Robotics and ophthalmology: Are we there yet?

Soft Tissue Robotic Assisted Orbital Surgery Using da Vinci SP: A Cadaveric Experience

PURPOSE

Robotic surgical techniques have transformed many surgical specialties however robotic techniques and applications have been much more limited in ophthalmology. This study aims to evaluate the feasibility of robotic assisted orbital surgery using a single-port novel robotic platform, the da Vinci SP.

METHODS

A series of orbital procedures were performed in cadaveric specimens utilizing the da Vinci SP robotic system. The procedures performed included lacrimal gland dissection and biopsy, medial and lateral orbital wall dissections, enucleation, and lid-sparing orbital exenteration. Successful completion of each procedure was defined by the operating surgeon and was considered the primary outcome and marker of feasibility.

RESULTS

Seven cadaveric procedures were performed in 3 cadaveric specimens. All 7 procedures were completed successfully without complication. Setup optimization occurred throughout the study and setup and operative times were acceptable. Three instrument arms and 1 endoscope were utilized throughout the study allowing 3 arm operating and dynamic retraction. Instrument size was found to limit surgical access and precision particular at the orbital apex.

CONCLUSIONS

This preclinical study demonstrates that the da Vinci SP can be utilized within the orbit and is feasible for several applications. Robotic surgical systems offer significant advantages over conventional techniques and should be embraced. However, current commercially available robotic platforms are not optimized for the orbit and have their limitations although they may be suitable for some clinical applications.

Unveiling the Potential: A Comprehensive Review of Artificial Intelligence Applications in Ophthalmology and Future Prospects

Artificial intelligence (AI) has emerged as a transformative force in healthcare, particularly in the field of ophthalmology. This comprehensive review examines the current applications of AI in ophthalmology, highlighting its significant contributions to diagnostic accuracy, treatment efficacy, and patient care. AI technologies, such as deep learning algorithms, have demonstrated exceptional performance in the early detection and diagnosis of various eye conditions, including diabetic retinopathy (DR), age-related macular degeneration (AMD), and glaucoma. Additionally, AI has enhanced the analysis of ophthalmic imaging techniques like optical coherence tomography (OCT) and fundus photography, facilitating more precise disease monitoring and management. The review also explores AI's role in surgical assistance, predictive analytics, and personalized treatment plans, showcasing its potential to revolutionize clinical practice and improve patient outcomes. Despite these advancements, challenges such as data privacy, regulatory hurdles, and ethical considerations remain. The review underscores the need for continued research and collaboration among clinicians, researchers, technology developers, and policymakers to address these challenges and fully harness the potential of AI in improving eye health worldwide. By integrating AI with teleophthalmology and developing AI-driven wearable devices, the future of ophthalmic care promises enhanced accessibility, efficiency, and efficacy, ultimately reducing the global burden of visual impairment and blindness.

Advancements in robotic surgery: innovations, challenges and future prospects

The use of robots has revolutionized healthcare, wherein further innovations have led to improved precision and accuracy. Conceived in the late 1960s, robot-assisted surgeries have evolved to become an integral part of various surgical specialties. Modern robotic surgical systems are equipped with highly dexterous arms and miniaturized instruments that reduce tremors and enable delicate maneuvers. Implementation of advanced materials and designs along with the integration of imaging and visualization technologies have enhanced surgical accuracy and made robots safer and more adaptable to various procedures. Further, the haptic feedback system allows surgeons to determine the consistency of the tissues they are operating upon, without physical contact, thereby preventing injuries due to the application of excess force. With the implementation of teleoperation, surgeons can now overcome geographical limitations and provide specialized healthcare remotely. The use of artificial intelligence (AI) and machine learning (ML) aids in surgical decision-making by improving the recognition of minute and complex anatomical structures. All these advancements have led to faster recovery and fewer complications in patients. However, the substantial cost of robotic systems, their maintenance, the size of the systems and proper surgeon training pose major challenges. Nevertheless, with future advancements such as AI-driven automation, nanorobots, microscopic incision surgeries, semi-automated telerobotic systems, and the impact of 5G connectivity on remote surgery, the growth curve of robotic surgery points to innovation and stands as a testament to the persistent pursuit of progress in healthcare.

