Robot-assisted simulated cataract surgery

Visualization of Cataract Surgery Steps With 4D Microscope-Integrated Swept-Source Optical Coherence Tomography in Ex Vivo Porcine Eyes

Purpose

To investigate the visualization capabilities of high-speed swept-source optical coherence tomography (SS-OCT) in cataract surgery.

Methods

Cataract surgery was simulated in wet labs with ex vivo porcine eyes. Each phase of the surgery was visualized with a novel surgical microscope-integrated SS-OCT with a variable imaging speed of over 1 million A-scans per second. It was designed to provide four-dimensional (4D) live-volumetric videos, live B-scans, and volume capture scans.

Results

Four-dimensional videos, B-scans, and volume capture scans of corneal incision, ophthalmic viscosurgical device injection, capsulorrhexis, phacoemulsification, intraocular lens (IOL) injection, and position of unfolded IOL in the capsular bag were recorded. The flexibility of the SS-OCT system allowed us to tailor the scanning parameters to meet the specific demands of dynamic surgical steps and static pauses. The entire length of the eye was recorded in a single scan, and unfolding of the IOL was visualized dynamically.

Conclusions

The presented novel visualization method for fast ophthalmic surgical microscope-integrated intraoperative OCT imaging in cataract surgery allowed the visualization of all major steps of the procedure by achieving large imaging depths covering the entire eye and high acquisition speeds enabling live volumetric 4D-OCT imaging. This promising technology may become an integral part of routine and advanced robotic-assisted cataract surgery in the future.

Translational Relevance

We demonstrate the visualization capabilities of a cutting edge swept-source OCT system integrated into an ophthalmic surgical microscope during cataract surgery.

Artificial Intelligence in Ophthalmic Surgery: Current Applications and Expectations

Artificial Intelligence (AI) has found rapidly growing applications in ophthalmology, achieving robust recognition and classification in most kind of ocular diseases. Ophthalmic surgery is one of the most delicate microsurgery, requiring high fineness and stability of surgeons. The massive demand of the AI assist ophthalmic surgery will constitute an important factor in boosting accelerate precision medicine. In clinical practice, it is instrumental to update and review the considerable evidence of the current AI technologies utilized in the investigation of ophthalmic surgery involved in both the progression and innovation of precision medicine. Bibliographic databases including PubMed and Google Scholar were searched using keywords such as "ophthalmic surgery", "surgical selection", "candidate screening", and "robot-assisted surgery" to find articles about AI technology published from 2018 to 2023. In addition to the Editorials and letters to the editor, all types of approaches are considered. In this paper, we will provide an up-to-date review of artificial intelligence in eye surgery, with a specific focus on its application to candidate screening, surgery selection, postoperative prediction, and real-time intraoperative guidance.

Using the language of surgery to enhance ophthalmology surgical education

Background

Currently, surgical education utilizes a combination of the apprentice model, wet-lab training, and simulation, but due to reliance on subjective data, the quality of teaching and assessment can be variable. The "language of surgery," an established concept in engineering literature whose incorporation into surgical education has been limited, is defined as the description of each surgical maneuver using quantifiable metrics. This concept is different from the traditional notion of surgical language, generally thought of as the qualitative definitions and terminology used by surgeons.

Methods

A literature search was conducted through April 2023 using MEDLINE/PubMed using search terms to investigate wet-lab, virtual simulators, and robotics in ophthalmology, along with the language of surgery and surgical education. Articles published before 2005 were mostly excluded, although a few were included on a case-by-case basis.

Results

Surgical maneuvers can be quantified by leveraging technological advances in virtual simulators, video recordings, and surgical robots to create a language of surgery. By measuring and describing maneuver metrics, the learning surgeon can adjust surgical movements in an appropriately graded fashion that is based on objective and standardized data. The main contribution is outlining a structured education framework that details how surgical education could be improved by incorporating the language of surgery, using ophthalmology surgical education as an example.

Conclusion

By describing each surgical maneuver in quantifiable, objective, and standardized terminology, a language of surgery can be created that can be used to learn, teach, and assess surgical technical skill with an approach that minimizes bias.

Key message

The "language of surgery," defined as the quantification of each surgical movement's characteristics, is an established concept in the engineering literature. Using ophthalmology surgical education as an example, we describe a structured education framework based on the language of surgery to improve surgical education.

Classifications

Surgical education, robotic surgery, ophthalmology, education standardization, computerized assessment, simulations in teaching.

Competencies

Practice-Based Learning and Improvement.

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.

Evolution and Applications of Artificial Intelligence to Cataract Surgery

Topic

Despite significant recent advances in artificial intelligence (AI) technology within several ophthalmic subspecialties, AI seems to be underutilized in the diagnosis and management of cataracts. In this article, we review AI technology that may soon become central to the cataract surgical pathway, from diagnosis to completion of surgery.

