Adverse Events in Robotic Surgery: A Retrospective Study of 14 Years of FDA Data

Institutional proficiency and learning curves in robotic-assisted thoracoscopic surgery: a single-center retrospective analysis using the cumulative sum method

Robot-assisted thoracoscopic surgery (RATS) has advanced the field of minimally invasive thoracic surgery. Its learning curve is reportedly shorter than that of video-assisted thoracoscopic surgery. However, few studies have examined how institutional proficiency evolves with the introduction of new surgeons and how this transition impacts surgical outcomes in RATS. This single-center retrospective study, conducted at a university hospital in Japan, included 154 patients who underwent RATS lobectomy between November 2018 and May 2024. The study population consisted of four thoracic surgeons at different stages of RATS experience. Operative metrics and learning curves were evaluated using the cumulative sum method. Trends in operating time, console time, blood loss, and non-console time were analyzed to assess surgeon-specific performance, and complications, if any, were recorded. The mean operating time was 206.5 min, console time was 153.3 min, and mean blood loss was 23.9 g. The lead surgeon demonstrated a typical upward convex learning curve, whereas subsequent surgeons showed smaller peaks. Non-console time increased during transitions between surgeons. Postoperative complications occurred in 13 patients, none of whom required conversion to thoracotomy. Mechanical malfunctions were noted in 11 cases and were resolved without significant delays. This study demonstrated that introducing new surgeons did not compromise institutional proficiency, indicating effective skill transfer. Optimizing training strategies to reduce early inefficiencies remains an important goal. In conclusion, structured training and workflow support may help maintain institutional proficiency during the expansion of RATS programs. Further prospective studies are recommended to validate training models and promote consistent surgical outcomes.

A national cross-sectional analysis of stakeholder views regarding the practice and governance of robotic surgery

The study objective was to explore the views of key national stakeholders regarding the practice and governance of robotic surgery in Ireland. A literature review and analysis by two expert robotic surgeons was used to design a customised questionnaire, interrogating respondent perceptions of key robotic surgical areas, including surgical practice, governance, audit and key performance indicators (KPIs). The questionnaire was disseminated via specialty representatives, inviting responses from robotic surgeons, senior trainees, bedside assistants, clinical nurse managers, hospital management and industry partners. The responses were compiled and analysed, with thematic analysis applied to free-text data. Responses were received from 87 stakeholders, with representation from all invited professional groups, surgical specialties and national geographical regions. The largest respondent cohort was consultant robotic surgeons (n = 61); estimated response rate 76.3%. Most respondents were in favour of proctorship/mentorship arrangements for early-career surgeons, with support expressed for external proctors (80.5%, n = 70), internal proctors (88.5%, n = 77) and peer-to-peer mentoring (87.4%, n = 76). The minimum average number of robotic cases necessary for a trained surgeon to maintain competency was most frequently perceived as 1 per fortnight (39.3%, n = 24), or 1 per week (37.7%, n = 23). The recording of KPIs was believed to be important at both unit level [93.1% (n = 81) agree] and surgeon level (94.3% (n = 82) agree). Ninety-five percent of respondents (n = 83), thought institutions should have robotic governance committees. Strong support [83.9% (n = 73)] was expressed for the creation of a national guideline or governance document for the practice of robotic surgery. This national, pan-specialty robotic surgery stakeholder survey is the first of its kind. It identifies strong national support for continued advances in the training and governance of robotic surgery, with consensus for institutional oversight of robotic surgery and the development of a national guidelines for the conduct of robotic surgery.

Applications of Natural Language Processing in Otolaryngology: A Scoping Review

OBJECTIVE

To review the current literature on the applications of natural language processing (NLP) within the field of otolaryngology.

DATA SOURCES

MEDLINE, EMBASE, SCOPUS, Cochrane Library, Web of Science, and CINAHL.

METHODS

The preferred reporting Items for systematic reviews and meta-analyzes extension for scoping reviews checklist was followed. Databases were searched from the date of inception up to Dec 26, 2023. Original articles on the application of language-based models to otolaryngology patient care and research, regardless of publication date, were included. The studies were classified under the 2011 Oxford CEBM levels of evidence.

RESULTS

One-hundred sixty-six papers with a median publication year of 2024 (range 1982, 2024) were included. Sixty-one percent (102/166) of studies used ChatGPT and were published in 2023 or 2024. Sixty studies used NLP for clinical education and decision support, 42 for patient education, 14 for electronic medical record improvement, 5 for triaging, 4 for trainee education, 4 for patient monitoring, 3 for telemedicine, and 1 for medical translation. For research, 37 studies used NLP for extraction, classification, or analysis of data, 17 for thematic analysis, 5 for evaluating scientific reporting, and 4 for manuscript preparation.

CONCLUSION

The role of NLP in otolaryngology is evolving, with ChatGPT passing OHNS board simulations, though its clinical application requires improvement. NLP shows potential in patient education and post-treatment monitoring. NLP is effective at extracting data from unstructured or large data sets. There is limited research on NLP in trainee education and administrative tasks. Guidelines for NLP use in research are critical.

The Society of Thoracic Surgeons Expert Consensus Statements on a Framework for a Standardized National Robotic Curriculum for Thoracic Surgery Trainees

OBJECTIVE

With robotic technology's rapid growth and integration, an urgent need to bridge the educational gap in thoracic surgical training has emerged. This document, a result of consensus among a group of experts in the practice and training of robotic surgery from The Society of Thoracic Surgeons, aims to provide a framework for a standardized national robotic curriculum for thoracic surgery trainees.

METHODS

The Society of Thoracic Surgeons Task Force on Robotic Thoracic Surgery and Workforce on E-learning and Educational Innovation assembled an expert group with the input of the Thoracic Surgery Director's Association. A focused literature review was performed, and expert consensus statements were developed using a modified Delphi process to address 3 major themes: (1) program expectations, (2) components of training, and (3) assessment and feedback.

RESULTS

A consensus was reached on 12 recommendations. These consensus statements reflect updated insights on developing a standardized robotics curriculum based on the latest literature and current educational experience, focusing on program expectations and educational guidelines to develop an optimal training curriculum.

CONCLUSIONS

The expert panel provides several key recommendations to provide a framework for developing a standardized national robotic thoracic curriculum, which would improve resident education and abridge any educational disparity that may exist among programs.

