles have round morphologies with average diameters between 20 nm and 80 nm, FT-IR analysis confirmed significant hydroxylapatite functional groups like carbonate, phosphate, and hydroxyl groups, while XRD analysis revealed a well crystalline monophasic HAp powder. The scaffold samples containing 10, 20, 25 and 30 % of AMB withstood a compressive stress up to 5, 20, 30 and 42 N/mm2 respectively which indicates that the compressive stress increased with the AMB content introduced as the pore forming agent. MTT assay performed using MG63 osteosarcoma cell lines showed that on comparing the sample of ESTHAp which contained 0 % AMB with other samples in the range of 0.01-1 mM, viability of above 85 % MG63 cells was achieved except for ESTHAp with 40 % AMB, which showed some level of toxicity. The cell adhesion studies of sintered ESTHAp porous scaffold with different weight percent of the pore forming agents using inverted microscopic images of MG 63 cells incubated with ESTHAp samples and treated with heat at 1000 °C appeared to be unstable in the media used with particle leaching observed, and no cells observed near to the samples.

Label-free functional imaging of vagus nerve stimulation-evoked potentials at the cortical surface.

Vagus nerve stimulation (VNS) is an FDA-approved stimulation therapy to treat patients with refractory epilepsy. In this work, we use a coherent holographic imaging system to characterize vagus nerve-evoked potentials (VEPs) in the cortex in response to VNS stimulation paradigms without electrode placement or any genetic, structural, or functional labels. We analyze stimulation amplitude up to saturation, pulse width up to 800 µs, and frequency from 10 Hz to 30 Hz, finding that stimulation amplitude strongly modulates VEPs response magnitude (effect size 0.401), while pulse width has a moderate modulatory effect (effect size 0.127) and frequency has almost no modulatory effect (effect size 0.009) on the evoked potential magnitude. We find mild interactions between pulse width and frequency. This non-contact label-free functional imaging technique may serve as a non-invasive rapid-feedback tool to characterize VEPs and may increase the efficacy of VNS in patients with refractory epilepsy.

Nanocellulose in targeted drug delivery: A review of modifications and synergistic applications.

Nanocellulose, a versatile biopolymer renowned for its exceptional physicochemical attributes including lightweight, biocompatibility, biodegradability, and higher mechanical strength properties has captured significant attention in biomedical research. This renewable material, extracted from widely abundant biosources including plants, bacteria, and algae, exists in three primary forms: cellulose-based nanocrystals (CNCs), nanofibrils (CNFs), and bacterial nanocellulose (BNC). CNCs are characterized by their highly crystalline, needle-shaped structure, while CNFs possess a blend of amorphous and crystalline regions. BNC stands out as the purest form of nanocellulose. Chemical functionalization enables precise tuning of nanocellulose properties, enhancing its suitability for diverse biomedical applications. In drug delivery systems, nanocellulose's unique structure and surface chemistry offer opportunities for targeted delivery of active molecules. Surface-modified nanocellulose can effectively deliver drugs to specific sites, utilizing its inherent properties to control drug release kinetics and improve therapeutic outcomes. Despite these advantages, challenges such as achieving optimal drug loading capacity and ensuring sustained drug release remain. Future research aims to address these challenges and explore novel applications of nano-structured cellulose in targeted drug delivery, highlighting the continued evolution of this promising biomaterial in biomedicine. Furthermore, the review delves into the impact of chemical, physical, and enzymatic methods for CNC surface modifications, showcasing how these approaches enhance the functionalization of CNCs for targeted delivery of different compounds in biological systems.

Engineering with Biomedical Sciences Changing the Horizon of Healthcare-A Review.