Clinical Relevance

This review describes recent advances in AI in the preoperative, intraoperative, and postoperative phase of cataract surgery, demonstrating its impact on the pathway and the surgical team.

Methods

A systematic search of PubMed was conducted to identify relevant publications on the topic of AI for cataract surgery. Articles of high quality and relevance to the topic were selected.

Results

Before surgery, diagnosis and grading of cataracts through AI-based image analysis has been demonstrated in several research settings. Optimal intraocular lens (IOL) power to achieve the desired postoperative refraction can be calculated with a higher degree of accuracy using AI-based modeling compared with traditional IOL formulae. During surgery, innovative AI-based video analysis tools are in development, promoting a paradigm shift for documentation, storage, and cataloging libraries of surgical videos with applications for teaching and training, complication review, and surgical research. Situation-aware computer-assisted devices can be connected to surgical microscopes for automated video capture and cloud storage upload. Artificial intelligence-based software can provide workflow analysis, tool detection, and video segmentation for skill evaluation by the surgeon and the trainee. Mixed reality features, such as real-time intraoperative warnings, may have a role in improving surgical decision-making with the key aim of reducing complications by recognizing surgical risks in advance and alerting the operator to them. For the management of patient flow through the pathway, AI-based mathematical models generating patient referral patterns are in development, as are simulations to optimize operating room use. In the postoperative phase, AI has been shown to predict the posterior capsule status with reasonable accuracy, and can therefore improve the triage pathway in the treatment of posterior capsular opacification.

Discussion

Artificial intelligence for cataract surgery will be as relevant as in other subspecialties of ophthalmology and will eventually constitute a future cornerstone for an enhanced cataract surgery pathway.

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.

Evaluation of ophthalmic surgical simulators for continuous curvilinear capsulorhexis training

PURPOSE

To evaluate performance and assessments by expert surgeons tasked to create a continuous curvilinear capsulorhexis (CCC) on 3 commercially available surgical simulators.

SETTING

Montefiore Medical Center Department of Ophthalmology and Visual Sciences, Bronx, New York.

DESIGN

Randomized, cross-sectional, comparative study.

METHODS

Expert cataract surgeons (N = 7) were tasked to create a 5.5-mm CCC on 3 surgical simulators (Bioniko, Kitaro, and SimulEYE). Surgeons rated how well each simulator approximated human tissue on a modified Likert scale (1 to 7). Duration, size, and number of forceps grabs were evaluated.

RESULTS

7 surgeons performed a total of 63 trials. Bioniko required a greater number (6.53 ± 3.14) of forceps grabs for CCC creation than Kitaro (4.90 ± 2.47, P = .01) and SimulEYE (3.90 ± 1.34, P < .0001). Surgeons created the 5.5-mm CCC most accurately on Bioniko and SimulEYE, with the largest mean CCC performed on Kitaro (8.00 ± 0.84) compared with that on Bioniko (5.24 ± 0.60, P < .0001) and SimulEYE (5.11 ± 0.41, P < .0001). Surgeons spent more time (seconds) performing the CCC on Bioniko (41.95 ± 26.70) than that on Kitaro (32.05 ± 14.99, P = .02) and SimulEYE (28.90 ± 15.18, P = .002). Kitaro (4.56 ± 0.84, P < .0001) and SimulEYE (4.19 ± 0.92, P < .0001) were rated as more realistic than Bioniko (1.38 ± 0.80).

CONCLUSIONS

SimulEYE and Kitaro were believed to most closely approximate human capsular tissue, and surgeons performed the CCC fastest on these models. However, surgeons created a 5.5-mm CCC most accurately on SimulEYE and Bioniko. SimulEYE had the best overall performance and fidelity across all studied metrics; however, each simulator demonstrated its own unique advantages and disadvantages. Larger validation studies will help residency programs best use training tools for novice surgeons.

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.

Clinical Evaluation of an Instrument-Integrated OCT-Based Distance Sensor for Robotic Vitreoretinal Surgery

PURPOSE

To assess the efficacy of an instrument-integrated OCT (iiOCT)-based distance sensor during robotic vitreoretinal surgery using the Preceyes Surgical System (PSS; Preceyes B.V.).

DESIGN

Single-center interventional study.

PARTICIPANTS

Patients requiring vitreoretinal surgery.

METHODS

Five patients were enrolled. Standard preoperative OCT images were obtained. After vitrectomy, a predefined set of actions was performed using the iiOCT-based sensor. Images then were processed to assess the signal-to-noise ratio (SNR) at various angles to the retina and at different distances between the instrument tip and the retinal surface. Preoperative and intraoperative OCT images were compared qualitatively and quantitatively.