Training in the use of basic functions of the daVinci Xi® robot: a comparative study of residents' skills

The rapid spread of the robotic surgical system has not been accompanied by an equally rapid creation of standardized training courses for the use of this technology.The purpose of our study was to evaluate skill acquisition in the handling and use of the daVinci Xi by comparing two groups of surgical residents. Surgical residents from the University of Turin were enrolled. The participants were divided into two groups: Group A: residents who had participated in at least 8 robotic surgical procedures, and Group B: residents who had never attended robotic surgery. All were administered two instructional videos on the patient cart and console exercises to be performed. Subsequently, the residents were tested and recorded to be evaluated by a senior surgeon experienced in robotic surgery, according to a previously assessed evaluation score. The time of the procedure was also recorded for each test. Patient cart exercises were completed by all participants. We found statistically significant differences between two groups for the first (p = 0.0000) and third (p = 0.0002) patient cart tests and for every test on the surgeon's console except the endoscope handling exercise. Group A scored higher on the patient cart exercises, and the difference reached statistical significance (p = 0.0001). The placement of a single hand-sewn knot on the silicone suture pad was the only exercise that was not fully completed by all participants and showed no statistical difference. The correlation analysis between surgical experience and final score was significant in Group A. The daVinci Xi robotic platform can be properly operated in its basic functions by young surgeons after a short training program even in the absence of previous exposure to robotic clinical procedure.

Evaluation of current and emerging endoluminal robotic platforms using the IDEAL framework

BACKGROUND

Robotic-assisted endoluminal systems are rapidly evolving within the field of minimally invasive surgery. The IDEAL framework (Idea, Development, Exploration, Assessment, and Surveillance) can be used to evaluate novel technologies. This review provides a summary of current and emerging endoluminal systems using the IDEAL framework.

METHODS

A scoping review was conducted to include all existing and developing robotic-assisted endoluminal systems. Data was collected via virtual interviews, questionnaires, biomedical databases, company websites, and peer-reviewed articles. Key metrics were reported, enabling the assignment of each system to an IDEAL stage.

RESULTS

The review identified 17 distinct systems from 16 companies. Nine systems received regulatory approval in their respective countries. Our evaluation showed that two systems were at the pre-IDEAL Stage 0. Seven systems were in the Idea stage (Stage 1), six systems were in the Development stage (Stage 2) and two systems completed Stage 3. No system underwent long-term study evaluation (Stage 4).

CONCLUSIONS

There is a gap in long-term clinical data of robotic-assisted endoluminal systems, indicated by the absence of systems at Stage 4. Collaborative efforts amongst the medical community, regulatory bodies, and industry specialists are vital to ensure the delivery of evidence-based medicine in the discipline of robotics.

Patient Perspective on Robotic-Assisted Total Joint Arthroplasty

Background

Robotic-assisted total joint arthroplasty (TJA) has gained popularity in recent years. Despite mixed patient and surgeon perceptions, conflicting evidence regarding efficacy and cost-effectiveness in comparison to manual TJA exists. Patients' beliefs surrounding robotic-assisted TJA remain unclear. This study aims to assess patients' expectations on robotic technology in TJA.

Methods

A 9-question survey assessing patient understanding and expectations of the use of robotics in TJA was distributed to preoperative and postoperative hip and knee patients of five surgeons at a high-volume academic center. Responses were descriptively analyzed.

Results

A total of 498 responses were collected. Of all respondents, 69.1% are aware of robotic usage in TJA, 68.5% are interested but unsure of the benefits, and only 19.5% feel it is superior to manual surgery. Most patients did not consider robotic TJA as minimally invasive surgery, with 61.7% stating they are not the same. In addition, 52.3% were not comfortable with extra or longer incisions for robotic procedures. Regarding surgeon choice, 94.9% did not consider if the surgeon is able to perform robotic TJA, 74.4% wanted their surgeon proficient in manual TJA, and 72.4% felt that surgeons who use robotic technology are not more capable than manual surgeons.

Conclusions

Awareness and curiosity of robotic-assisted TJA exists; however, most patients did not appear to acknowledge superiority or benefits over manual surgery. Furthermore, patients appear to prefer surgeon proficiency in manual techniques, which may influence training programs in the future. Surgeons should weigh patient goals, expectations, outcomes, and costs when choosing to perform robotic TJA.

A pan-European survey of robotic training for gastrointestinal surgery: European Robotic Surgery Consensus (ERSC) initiative

BACKGROUND

There has been a recent rapid growth in the adoption of robotic systems across Europe. This study aimed to capture the current state of robotic training in gastrointestinal (GI) surgery and to identify potential challenges and barriers to training within Europe.

METHODS

A pan-European survey was designed to account for the opinion of the following GI surgery groups: (i) experts/independent practitioners; (ii) trainees with robotic access; (iii) trainees without robotic access; (iv) robotic industry representatives. The survey explored various aspects, including stakeholder opinions on bedside assisting, console operations, challenges faced and performance assessment. It was distributed through multiple European surgical societies and industry, in addition to social media and snowball sampling, between December 2023 and March 2024.

RESULTS

A total of 1360 participants responded, with valid/complete responses from 1045 participants across 38 European countries. Six hundred and ninety-five (68.0%) experts and trainees were not aware of a dedicated robotic training curriculum for trainees, with 13/23 (56.5%) industry representatives not incorporating training for trainees in their programme. Among trainees with access to robotic systems, 94/195 (48.2%) had not performed any robotic cases, citing challenges including a lack of certified robotic trainers and training lists. Both experts and trainees agreed that trainees should start bedside assisting and operating on the console earlier than they currently do. Assessment tools of trainee performance were not being used by 139/479 (29.0%) participants.

CONCLUSION

This pan-European survey highlights the need for a standardised robotic curriculum to address the gap in visceral training, assessment and certification. A greater emphasis may be required on implementing robotic training earlier through simulation training, dual console learning, bedside assisting, key clinical performance indicators, and assessment tools. The findings will guide the development of a pan-European consensus on the essential components of a comprehensive training programme for GI robotic surgery.