Revolutionizing Dental Care: A Comprehensive Review of Artificial Intelligence Applications Among Various Dental Specialties

Since the beginning of recorded history, the human brain has been one of the most intriguing structures for scientists and engineers. Over the centuries, newer technologies have been developed based on principles that seek to mimic their functioning, but the creation of a machine that can think and behave like a human remains an unattainable fantasy. This idea is now known as "artificial intelligence". Dentistry has begun to experience the effects of artificial intelligence (AI). These include image enhancement for radiology, which improves the visibility of dental structures and facilitates disease diagnosis. AI has also been utilized for the identification of periapical lesions and root anatomy in endodontics, as well as for the diagnosis of periodontitis. This review is intended to provide a comprehensive overview of the use of AI in modern dentistry's numerous specialties. The relevant publications published between March 1987 and July 2023 were identified through an exhaustive search. Studies published in English were selected and included data regarding AI applications among various dental specialties. Dental practice involves more than just disease diagnosis, including correlation with clinical findings and administering treatment to patients. AI cannot replace dentists. However, a comprehensive understanding of AI concepts and techniques will be advantageous in the future. AI models for dental applications are currently being developed.

Robotics and cybersurgery in ophthalmology: a current perspective

Ophthalmology is one of the most enriched fields, allowing the domain of artificial intelligence to be part of its point of interest in scientific research. The requirement of specialized microscopes and visualization systems presents a challenge to adapting robotics in ocular surgery. Cyber-surgery has been used in other surgical specialties aided by Da Vinci robotic system. This study focuses on the current perspective of using robotics and cyber-surgery in ophthalmology and highlights factors limiting their progression. A review of literature was performed with the aid of Google Scholar, Pubmed, CINAHL, MEDLINE (N.H.S. Evidence), Cochrane, AMed, EMBASE, PsychINFO, SCOPUS, and Web of Science. Keywords: Cybersurgery, Telesurgery, ophthalmology robotics, Da Vinci robotic system, artificial intelligence in ophthalmology, training on robotic surgery, ethics of the use of robots in medicine, legal aspects, and economics of cybersurgery and robotics. 150 abstracts were reviewed for inclusion, and 68 articles focusing on ophthalmology were included for full-text review. Da Vinci Surgical System has been used to perform a pterygium repair in humans and was successful in ex vivo corneal, strabismus, amniotic membrane, and cataract surgery. Gamma Knife enabled effective treatment of uveal melanoma. Robotics used in ophthalmology were: Da Vinci Surgical System, Intraocular Robotic Interventional Surgical System (IRISS), Johns Hopkins Steady-Hand Eye Robot and smart instruments, and Preceyes' B.V. Cybersurgery is an alternative to overcome distance and the shortage of surgeons. However, cost, availability, legislation, and ethics are factors limiting the progression of these fields. Robotic and cybersurgery in ophthalmology are still in their niche. Cost-effective studies are needed to overcome the delay. Technologies, such as 5G and Tactile Internet, are required to help reduce resource scheduling problems in cybersurgery. In addition, prototype development and the integration of artificial intelligence applications could further enhance the safety and precision of ocular surgery.

Algorithm of segmentation of OCT macular images to analyze the results in patients with age-related macular degeneration

Age-related macular degeneration (AMD) is one of the main causes of loss of sight and hypovision in people over working age. Results of optical coherence tomography (OCT) are essential for diagnostics of the disease. Developing the recommendation system to analyze OCT images will reduce the time to process visual data and decrease the probability of errors while working as a doctor. The purpose of the study was to develop an algorithm of segmentation to analyze the results of macular OCT in patients with AMD. It allows to provide a correct prediction of an AMD stage based on the form of discovered pathologies. A program has been developed in the Python programming language using the Pytorch and TensorFlow libraries. Its quality was estimated using OCT macular images of 51 patients with early, intermediate, late AMD. A segmentation algorithm of OCT images was developed based on convolutional neural network. UNet network was selected as architecture of high-accuracy neural net. The neural net is trained on macular OCT images of 125 patients (197 eyes). The author algorithm displayed 98.1% of properly segmented areas on OCT images, which are the most essential for diagnostics and determination of an AMD stage. Weighted sensitivity and specificity of AMD stage classifier amounted to 83.8% and 84.9% respectively. The developed algorithm is promising as a recommendation system that implements the AMD classification based on data that promote taking decisions regarding the treatment strategy.