MAIN OUTCOMES MEASURES

The feasibility in performing surgical tasks using the iiOCT-based sensor during vitreoretinal surgery, the SNR when imaging the retina, differences among intraoperative and preoperative OCT images, and characteristics of intraoperative retinal movements detected with the iiOCT-based probe.

RESULTS

Surgeons were able to perform all the tasks but one. The PSS was able to maintain a fixed distance. The SNR of the iiOCT-based sensor signal was adequate to determine the distance to the retina and to control the PSS. Analysis of iiOCT-based sensor A-scans identified 3 clearly distinguishable retinal layers, including the inner retinal boundary and the interface at the retinal pigment epithelium-Bruch's membrane. Thickness values differed by less than 5% from that measured by preoperative OCT, indicating its accuracy. The Fourier analysis of iiOCT-based sensor recordings identified anteroposterior retinal movements attributed to heartbeat and respiration.

CONCLUSIONS

This iiOCT-based sensor was tested successfully and promises reliable use during robot-assisted surgery. An iiOCT-based sensor is a promising step toward OCT-guided robotic retinal surgery.

A review of robotic surgical training: establishing a curriculum and credentialing process in ophthalmology

Ophthalmic surgery requires a highly dexterous and precise surgical approach to work within the small confines of the eye, and the use of robotics offers numerous potential advantages to current surgical techniques. However, there is a lag in the development of a comprehensive training and credentialing system for robotic eye surgery, and certification of robotic skills proficiency relies heavily on industry leadership. We conducted a literature review on the curricular elements of established robotics training programs as well as privileging guidelines from various institutions to outline key components in training and credentialing robotic surgeons for ophthalmic surgeries. Based on our literature review and informal discussions between the authors and other robotic ophthalmic experts, we recommend that the overall training framework for robotic ophthalmic trainees proceeds in a stepwise, competency-based manner from didactic learning, to simulation exercises, to finally operative experiences. Nontechnical skills such as device troubleshooting and interprofessional teamwork should also be formally taught and evaluated. In addition, we have developed an assessment tool based on validated global rating scales for surgical skills that may be used to monitor the progress of trainees. Finally, we propose a graduating model for granting privileges to robotic surgeons. Further work will need to be undertaken to assess the feasibility, efficacy and integrity of the training curriculum and credentialing practices for robotic ophthalmic surgery.

State of the Art in Robot-Assisted Eye Surgery

Despite the advantages that robot-assisted surgery can offer to patient care, its use in ophthalmic surgery has not yet progressed to the extent seen in other fields. As such, its use remains limited to research environments, both basic and clinical. The technical specifications for such ophthalmic surgical robots are highly challenging, but rapid progress has been made in recent years, and recent developments in this field ensure that the use of this technology in operating theatres will soon be a real possibility. Fully automated ocular microsurgery, carried out by a robot under the supervision of a surgeon, is likely to become our new reality. This review discusses the use of robot-assisted ophthalmic surgery, the recent progress in the field, and the necessary future developments which must occur before its use in operating theatres becomes routine.

ROBOT-ASSISTED VITREORETINAL SURGERY IMPROVES SURGICAL ACCURACY COMPARED WITH MANUAL SURGERY: A Randomized Trial in a Simulated Setting

Robot-assisted vitreoretinal surgery increases precision and limits tissue damage compared with manual surgery especially for the novice surgeon. The Eyesi Simulator is a feasible platform for investigating robot-assisted vitreoretinal surgery.

Purpose:

To compare manual and robot-assisted vitreoretinal surgery using a virtual-reality surgical simulator.

Methods:

Randomized controlled crossover study. Ten experienced vitreoretinal surgeons and 10 novice ophthalmic surgeons were included. The participants were randomized to start with either manual or robot-assisted surgery. Participants completed a test session consisting of three vitreoretinal modules on the Eyesi virtual-reality simulator. The automated metrics of performance supplied by the Eyesi simulator were used as outcome measures. Primary outcome measures were time with instruments inserted (seconds), instrument movement (mm), and tissue treatment (mm²).

Results:

Robot-assisted surgery was slower than manual surgery for both novices and vitreoretinal surgeons, 0.24 SD units (P = 0.024) and 0.73 SD units (P < 0.001), respectively. Robot-assisted surgery allowed for greater precision in novices and vitreoretinal surgeons, −0.96 SD units (P < 0.001) and −0.47 SD units (P < 0.001), respectively. Finally, novices using robot-assisted surgery inflicted less tissue damage when compared with that using manual surgery, −0.59 SD units (P = 0.009).

Conclusion:

At the cost of time, robot-assisted vitreoretinal surgery seems to improve precision and limit tissue damage compared with that of manual surgery. In particular, the performance of novice surgeons is enhanced with robot-assisted vitreoretinal surgery.