Computer-aided robotics for applications in fracture reduction surgery: Advances, challenges, and opportunities

The advancement of information technology and AI has boosted global economic and social development. Robot systems (RS) and computer-aided technology (CAT) are used in various domains, including social production and human existence. Traditional fracture reduction surgery relies on the expertise and surgical skills of surgeons to realign fractures in patients. Researchers have developed robotic and assisted systems to automate fracture reduction surgery in recent decades. Computer-aided fracture reduction robot system (CARS) is used to replace the manual reduction performed by conventional physicians. A partial CARS has been used successfully in clinical fracture reduction surgery. This study provides an overview of CARS. First, the RS and CAT used in fracture reduction surgery are overviewed. Furthermore, a comprehensive analysis of CARS is presented, encompassing their design, experimental validation, and clinical applications, while highlighting recent advancements and potential future directions in this domain. The suggested CARS for fracture reduction are compared in different ways. The learning curve and technical ethics of CARS are summarized. The paper addresses unresolved research gaps and technical challenges, providing recommendations to guide future study.

Artificial Intelligence in Cardiac Surgery: Transforming Outcomes and Shaping the Future

Background: Artificial intelligence (AI) has emerged as a transformative technology in healthcare, with its integration into cardiac surgery offering significant advancements in precision, efficiency, and patient outcomes. However, a comprehensive understanding of AI's applications, benefits, challenges, and future directions in cardiac surgery is needed to inform its safe and effective implementation. Methods: A systematic review was conducted following PRISMA guidelines. Literature searches were performed in PubMed, Scopus, Cochrane Library, Google Scholar, and Web of Science, covering publications from January 2000 to November 2024. Studies focusing on AI applications in cardiac surgery, including risk stratification, surgical planning, intraoperative guidance, and postoperative management, were included. Data extraction and quality assessment were conducted using standardized tools, and findings were synthesized narratively. Results: A total of 121 studies were included in this review. AI demonstrated superior predictive capabilities in risk stratification, with machine learning models outperforming traditional scoring systems in mortality and complication prediction. Robotic-assisted systems enhanced surgical precision and minimized trauma, while computer vision and augmented cognition improved intraoperative guidance. Postoperative AI applications showed potential in predicting complications, supporting patient monitoring, and reducing healthcare costs. However, challenges such as data quality, validation, ethical considerations, and integration into clinical workflows remain significant barriers to widespread adoption. Conclusions: AI has the potential to revolutionize cardiac surgery by enhancing decision making, surgical accuracy, and patient outcomes. Addressing limitations related to data quality, bias, validation, and regulatory frameworks is essential for its safe and effective implementation. Future research should focus on interdisciplinary collaboration, robust testing, and the development of ethical and transparent AI systems to ensure equitable and sustainable advancements in cardiac surgery.

Impact of innovative technologies on quality and safety in surgery

Technological advancements gradually lead to the revision and transformation of healthcare, training, and research. Surgery is a field of medicine where the collaboration of human resources and the application of innovative technologies could elevate faithfulness and efficiency. The article, exploring the technologies and analyzing them in terms of their reliability, the benefits of performing precision surgeries, the effectiveness in the outcome of surgery with less psychosomatic fatigue, and the improvements in the training process for surgeons, emphasizes the safety and quality that can be achieved. The study was conducted by searching the relevant papers mainly from 2016-2024 using different online databases such as Web of Science, Google Scholar, and PubMed to examine the impact of adopting new technologies in medicine. This paper highlights that the use of innovative technologies in a wide range of surgical procedures could, by adapting interdisciplinary procedures, provide significant results in issues related to safety, quality, reliability, and training.

Adverse events associated with robotic-assistance in total hip arthroplasty: an analysis based on the FDA MAUDE database

BACKGROUND

The Food and Drug Administration (FDA) maintains the Manufacturer and User Facility Device Experience (MAUDE) database for reporting adverse events associated with medical devices, including emerging technologies, such as robotic-assisted total hip arthroplasty (THA). Aim of this study was to evaluate the variation of adverse events associated with robotics in THA.

METHODS

Medical device reports (MDRs) within the MAUDE database were identified between 2017 and 2021. For MDR identification the product class "orthopaedic stereotaxic equipment" and terms associated with THA were used. Individual adverse events were identified and organised by type and consequences, such as patient injury, surgical delay, or conversion to the manual technique.

RESULTS

521 MDRs constituting 546 discrete events were found. The most common reported complication was intraoperative hardware failure (304/546, 55.7%), among which the most common failure was a broken impaction handle/platform (110, 20.1%). Inaccurate cup placement was the second most common reported complication (63, 11.5%). Abandoning the robot occurred in 13.0% (71/521) of reports. A surgical delay was noted in 28% (146/521) of reports, with an average delay of 17.9 (range 1-60) minutes.

CONCLUSIONS

Identifying complications that may occur with robotics in THA is an important first step in preventing adverse events and surgical delays. Database analysis provide an overview of the range of complications.

Design and Experimental Evaluation of a Leader-follower Robot-assisted System for Femur Fracture Surgery

In the face of challenges encountered during femur fracture surgery, such as the high rates of malalignment and X-ray exposure to operating personnel, robot-assisted surgery has emerged as an alternative to conventional state-of-the-art surgical methods. This paper introduces the development of a leader-follower robot-assisted system for femur fracture surgery, called Robossis. Robossis comprises a 7-DOF haptic controller and a 6-DOF surgical robot. A control architecture is developed to address the kinematic mismatch and the motion transfer between the haptic controller and the Robossis surgical robot. A motion control pipeline is designed to address the motion transfer and evaluated through experimental testing. The analysis illustrates that the Robossis surgical robot can adhere to the desired trajectory from the haptic controller with an average translational error of 0.32 mm and a rotational error of 0.07°. Additionally, a haptic rendering pipeline is developed to resolve the kinematic mismatch by constraining the haptic controller's (user's hand) movement within the permissible joint limits of the Robossis surgical robot. Lastly, in a cadaveric lab test, the Robossis system was tested during a mock femur fracture surgery. The result shows that the Robossis system can provide an intuitive solution for surgeons to perform femur fracture surgery.