Robotic Integration in the Field of Opthalmology and Its Prospects in India

In this paper, an overview of the integration of robotic techniques into surgical fields of ophthalmology is described and the details about the latest advancements and future potentials associated with it are presented. The eye is a small, enclosed space that does not tolerate the misplacement of instruments that general surgery can tolerate. As the retina doesn't regenerate, it is of paramount importance to avoid injury. Furthermore, there are additional limitations of unassisted human hands in terms of dexterity, tremor, and precision in positioning instruments in the eye. Robotics has become a promising solution to these human challenges. The emergence of robotic technology into the domain of rapidly advancing micro-invasive surgery has reduced discomfort in patients and enhanced safety, capabilities, and outcomes. With the arrival of the Femtosecond laser system for robotic cataract surgery in several hospitals in India, the paradigm of robotic surgery has shifted as people started to accept and apply it. Although there is still much to learn in this area, there is growing interest in creating gadgets that perform complete surgical procedures. The fundamental objective of these surgeries would be to increase speed and efficiency without compromising the capacity to increase precision. Major criteria include an acceptable range of motion, the capacity to switch instruments mid-surgery, and simultaneous manipulation of the surgical instrument. Robotic surgery is an already well-established technological advancement employed across the globe by leading surgeons in their fields but its curve in ophthalmology is still under supervision. Just like every other advance, robotics has its own set of disadvantages including but not limited to the costs, limited availability, and long learning curve. Nonetheless, this paper doesn't intend to promote the replacement of surgeons with technology, it's intended to get aware of the utilities of technology to improve care and deliver personal compassionate care. This quest is for the idea of robotics in the ocular field and improvisation of the field.

Robot-Assisted Orbital Fat Decompression Surgery: First in Human

Purpose

To explore the safety and feasibility of robot-assisted orbital fat decompression surgery.

Methods

Ten prospectively enrolled patients (18 eyes) with Graves’ ophthalmopathy underwent robot-assisted orbital fat decompression surgery with the da Vinci Xi surgical system. Intraoperative blood loss, operative time, and complications were recorded. For every patient, the exophthalmos of the operated eyes and Graves’ orbitopathy quality of life (GO-QoL) were measured both preoperatively and 3 months postoperatively to assess the surgical effect.

Results

All surgical procedures were successfully performed. The mean duration to complete the whole procedure was 124.3 ± 33.2 minutes (range, 60–188). The mean intraoperative blood loss was 17.8 ± 6.2 mL (range, 7.5–28). There were neither complications nor unexpected events in terms of either orbital decompression surgery or robot-assisted procedures. The mean exophthalmos was 20.2 ± 1.8 mm before surgery and 17.9 ± 1.4 mm postoperatively (P < 0.0001). The preoperative and postoperative GO-QoL on the visual function arm was 84.38 ± 20.04 and 93.75 ± 9.32, respectively. The preoperative and postoperative GO-QoL on the appearance arm was 42.50 ± 14.97 and 64.38 ± 21.46, respectively (P = 0.027).

Conclusions

The da Vinci Xi surgical system provided the stability, dexterity, and good visualization necessary for orbital fat decompression surgery, indicating the safety and feasibility of robot-assisted orbital fat decompression surgery.

Translational Relevance

Based on a literature search using EMBASE and MEDLINE databases, we believe that this study reports the first in-human results of the safety and effectiveness of da Vinci robot-assisted orbital fat decompression surgery.

Prevalence of work-related musculoskeletal symptoms among young orthopedics during the surgical practice: an intervention study

BACKGROUND

Work-related muscle-skeletal symptoms (WRMS) represent a substantial social and economic impact on the way of work and have a high incidence in surgeons. In the literature, several studies address the impact of WRMS in surgeons performing gynecological, laparoscopic, and robotic surgery, but there are no studies in the field of orthopedic surgery. This pilot study aims to assess the effectiveness of a preventive program to reduce pain.

METHODS

All workers filled in a standardized questionnaire, and postoperative pain in the operating room was quantified using a numeric scale (NAS). The intervention group followed ergonomic principles in the operating room supervised by a physiotherapist and specific physical exercises before and after surgery. Data were analyzed using the statistical program STATA rel. 14.0.

RESULTS

Twenty-one surgeons were assigned to intervention groups and thirty-three to controls. At baseline, the two groups were homogeneous for anthropometric factors, and controls were older and with higher work seniority. Pain perception resulted in high in both groups in many body districts. At follow-up, after three months, the intervention group significantly reduced pain perception in all body districts for the lumbar back, knees, ankles and feet (p<0.05). In the control group, pain perception increased in all body districts investigated.

CONCLUSIONS

We found a high prevalence of WRMS in young orthopedic surgeons, and we demonstrated the effectiveness of a preventive program through targeted ergonomic education and exercises for the most affected body districts.