In the dynamic realm of healthcare, the convergence of engineering and biomedical sciences has emerged as a pivotal frontier. In this review we go into specific areas of innovation, including medical imaging and diagnosis, developments in biomedical sensors, and drug delivery systems. Wearable biosensors, non-wearable biosensors, and biochips, which include gene chips, protein chips, and cell chips, are all included in the scope of the topic that pertains to biomedical sensors. Extensive research is conducted on drug delivery systems, spanning topics such as the integration of computer modeling, the optimization of drug formulations, and the design of delivery devices. Furthermore, the paper investigates intelligent drug delivery methods, which encompass stimuli-responsive systems such as temperature, redox, pH, light, enzyme, and magnetic responsive systems. In addition to that, the review goes into topics such as tissue engineering, regenerative medicine, biomedical robotics, automation, biomechanics, and the utilization of green biomaterials. The purpose of this analysis is to provide insights that will enhance continuing research and development efforts in engineering-driven biomedical breakthroughs, ultimately contributing to the improvement of healthcare. These insights will be provided by addressing difficulties and highlighting future prospects.

• Integration of engineering into diagnostics leads to early disease detection through medical imaging.• Biosensors offer cost-effective, simple, and reliable early detection of abnormal health parameters. A smart drug delivery system requires fewer drugs compared to conventional methods.• Use of natural materials will enhance the biocompatibility of nanomaterials.• Nanomaterial enhanced tissue regeneration.

Advances in Novel Biomaterial-Based Strategies for Spinal Cord Injury Treatment.

Spinal cord injury (SCI) is a highly disabling neurological disorder. Its pathological process comprises an initial acute injury phase (primary injury) and a secondary injury phase (subsequent chronic injury). Although surgical, drug, and cell therapies have made some progress in treating SCI, there is no exact therapeutic strategy for treating SCI and promoting nerve regeneration due to the complexity of the pathological SCI process. The development of novel drug delivery systems to treat SCI is expected to significantly impact the individualized treatment of SCI due to its unique and excellent properties, such as active targeting and controlled release. In this review, we first describe the pathological progression of the SCI response, including primary and secondary injuries. Next, we provide a concise overview of newly developed nanoplatforms and their potential application in regulating and treating different pathological processes of SCI. Then, we introduce the existing potential problems and future clinical application perspectives of biomedical engineering-based therapies for SCI.

Harnessing exosomes for targeted therapy: strategy and application.

Exosomes, nanoscopic extracellular vesicles produced by cells, are pivotal in mediating intracellular communication by transporting nucleic acids, proteins, lipids, and other bioactive molecules, thereby influencing physiological and pathological states. Their endogenous origin and inherent diversity confer distinct advantages over synthetic vehicles like liposomes and nanoparticles in diagnostic and therapeutic applications. Despite their potential, the clinical utility of exosomes is hampered by challenges such as limited storage stability, yield, purity, and targeting efficiency. This review focuses on exosomes as targeted therapeutic agents, examining their biogenesis, classification, isolation, and characterisation, while also addressing the current limitations in yield, purity, and targeting. We delve into the literature to propose optimisation strategies that can enhance their therapeutic efficacy and accelerate the translation of exosome-based therapies into clinical practice.

Robust Differentiation of Human Pluripotent Stem Cells into Lymphatic Endothelial Cells Using Transcription Factors.

INTRODUCTION: Generating new lymphatic vessels has been postulated as an innovative therapeutic strategy for various disease phenotypes, including neurodegenerative diseases, metabolic syndrome, cardiovascular disease, and lymphedema. Yet, compared to the blood vascular system, protocols to differentiate human induced pluripotent stem cells (hiPSCs) into lymphatic endothelial cells (LECs) are still lacking. METHODS: Transcription factors, ETS2 and ETV2 are key regulators of embryonic vascular development, including lymphatic specification. While ETV2 has been shown to efficiently generate blood endothelial cells, little is known about ETS2 and its role in lymphatic differentiation. Here, we describe a method for rapid and efficient generation of LECs using transcription factors, ETS2 and ETV2. RESULTS: This approach reproducibly differentiates four diverse hiPSCs into LECs with exceedingly high efficiency. Timely activation of ETS2 was critical, to enable its interaction with Prox1, a master lymphatic regulator. Differentiated LECs express key lymphatic markers, VEGFR3, LYVE-1, and Podoplanin, in comparable levels to mature LECs. The differentiated LECs are able to assemble into stable lymphatic vascular networks in vitro, and secrete key lymphangiocrine, reelin. CONCLUSION: Overall, our protocol has broad applications for basic study of lymphatic biology, as well as toward various approaches in lymphatic regeneration and personalized medicine.