Simulation-based training in robotic surgery education: bibliometric analysis and visualization

Simulation-based robotic surgery training may help surgeons gain operative skills and experience in the simulation environment. This bibliometric analysis examined the development of simulation-based training for robotic surgical education. Articles pertaining to robotic surgical simulation training that were included in the Web of Science Core Collection up to April 25, 2024, were included. The temporal patterns in published paper numbers were evaluated using Microsoft Excel software, and the data regarding co-authorship and keyword co-occurrence were analyzed and visualized using the VOSviewer and SCImago Graphica tools. A total of 594 papers on simulation-based training for robotic surgical education were evaluated in this study. The United States and United Kingdom were the leading contributors in this field. The most published authors were Professor Ahmed Kamran (23 publications) and Prokar Dasgupta (22 publications). The highest number of papers was published in the journal titled "Surgical Endoscopy and Other Interventional Techniques." The most common keywords were "virtual reality," "curriculum," "robotic surgery simulator," "assessment," and "learning curve." Our study offers a detailed overview of international research on simulation-based training for robotic surgical education, including the publishing countries, institutions, authors, journals, and research hotspots. It also methodically summarizes the state of knowledge in the area, and provides definite directions and concepts for further in-depth analysis.

Minimizing and managing needle and instrument loss during pediatric robotic surgery

INTRODUCTION

Lost objects and equipment malfunctions during robotic and laparoscopic cases can lead to an increase in operating time and potential risk to the patient. The literature on the management of foreign bodies during pediatric robotic-assisted surgery is limited. The purpose of the video is to review proper instrument handling to prevent loss of an object and to propose our technique for retrieving lost objects through two pediatric case examples.

MATERIALS AND METHODS

The first case is a robotic-assisted laparoscopic left pyeloplasty in a 6-week-old male with congenital uteropelvic junction obstruction during which a needle was lost. In the video, we describe our techniques for safe needle passage, proper suturing technique, and recovering a lost needle. The second case is a robotic-assisted right upper pole heminephrectomy in a 14-month-old female with a duplicated renal collecting system and hydroureteronephrosis. We present the management of a rare case during which a harmonic scalpel jaw malfunctioned leading to a lost foreign body. We describe our technique for retrieving the lost fragment.

RESULTS

All objects were safely removed, and patients were discharged post-op day one without complication.

CONCLUSION

Our video presents two case examples of foreign bodies lost during pediatric robotic surgeries and approaches to manage each of these incidents.

Assessing the Reproducibility of Research Based on the Food and Drug Administration Manufacturer and User Facility Device Experience Data

OBJECTIVE

This article aims to assess the reproducibility of Manufacturer and User Facility Device Experience (MAUDE) data-driven studies by analyzing the data queries used in their research processes.

METHODS

Studies using MAUDE data were sourced from PubMed by searching for "MAUDE" or "Manufacturer and User Facility Device Experience" in titles or abstracts. We manually chose articles with executable queries. The reproducibility of each query was assessed by replicating it in the MAUDE Application Programming Interface. The reproducibility of a query is determined by a reproducibility coefficient that ranges from 0.95 to 1.05. This coefficient is calculated by comparing the number of medical device reports (MDRs) returned by the reproduced queries to the number of reported MDRs in the original studies. We also computed the reproducibility ratio, which is the fraction of reproducible queries in subgroups divided by the query complexity, the device category, and the presence of a data processing flow.

RESULTS

As of August 8, 2022, we identified 523 articles from which 336 contained queries, and 60 of these were executable. Among these, 14 queries were reproducible. Queries using a single field like product code, product class, or brand name showed higher reproducibility (50%, 33.3%, 31.3%) compared with other fields (8.3%, P = 0.037). Single-category device queries exhibited a higher reproducibility ratio than multicategory ones, but without statistical significance (27.1% versus 8.3%, P = 0.321). Studies including a data processing flow had a higher reproducibility ratio than those without, although this difference was not statistically significant (42.9% versus 17.4%, P = 0.107).

CONCLUSIONS

Our findings indicate that the reproducibility of queries in MAUDE data-driven studies is limited. Enhancing this requires the development of more effective MAUDE data query strategies and improved application programming interfaces.

Predictors and Outcomes Associated with Bariatric Robotic Delivery: An MBSAQIP Analysis of 318,151 Patients

Background: The adoption of robotic bariatric surgery has increased dramatically over the last decade. While outcomes comparing bariatric and laparoscopic approaches are debated, little is known about patient factors responsible for the growing delivery of robotic surgery. A better understanding of these factors will help guide the planning of bariatric delivery and resource allocation. Methods: Data were extracted from the MBSAQIP registry from 2020 to 2021. The patient population was organized into primary robot-assisted sleeve gastrectomy or Roux-en-Y gastric bypass (RYGB) versus those who underwent laparoscopic procedures. Bivariate analysis and multivariable logistic regression modeling were conducted to characterize cohort differences and identify independent patient predictors of robotic selection. Results: Of 318,151, 65,951 (20.7%) underwent robot-assisted surgery. Patients undergoing robotic procedures were older (43.4 ± 11.8 vs. 43.1 ± 11.8; p < 0.001) and had higher body mass index (BMI; 45.4 ± 7.9 vs. 45.0 ± 7.6; p < 0.001). Robotic cases had higher rates of medical comorbidities, including sleep apnea, hyperlipidemia, gastroesophageal reflux disease (GERD), and diabetes mellitus. Robotic cases were more likely to undergo RYGB (27.4% vs. 26.4%; p < 0.001). Robotic patients had higher rates of numerous complications, including bleed, reoperation, and reintervention, resulting in higher serious complication rates on multivariate analysis. Independent predictors of robotic selection included increased BMI (aOR 1.02), female sex (aOR 1.04), GERD (aOR 1.12), metabolic dysfunction, RYGB (aOR 1.08), black racial status (aOR 1.11), and lower albumin (aOR 0.84). Conclusions: After adjusting for comorbidities, patients with greater metabolic comorbidities, black racial status, and those undergoing RYGB were more likely to receive robotic surgery. A more comprehensive understanding of patient factors fueling the adoption of robotic delivery, as well as those expected to benefit most, is needed to better guide healthcare resources as the landscape of bariatric surgery continues to evolve.

Ethical Dilemmas of Using Artificial Intelligence in Medicine

BACKGROUND

Artificial intelligence (AI) is considered the fourth industrial revolution that will change the evolution of humanity technically and relationally. Although the term has been around since 1956, it has only recently become apparent that AI can revolutionize technologies and has many applications in the medical field.