Anterior Segment and Others in Teleophthalmology: Past, Present, and Future

ABSTRACT

Teleophthalmology, a subfield of telemedicine, has recently been widely applied in ophthalmic disease management, accelerated by ubiquitous connectivity via mobile computing and communication applications. Teleophthalmology has strengths in overcoming geographic barriers and broadening access to medical resources, as a supplement to face-to-face clinical settings. Eyes, especially the anterior segment, are one of the most researched superficial parts of the human body. Therefore, ophthalmic images, easily captured by portable devices, have been widely applied in teleophthalmology, boosted by advancements in software and hardware in recent years. This review aims to revise current teleophthalmology applications in the anterior segment and other diseases from a temporal and spatial perspective, and summarize common scenarios in teleophthalmology, including screening, diagnosis, treatment, monitoring, postoperative follow-up, and tele-education of patients and clinical practitioners. Further, challenges in the current application of teleophthalmology and the future development of teleophthalmology are discussed.

Robotic posterior capsule polishing by optical coherence tomography image guidance

BACKGROUND

In cataract surgery, polishing of the posterior capsule (PC) can lead to improved surgical outcomes but is currently avoided due to its high-risk nature. This work developed a robotic system capable of performing PC polishing on ex vivo pig eyes using optical coherence tomography (OCT) guidance.

METHODS

The lenses of five ex vivo pig eyes were extracted and a thin layer of glue deposited onto the PC. Transpupillary OCT scans of the anterior segment were used to generate a PC-polishing trajectory. During polishing, OCT B-scans tracked the tool tip and were displayed to the operator.

RESULTS

Complete removal of the glue was accomplished in all five trials with no PC rupture reported.

CONCLUSIONS

The feasibility of using a robotic system guided by OCT to perform PC polishing on a biological model was demonstrated. Contributions include modelling of the PC anatomy, intraoperative OCT visualization, and automated tool-tip motion with scheduled aspiration pressures.

[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.

Robot-Assisted Simulated Strabismus Surgery

Purpose

This study aims to investigate the feasibility of robot-assisted simulated strabismus surgery using the new da Vinci Xi Surgical System and to report what we believe is the first use of a surgical robot in experimental eye muscle surgery.

Methods

Robot-assisted strabismus surgeries were performed on a strabismus eye model using the robotic da Vinci Xi Surgical System. On the lateral rectus of each eye, we performed a procedure including, successively, a 4-mm plication followed by a 4-mm recession of the muscle to end with a 4-mm resection. Operative time from conjunctival opening to closing and successful completion of the different steps with or without complications or unexpected events were assessed.

Results

Robot-assisted strabismus procedures were successfully performed on six eyes. The feasibility of robot-assisted simulated strabismus surgery is confirmed. The da Vinci Xi system provided the appropriate dexterity and operative field visualization necessary to perform conjunctival and Tenon's capsule opening and closing, muscle identification, suturing, desinsertion, sectioning, and resuturing. The mean duration to complete the whole procedure was 27 minutes (range, 22–35). There were no complications or unexpected intraoperative events.

Conclusions

Experimental robot-assisted strabismus surgery is technically feasible using the new robotic da Vinci Xi Surgical System. This is, to our knowledge, the first use of a surgical robot in ocular muscle surgery.

Translational Relevance

Further experimentation will allow the advantages of robot-assisted microsurgery to be identified while underlining the improvements and innovations necessary for clinical use.

Development of a new valid and reliable microsurgical skill assessment scale for ophthalmology residents

Background

More and more concerns have been arisen about the ability of new medical graduates to meet the demands of today’s practice environment. In this study, we wanted to develop a valid, reliable and standardized assessment tool for evaluating the basic microsurgical skills of residents in a microsurgery laboratory, to get them well prepared before entering the surgical realm of ophthalmology.

Methods

Twenty-three experts who have teaching experience reviewed the assessment scale. Constructive comments were incorporated to ensure face and content validity. Twenty-one attendings from different specialties then graded eight corneal rupture suturing videos with the scale to investigate interrater reliability. Fourteen of them graded the same videos 3 months later to investigate intrarater reliability (repeatability).

Results

A total of 280 assessment scales were completed. All the ICC values of interrater reliability were greater than 0.8 with 75% data greater than 0.9 (range 0.860–0.976). All the ICC values of intrarater reliability (repeatability) were also greater than 0.8 with 63% data greater than 0.9 (range 0.833–0.954).

Conclusions

The assessment scale we developed is valid and reliable. This tool could be useful to ensure that junior residents achieve a certain level of microsurgical technique in a laboratory environment before training in the operation room. Hopefully, this tool will provide a structured template for other residency programs to assess their residents for basic microsurgical skills.