Efficient Light-Based Bioprinting via Rutin Nanoparticle Photoinhibitor for Advanced Biomedical Applications.

Digital light processing (DLP) bioprinting, known for its high resolution and speed, enables the precise spatial arrangement of biomaterials and has become integral to advancing tissue engineering and regenerative medicine. Nevertheless, inherent light scattering presents significant challenges to the fidelity of the manufactured structures. Herein, we introduce a photoinhibition strategy based on Rutin nanoparticles (Rnps), attenuating the scattering effect through concurrent photoabsorption and free radical reaction. Compared to the widely utilized biocompatible photoabsorber tartrazine (Tar), Rnps-infused bioink enhanced printing speed (1.9×), interlayer homogeneity (58% less overexposure), resolution (38.3% improvement), and print tolerance (3× high-precision range) to minimize trial-and-error. The biocompatible and antioxidative Rnps significantly improved cytocompatibility and exhibited resistance to oxidative stress-induced damage in printed constructs, as demonstrated with human induced pluripotent stem cell-derived endothelial cells (hiPSC-ECs). The related properties of Rnps facilitate the facile fabrication of multimaterial, heterogeneous, and cell-laden biomimetic constructs with intricate structures. The developed photoinhibitor, with its profound adaptability, promises wide biomedical applications tailored to specific biological requirements.

Imperceptible augmentation of living systems with organic bioelectronic fibres.

The functional and sensory augmentation of living structures, such as human skin and plant epidermis, with electronics can be used to create platforms for health management and environmental monitoring. Ideally, such bioelectronic interfaces should not obstruct the inherent sensations and physiological changes of their hosts. The full life cycle of the interfaces should also be designed to minimize their environmental footprint. Here we report imperceptible augmentation of living systems through in situ tethering of organic bioelectronic fibres. Using an orbital spinning technique, substrate-free and open fibre networks-which are based on poly (3,4-ethylenedioxythiophene):polystyrene sulfonate-can be tethered to biological surfaces, including fingertips, chick embryos and plants. We use customizable fibre networks to create on-skin electrodes that can record electrocardiogram and electromyography signals, skin-gated organic electrochemical transistors and augmented touch and plant interfaces. We also show that the fibres can be used to couple prefabricated microelectronics and electronic textiles, and that the fibres can be repaired, upgraded and recycled.

Dispersion strategies of nanomaterials in polymeric inks for efficient 3D printing of soft and smart 3D structures: A systematic review.

Nanoscience-often summarized as "the future is tiny"-highlights the work of researchers advancing nanotechnology through incremental innovations. The design and innovation of new nanomaterials are vital for the development of next-generation three-dimensional (3D) printed structures characterized by low cost, high speed, and versatile capabilities, delivering exceptional performance in advanced applications. The integration of nanofillers into polymeric-based inks for 3D printing heralds a new era in additive manufacturing, allowing for the creation of custom-designed 3D objects with enhanced multifunctionality. To optimize the use of nanomaterials in 3D printing, effective disaggregation techniques and strong interfacial adhesion between nanofillers and polymer matrices are essential. This review provides an overview of the application of various types of nanomaterials used in 3D printing, focusing on their functionalization principles, dispersion strategies, and colloidal stability, as well as the methodologies for aligning nanofillers within the 3D printing framework. It discusses dispersive methods, synergistic dispersion, and in-situ growth, which have yielded smart 3D-printed structures with unique functionality for specific applications. This review also focuses on nanomaterial alignment in 3D printing, detailing methods that enhance selective deposition and orientation of nanofillers within established and customized printing techniques. By emphasizing alignment strategies, we explore their impact on the performance of 3D-printed composites and highlight potential applications that benefit from ordered nanoparticles. Through these continuing efforts, this review shows that the design and development of the new class of nanomaterials are crucial to developing the next generation of smart 3D printed architectures with versatile abilities for advanced structures with exceptional performance.