AREAS OF UNCERTAINTY

The ethical dilemmas posed by the use of AI in medicine revolve around issues related to informed consent, respect for confidentiality, protection of personal data, and last but not least the accuracy of the information it uses.

DATA SOURCES

A literature search was conducted through PubMed, MEDLINE, Plus, Scopus, and Web of Science (2015-2022) using combinations of keywords, including: AI, future in medicine, and machine learning plus ethical dilemma.

ETHICS AND THERAPEUTIC ADVANCES

The ethical analysis of the issues raised by AI used in medicine must mainly address nonmaleficence and beneficence, both in correlation with patient safety risks, ability versus inability to detect correct information from inadequate or even incorrect information. The development of AI tools that can support medical practice can increase people's access to medical information, to obtain a second opinion, for example, but it is also a source of concern among health care professionals and especially bioethicists about how confidentiality is maintained and how to maintain cybersecurity. Another major risk may be related to the dehumanization of the medical act, given that, at least for now, empathy and compassion are accessible only to human beings.

CONCLUSIONS

AI has not yet managed to overcome certain limits, lacking moral subjectivity, empathy, the level of critical thinking is still insufficient, but no matter who will practice preventive or curative medicine in the next period, they will not be able to ignore AI, which under human control can be an important tool in medical practice.

Exploring robotic total hysterectomies: a multi-site experience with the Senhance Surgical System

Robotic-assisted surgery emerged as a technological advancement in the twentieth century, with gynaecology being a key adopter of this approach. The Senhance Surgical System has gained prominence for total hysterectomies from single-site experiences, but multi-site reporting are still lacking in present literature. This multi-site study, conducted at Klaipeda University Hospital and Academic Teaching Hospital Feldkirch, aimed to explore the safety and feasibility of total hysterectomies with the Senhance Surgical System. The study involved 295 cases, showcasing a well-established routine with minimal procedure times. The average age of the patients was 53.5 years (SD: 10.3 years), ranging from 18 to 80 years. The patients' BMI averaged 25.6 kg/m2 (SD: 6.2 kg/m2), ranging from a minimum of 17.7 kg/m2 to a maximum of 69.5 kg/m2. The duration of surgery varied between 30 and 215 min, with a median of 95 min (IQR: 81-116). The docking time was a median of 3 (IQR: 2-5) min and varied between 1.0 and 30.0 min, with a minimum to a maximum range of 1.0 to 122 min. Conversion (3 cases, 1%) and adverse events (6 cases, 2%) were infrequent. Additionally, robotic malfunctions were recorded minimally in 4,1% (12 cases) of the procedures, and pain on a 0-10 visual pain scale was reduced from mild [2.7 (± 1.2)] one day postoperative to minimal [0.9 (± 0.5)] at discharge. Overall, a great routine with the Senhance Surgical System proves good control and, thus, feasibility and safety. Therefore, the Senhance Surgical System is a viable option for total hysterectomy.

The Role of Robotics in Meeting Institutional Goals: A Unified Strategy to Facilitate Program Excellence

PURPOSE

The rapid expansion of robotic surgical equipment necessitates a review of the needs and challenges faced by hospitals introducing robots for the first time to compete with experienced institutions. The aim of this study was to analyze the impact of robotic surgery on our hospital compared to open and laparoscopic surgery, examine internal transformations, and assess regional, domestic, and international implications.

METHODS

A retrospective review was conducted of electronic medical records (EMRs) from 2019 to 2022 at Inha University Hospital, including patients who underwent common robotic procedures and equivalent open and laparoscopic operations. The study investigated clinical and operational performance changes in the hospital after the introduction of robotic technology. It also evaluated the operational effectiveness of robot implementation in local, national, and international contexts. To facilitate comparison with other hospitals, the data were transmitted to Intuitive Surgical, Inc. for analysis. The study was conducted in compliance with domestic personal information regulations and received approval from our Institutional Review Board.

RESULTS

We analyzed EMR data from 3,147 patients who underwent surgical treatment. Over a period of 3.5 years, the adoption of robotic technology in a hospital setting significantly enhanced the technical skills of all professors involved. The introduction of robotic systems led to increased patient utilization of conventional surgical techniques, as well as a rise in the number of patients choosing robotic surgery. This collective trend contributed to an overall increase in patient numbers. This favorable evaluation of the operational effectiveness of our hospital's robot implementation in the context of local, national, and global factors is expected to positively influence policy changes.

CONCLUSION

Stakeholders should embrace data science and evidence-based techniques to generate valuable insights from objective data, assess the health of robot-assisted surgery programs, and identify opportunities for improvement and excellence.

Assessment of Surgeons' Stress Levels with Digital Sensors during Robot-Assisted Surgery: An Experimental Study

Robot-Assisted Minimally Invasive Surgery (RAMIS) marks a paradigm shift in surgical procedures, enhancing precision and ergonomics. Concurrently it introduces complex stress dynamics and ergonomic challenges regarding the human-robot interface and interaction. This study explores the stress-related aspects of RAMIS, using the da Vinci XI Surgical System and the Sea Spikes model as a standard skill training phantom to establish a link between technological advancement and human factors in RAMIS environments. By employing different physiological and kinematic sensors for heart rate variability, hand movement tracking, and posture analysis, this research aims to develop a framework for quantifying the stress and ergonomic loads applied to surgeons. Preliminary findings reveal significant correlations between stress levels and several of the skill-related metrics measured by external sensors or the SURG-TLX questionnaire. Furthermore, early analysis of this preliminary dataset suggests the potential benefits of applying machine learning for surgeon skill classification and stress analysis. This paper presents the initial findings, identified correlations, and the lessons learned from the clinical setup, aiming to lay down the cornerstones for wider studies in the fields of clinical situation awareness and attention computing.

Proficiency Levels and Validity Evidence for Scoring Metrics for a Virtual Reality and Inanimate Robotic Surgery Simulation Curriculum

OBJECTIVE

Our institution recently implemented a virtual reality (VR) skills curriculum for general surgery residents using the SimNow simulator. Based on a content alignment study, we revised the curriculum to include only 20 of 33 VR tasks and we added 3 previously validated inanimate tasks. The purpose of this study was to establish expert-derived proficiency levels for all tasks and to evaluate the validity of the scoring for the VR tasks.