Three-dimensional telesurgery and remote proctoring over a 5G network

Purpose

To present 2 cases of vitreoretinal surgery performed on a three-dimensional (3D) heads-up display surgical platform with real-time transfer of 3D video over a fifth-generation (5G) cellular network.

Methods

An epiretinal membrane peel and tractional retinal detachment repair performed at Massachusetts Eye and Ear in April 2019 were broadcast live to the Verizon 5G Lab in Cambridge, MA.

Results

Both surgeries were successful. The heads-up digital surgery platform, combined with a 5G network, allowed telesurgical transfer of high-quality 3D vitreoretinal surgery with minimal degradation. Average end-to-end latency was 250 ms, and average round-trip latency was 16 ms. Fine surgical details were observed remotely by a proctoring surgeon and trainee, with real-time communication via mobile phone.

Conclusions

This pilot study represents the first successful demonstration of vitreoretinal surgery transmitted over a 5G network. Telesurgery has the potential to enhance surgical education, provide intraoperative consultation and guidance from expert proctors, and improve patient outcomes, especially in remote and low-resource areas.

Mechanical Properties of Bioengineered Corneal Stroma

For the majority of patients with severe corneal injury or disease, corneal transplantation is the only suitable treatment option. Unfortunately, the demand for donor corneas greatly exceeds the availability. To overcome shortage issues, a myriad of bioengineered constructs have been developed as mimetics of the corneal stroma over the last few decades. Despite the sheer number of bioengineered stromas developed , these implants fail clinical trials exhibiting poor tissue integration and adverse effects in vivo. Such shortcomings can partially be ascribed to poor biomechanical performance. In this review, existing approaches for bioengineering corneal stromal constructs and their mechanical properties are described. The information collected in this review can be used to critically analyze the biomechanical properties of future stromal constructs, which are often overlooked, but can determine the failure or success of corresponding implants.

Impact and Challenges of Integrating Artificial Intelligence and Telemedicine into Clinical Ophthalmology

ABSTRACT

Aging populations and worsening burden of chronic, treatable disease is increasingly creating a global shortfall in ophthalmic care provision. Remote and automated systems carry the promise to expand the scale and potential of health care interventions, and reduce strain on health care services through safe, personalized, efficient, and cost-effective services. However, significant challenges remain. Forward planning in service design is paramount to safeguard patient safety, trust in digital services, data privacy, medico-legal implications, and digital exclusion. We explore the impact and challenges facing patients and clinicians in integrating AI and telemedicine into ophthalmic care-and how these may influence its direction.

Robot-Automated Cartilage Contouring for Complex Ear Reconstruction: A Cadaveric Study

OBJECTIVES/HYPOTHESIS

Auricular reconstruction requiring manual contouring of costal cartilage is complex and time consuming, which could be facilitated by a robot in a fast and precise manner. This feasibility study evaluates the accuracy and speed of robotic contouring of cadaver costal cartilage.

METHODS

An augmented robot with a spherical burr was used on cadaveric rib cartilage. Using a laser scanner, each rib section was converted to a three-dimensional model for preoperative planning. A model ear was also scanned to define a carving path for each piece of cartilage. After being contoured, each specimen was compared against the preoperative plan utilizing deviation maps to analyze topographic accuracy. Contouring times of the robot were compared with 13 retrospectively reviewed cases (2006-2017) by an experienced surgeon.

RESULTS

Scanning the cartilage sections took 24.8 ± 6.8 seconds. Preoperative processing took an additional 29.9 ± 8.9 seconds for the preparation of the contouring path. Once the path was prepared, the robot contoured the specimens with a root mean square error of 0.54 mm and a mean absolute deviation of 0.40 mm. The average time to contour the specimens with the robot was 13 ± 2 minutes compared to 71 ± 6 minutes for the manual contouring in the reviewed cases.

CONCLUSIONS

The accuracy of the robotic system was high, with submillimeter deviations from the preoperative plan. The robot required <20% of the contouring time compared to the experienced surgeon. This represents a fast and accurate alternative to hand-contouring costal cartilage grafts for auricular reconstruction. Laryngoscope, 131:1002-1007, 2021.

[What will cataract surgery look like in the future? Alternatives in the pipeline]

Phacoemulsification is the most frequently performed surgery in the world. Over the past few years, this surgery seems to have reached a plateau with no further innovative breakthroughs. In this paper, we focus on alternatives techniques, the latest innovations, and the research and development pipeline in this field.