An Open-Source 3D-Printed Recording Stage with Customizable Chambers for Ex Vivo Experiments.

Much of what has been discovered concerning neurophysiological mechanisms can be credited to ex vivo biomedical experiments. Beyond these discoveries, ex vivo research techniques have enhanced the global understanding of human physiology and pathology in almost every biomedical specialty. Naturally, ex vivo experiments are among the most desired methods of research, particularly in the field of neuroscience. Ex vivo experiment platforms may be purchased commercially. However, their substantial cost and sometimes limited availability can render them inaccessible to many research labs. Moreover, these manufactured systems are often rigid in function with no possibility of customization, severely narrowing their capabilities. However, developing essential components for ex vivo laboratory systems with a fused deposition modeling printer provides a practical solution to each of these obstacles. Here, we provide the designs and construction process for an easily accessible, highly adaptable recording stage with modifiable submersion chambers using a 3D printer for a total cost under $15.00. With the versatility afforded by the exchangeable custom chambers, the system may be used to conduct research on a variety of ex vivo tissue preparations, paving the way for novel research.

Curvature-Assisted Vesicle Explosion Under Light-Induced Asymmetric Oxidation.

Exposure of cell membranes to reactive oxygen species can cause oxidation of membrane lipids. Oxidized lipids undergo drastic conformational changes, compromising the mechanical integrity of the membrane and causing cell death. For giant unilamellar vesicles, a classic cell mimetic system, a range of mechanical responses under oxidative assault has been observed including formation of nanopores, transient micron-sized pores, and total sudden catastrophic collapse (i.e., explosion). However, the physical mechanism regarding how lipid oxidation causes vesicles to explode remains elusive. Here, with light-induced asymmetric oxidation experiments, the role of spontaneous curvature on vesicle instability and its link to the conformational changes of oxidized lipid products is systematically investigated. A comprehensive membrane model is proposed for pore-opening dynamics incorporating spontaneous curvature and membrane curling, which captures the experimental observations well. The kinetics of lipid oxidation are further characterized and how light-induced asymmetric oxidation generates spontaneous curvature in a non-monotonic temporal manner is rationalized. Using the framework, a phase diagram with an analytical criterion to predict transient pore formation or catastrophic vesicle collapse is provided. The work can shed light on understanding biomembrane stability under oxidative assault and strategizing release dynamics of vesicle-based drug delivery systems.

Smart Glasses in Surgery: The Theatre and Beyond.

AIMS & OBJECTIVES: The primary aim of this paper is to determine whether smart glasses or head-mounted displays improve efficiency in a procedural or theatre setting without compromising the quality of the procedure performed. Additionally, this paper aims to qualitatively explore applications in surgical education, whilst on-call, consulting and patient observation. DESIGN: This paper is a systematic review of the literature available on the topic of smart glasses or head-mounted displays in surgical or procedural settings. METHODS: A search of Pubmed, Cochrane and the Wiley Online Library was performed in accordance with the PRISMA guidelines. Procedural times and adverse outcomes were compared between the smart glass and non-smart glass groups in each of the quantitative studies. A literature review of studies, including those not satisfying the primary aim was conducted and is included in this paper. RESULTS: 32 studies were identified that complied with the inclusion criteria of this paper. 8 of these studies focused on procedural times and adverse outcomes, with and without smart glass usage. Procedural time was reduced when smart glass technology was used, without an increase in adverse patient outcomes. CONCLUSIONS: Surgeons should consider whether the relatively short reduction in procedural time is worth the high cost, privacy issues, battery complaints and user discomfort involved with these devices. There are promising applications of this technology in the areas of surgical education and consultation. However, more trials are necessary to assess the value of using smart glasses in these settings.