DESIGN

Two expert robotic surgeons performed 5 repetitions of each VR and inanimate task. The trimmed mean (lowest scoring attempt and outliers [>2 standard deviations] were eliminated) was defined as the expert level for each task. For the VR tasks, expert levels were compared to resident performance to evaluate validity.

SETTING

This study was conducted at the University of Texas Southwestern Medical Center (Dallas, TX), a tertiary care academic teaching hospital.

PARTICIPANTS

Two expert robotic surgeons participated in this study. The data from 42 residents (PGY2-4) who completed the original curriculum was used to represent novice performance.

RESULTS

Comparison of expert levels and resident performance was statistically significant for 15 VR tasks (supporting validity) and approached significance (p = 0.06, 0.09) for 2 VR tasks; expert levels were designated as proficiency levels for these 17 tasks. Group comparisons were clearly not significant (p = 0.2-0.8) for 3 VR tasks; 2 of these 3 tasks were retained as introductory exercises (with 3 repetitions required) and 1 was excluded. For the 3 inanimate tasks, expert levels minus 2 standard deviations were designated as proficiency levels.

CONCLUSIONS

This analysis generated validity evidence for 15 VR tasks and established expert-derived proficiency levels for 17 VR tasks and 3 inanimate tasks. Our proposed curriculum now consists of 19 VR and 3 inanimate tasks using the selected proficiency levels. We anticipate that this design will maximize curriculum efficiency and effectiveness.

Autonomous Nanorobots as Miniaturized Surgeons for Intracellular Applications

Artificial nanorobots have emerged as promising tools for a wide range of biomedical applications, including biosensing, detoxification, and drug delivery. Their unique ability to navigate confined spaces with precise control extends their operational scope to the cellular or subcellular level. By combining tailored surface functionality and propulsion mechanisms, nanorobots demonstrate rapid penetration of cell membranes and efficient internalization, enhancing intracellular delivery capabilities. Moreover, their robust motion within cells enables targeted interactions with intracellular components, such as proteins, molecules, and organelles, leading to superior performance in intracellular biosensing and organelle-targeted cargo delivery. Consequently, nanorobots hold significant potential as miniaturized surgeons capable of directly modulating cellular dynamics and combating metastasis, thereby maximizing therapeutic outcomes for precision therapy. In this review, we provide an overview of the propulsion modes of nanorobots and discuss essential factors to harness propulsive energy from the local environment or external power sources, including structure, material, and engine selection. We then discuss key advancements in nanorobot technology for various intracellular applications. Finally, we address important considerations for future nanorobot design to facilitate their translation into clinical practice and unlock their full potential in biomedical research and healthcare.

Human Factors Integration in Robotic Surgery

OBJECTIVE

Using the example of robotic-assisted surgery (RAS), we explore the methodological and practical challenges of technology integration in surgery, provide examples of evidence-based improvements, and discuss the importance of systems engineering and clinical human factors research and practice.

BACKGROUND

New operating room technologies offer potential benefits for patients and staff, yet also present challenges for physical, procedural, team, and organizational integration. Historically, RAS implementation has focused on establishing the technical skills of the surgeon on the console, and has not systematically addressed the new skills required for other team members, the use of the workspace, or the organizational changes.

RESULTS

Human factors studies of robotic surgery have demonstrated not just the effects of these hidden complexities on people, teams, processes, and proximal outcomes, but also have been able to analyze and explain in detail why they happen and offer methods to address them. We review studies on workload, communication, workflow, workspace, and coordination in robotic surgery, and then discuss the potential for improvement that these studies suggest within the wider healthcare system.

CONCLUSION

There is a growing need to understand and develop approaches to safety and quality improvement through human-systems integration at the frontline of care.Precis: The introduction of robotic surgery has exposed under-acknowledged complexities of introducing complex technology into operating rooms. We explore the methodological and practical challenges, provide examples of evidence-based improvements, and discuss the implications for systems engineering and clinical human factors research and practice.

Tips and tricks in gynaecological robotic surgery

It was the dawn of a new era for robotic surgery when the Food and Drug Administration (FDA) approved da Vinci robotic surgical system for general laparoscopic procedures in 2000. The surgical practice saw a transformative breakthrough towards minimally invasive approach with the ever-increasing uptake of advanced robots proven to benefit patients and surgeons in various ways. However, these innovative machines only complement and enhance a surgeon's operating skills, and with such privilege come responsibilities and new challenges. Heavy reliance on such advanced devices while operating on humans necessitates thorough training and supervision to ensure safe and efficient applications. It is the surgeon's responsibility to direct the procedure constantly and lead other team members who assist during the surgery. In this chapter, we provide miscellaneous tips and tricks that can help beginners navigate through robotic surgery with more confidence and enthusiasm.

ESRU-ESU-YAU_UROTECH Survey on Urology Residents Surgical Training: Are We Ready for Simulation and a Standardized Program?

Background

Currently, the landscape of surgical training is undergoing rapid evolution, marked by the initial implementation of standardized surgical training programs, which are further facilitated by the emergence of new technologies. However, this proliferation is uneven across various countries and hospitals.

Objective

To offer a comprehensive overview of the existing surgical training programs throughout Europe, with a specific focus on the accessibility of simulation resources and standardized surgical programs.

Design setting and participants

A dedicated survey was designed and spread in May 2022 via the European Association of Urology (EAU) mail list, to Young Urologist Office (YUO), Junior membership, European Urology Residents Education Program participants between 2014 and 2022, and other urologists under 40 yr, and via the EAU Newsletter.

Intervention

A 64-item, online-based survey in accordance with the Checklist for Reporting Results of Internet E-Surveys (CHERRIES) using the platform of Survey Monkey (Portland, OR, USA) was realized.

Outcome measurements and statistical analysis

The study involved an assessment of the demographic characteristics. Additionally, it explored the type of center, availability of various surgical approaches, presence of training infrastructure, participation in courses, organization of training, and participants' satisfaction with the training program. The level of satisfaction was evaluated using a Likert-5 scale. The subsequent sections delved into surgical training within the realms of open, laparoscopic, robotic, and endoscopic surgery, each explored separately. Finally, the investigation encompassed the presence of a structured training course and the availability of a duly validated final evaluation process.

Results and limitations

There were 375 responders with a completion rate of 82%. Among them, 75% were identified as male, 50.6% were young urologists, 31.7% were senior residents, and 17.6% were junior residents. A significant majority of participants (69.6%) were affiliated with academic centers. Regarding the presence of dry lab training facilities, only 50.3% of respondents indicated its availability. Among these centers, 46.7% were primarily focused on laparoscopy training. The availability of virtual and wet lab training centers was even more limited, with rates of 31.5% and 16.2%, respectively. Direct patient involvement was reported in 80.5% of cases for open surgery, 58.8% for laparoscopy, 25.0% for robotics, and 78.6% for endourology. It is worth noting that in <25% of instances, training followed a well-defined standardized program comprising both preclinical and clinical modular phases. Finally, the analysis of participant feedback showed that 49.7% of respondents expressed a satisfaction rating of either 4 or 5 points with respect to the training program. The limitations of our study include the low response rate, predominance of participants from academic centers, and absence of responses from individuals not affiliated with the EAU network.

Conclusions

The current distribution of surgical training centers falls short of ensuring widespread access to standardized training programs. Although dry lab facilities are relatively well spread, the availability of wet lab resources remains restricted. Additionally, it appears that many trainees' initial exposure to surgery occurs directly with patients. There is a pressing need for continued endeavors to establish uniform training routes and assessment techniques across various surgical methodologies.

Patient summary

Nowadays, the surgical training landscape is heterogeneous across different countries. The implementation of a standardized training methodology to enhance the overall quality of surgical training and thereby improving patient outcomes is needed.

First experience with the Hugo™ robot-assisted surgery system for endometriosis: A descriptive study

INTRODUCTION

The Medtronic Hugo™ Robot-assisted Surgery (RAS) system was recently approved for clinical use. We explored the safety and feasibility of this system for endometriosis surgery. The primary outcome was safe case completion without major surgical complications (Clavien-Dindo grade ≤2) and no conversion to open surgery or laparoscopy.

MATERIAL AND METHODS

Surgeries for endometriosis performed at the Department of Gynecology, Rigshospitalet, on the Medtronic Hugo™ RAS system were included. Two experienced robotic surgeons performed all surgeries with their usual robotic team. The variables included were patient demographics, peri- and postoperative data, complications and 30-day readmission rate. We used the IDEAL framework 1/2a for surgical innovation in this descriptive study.

RESULTS

The first 12 patients were included. All cases were completed without intraoperative complications or conversion. Four patients experienced Clavien-Dindo grade 1 postoperative complications. No patients were re-admitted within 30 days. Median docking time (17 minutes), console time (87.5 minutes), blood loss (40 mL) and length of hospital stay (1 day) were acceptable compared with previous literature.

CONCLUSIONS

In this pilot study, we found the Medtronic Hugo™ RAS system safe and feasible for robot-assisted surgery for endometriosis. The advent of new robotic systems is welcomed to accelerate the development of technology that will advance surgical care for patients across the globe.

Evaluation status of current and emerging minimally invasive robotic surgical platforms

BACKGROUND

The rapid adoption of robotics within minimally invasive surgical specialties has also seen an explosion of new technology including multi- and single port, natural orifice transluminal endoscopic surgery (NOTES), endoluminal and "on-demand" platforms. This review aims to evaluate the validation status of current and emerging MIS robotic platforms, using the IDEAL Framework.

METHODS

A scoping review exploring robotic minimally invasive surgical devices, technology and systems in use or being developed was performed, including general surgery, gynaecology, urology and cardiothoracics. Systems operating purely outside the abdomen or thorax and endoluminal or natural orifice platforms were excluded. PubMed, Google Scholar, journal reports and information from the public domain were collected. Each company was approached via email for a virtual interview to discover more about the systems and to quality check data. The IDEAL Framework is an internationally accepted tool to evaluate novel surgical technology, consisting of four stages: idea, development/exploration, assessment, and surveillance. An IDEAL stage, synonymous with validation status in this review, was assigned by reviewing the published literature.

RESULTS

21 companies with 23 different robotic platforms were identified for data collection, 13 with national and/or international regulatory approval. Of the 17 multiport systems, 1 is fully evaluated at stage 4, 2 are stage 3, 6 stage 2b, 2 at stage 2a, 2 stage 1, and 4 at the pre-IDEAL stage 0. Of the 6 single-port systems none have been fully evaluated with 1 at stage 3, 3 at stage 1 and 2 at stage 0.

CONCLUSIONS

The majority of existing robotic platforms are currently at the preclinical to developmental and exploratory stage of evaluation. Using the IDEAL framework will ensure that emerging robotic platforms are fully evaluated with long-term data, to inform the surgical workforce and ensure patient safety.

The application of objective clinical human reliability analysis (OCHRA) in the assessment of basic robotic surgical skills

BACKGROUND

Using a validated, objective, and standardised assessment tool to assess progression and competency is essential for basic robotic surgical training programmes. Objective clinical human reliability analysis (OCHRA) is an error-based assessment tool that provides in-depth analysis of individual technical errors. We conducted a feasibility study to assess the concurrent validity and reliability of OCHRA when applied to basic, generic robotic technical skills assessment.

METHODS

Selected basic robotic surgical skill tasks, in virtual reality (VR) and dry lab equivalent, were performed by novice robotic surgeons during an intensive 5-day robotic surgical skills course on da Vinci® X and Xi surgical systems. For each task, we described a hierarchical task analysis. Our developed robotic surgical-specific OCHRA methodology was applied to error events in recorded videos with a standardised definition. Statistical analysis to assess concurrent validity with existing tools and inter-rater reliability were performed.

RESULTS

OCHRA methodology was applied to 272 basic robotic surgical skills tasks performed by 20 novice robotic surgeons. Performance scores improved from the start of the course to the end using all three assessment tools; Global Evaluative Assessment of Robotic Skills (GEARS) [VR: t(19) = - 9.33, p < 0.001] [dry lab: t(19) = - 10.17, p < 0.001], OCHRA [VR: t(19) = 6.33, p < 0.001] [dry lab: t(19) = 10.69, p < 0.001] and automated VR [VR: t(19) = - 8.26, p < 0.001]. Correlation analysis, for OCHRA compared to GEARS and automated VR scores, shows a significant and strong inverse correlation in every VR and dry lab task; OCHRA vs GEARS [VR: mean r = - 0.78, p < 0.001] [dry lab: mean r = - 0.82, p < 0.001] and OCHRA vs automated VR [VR: mean r = - 0.77, p < 0.001]. There is very strong and significant inter-rater reliability between two independent reviewers (r = 0.926, p < 0.001).

CONCLUSION

OCHRA methodology provides a detailed error analysis tool in basic robotic surgical skills with high reliability and concurrent validity with existing tools. OCHRA requires further evaluation in more advanced robotic surgical procedures.

Troubleshooting Robotics During Total Hip and Knee Arthroplasty

The introduction of new surgical technology highlights appreciable concerns; robotic arthroplasty is no exception. Acquiring comprehensive understanding of the robotic technology to avoid complications during surgery and devising troubleshooting strategies to overcome potential difficulties is of paramount importance. Troubleshooting algorithms depend on the stage of the procedure and problem encountered, such as loosening of the pins or array, registration or verification problems, or malfunctioning of the device, which is rare. This article aims to outline reproducible workflows and solutions for troubleshooting during robotic-arm assisted total hip arthroplasty and total knee arthroplasty.

Adverse Events and Morbidity in a Multidisciplinary Pediatric Robotic Surgery Program. A prospective, Observational Study

OBJECTIVE

To report one-year morbidity of robotic-assisted laparoscopic surgery (RALS) in a dedicated, multidisciplinary, pediatric robotic surgery program. Summary Background Data. RALS in pediatric surgery is expanding, but data on morbidity in children is limited.

METHODS

All children who underwent RALS (Da Vinci Xi, Intuitive Surgical, USA) were prospectively included (October 2016 to May 2020; follow-up ≥1 year). Analyzed data: patient characteristics, surgical indication/procedure, intraoperative adverse events (ClassIntra classification), blood transfusion, hospital stay, postoperative complications (Clavien-Dindo).

RESULTS

Three hundred consecutive surgeries were included: urology/gynecology (n=105), digestive surgery (n=83), oncology (n=66), ENT surgery (n=28), thoracic surgery (n=18). Median age and weight at surgery were 9.5 [interquartile range (IQR)=8.8] years and 31 [IQR=29.3] kg, respectively. Over one year, 65 (22%) children presented with ≥1 complication, with Clavien-Dindo ≥III in 14/300 (5%) children at ≤30 days, 7/300 (2%) at 30-90 days, and 12/300 (4%) at >90 days. Perioperative transfusion was necessary in 15 (5%) children, mostly oncological (n=8). Eight (3%) robotic malfunctions were noted, one leading to conversion (laparotomy). Overall conversion rate was 4%. ASA ≥3, weight ≤15 kg, and surgical oncology did not significantly increase the conversion rate, complications, or intraoperative adverse events (ClassIntra ≥2). ASA score was significantly higher in children with complications (Clavien-Dindo ≥III) than without (p=0.01). Median hospital stay was 2 [IQR=3] days. Three children died after a median follow-up of 20 [IQR=16] months.

CONCLUSIONS

RALS is safe, even in the most vulnerable children with a wide scope of indications, age, and weight. Robot-specific complications or malfunctions are scarce.

Early and Long-term Complications of Robotic Assisted Laparoscopy in Infants and Children

BACKGROUND

Robotic-assisted laparoscopy still lacks wide acceptance in infants and children. We developed the service and report the largest single institution experience of complications over a period of 11 years.

METHODS

Between March 2006 and May 2017, consecutive infants and children who underwent robotic assisted laparoscopy under the care of two laparoscopic surgeons were studied. Data for patients, surgeons, year of surgery, operation, and timing, nature, grades of complications were assessed.

RESULTS

A total of 601 robotic procedures (45 different types) were carried out in 539 patients. Of these 31 (5.8%) were converted, none for operative complications. These and another 4 with complicated co-morbidity were excluded, leaving 504 patients for further analysis. There were 60 (11.9%) complications in 57 (11.3%) patients. Mean (SD) age was 7.7 years -/+5.1 with the youngest being 4 weeks. Concomitant or bilateral robotic and non-robotic procedures took place in 8.1% and 13.3% of patients respectively. Significant medical co-morbidity and abdominal scarring were present in 29% and 14.9% of patients respectively. Complications occurred in theatre 1.6%, hospital 5.6%, 28 days 1.2%, and late 3.6%. Mean follow up was 7.6 years -/+ 3.1 SD. Over-all postoperative complication rate was 10.3%: CD grade I 6.5% (33), II 0.6% (3), and IIIa/b 3.2% (16) which included 1.4% (7) re-do surgery. Most (11/16) grade III occurred late. There were no bleeding, grade IV or V complications, surgical mortality, or technology related complications.

CONCLUSIONS

Complications are low even during the learning phase and while developing the new technique. Most complications occurred early and were minor. Most high-grade complications presented late.

LEVELS OF EVIDENCE

2B.

Force-Position Hybrid Compensation Control for Path Deviation in Robot-Assisted Bone Drilling

Bone drilling is a common procedure in orthopedic surgery and is frequently attempted using robot-assisted techniques. However, drilling on rigid, slippery, and steep cortical surfaces, which are frequently encountered in robot-assisted operations due to limited workspace, can lead to tool path deviation. Path deviation can have significant impacts on positioning accuracy, hole quality, and surgical safety. In this paper, we consider the deformation of the tool and the robot as the main factors contributing to path deviation. To address this issue, we establish a multi-stage mechanistic model of tool-bone interaction and develop a stiffness model of the robot. Additionally, a joint stiffness identification method is proposed. To compensate for path deviation in robot-assisted bone drilling, a force-position hybrid compensation control framework is proposed based on the derived models and a compensation strategy of path prediction. Our experimental results validate the effectiveness of the proposed compensation control method. Specifically, the path deviation is significantly reduced by 56.6%, the force of the tool is reduced by 38.5%, and the hole quality is substantially improved. The proposed compensation control method based on a multi-stage mechanistic model and joint stiffness identification method can significantly improve the accuracy and safety of robot-assisted bone drilling.

Developing surgical skill level classification model using visual metrics and a gradient boosting algorithm

Objective

Assessment of surgical skills is crucial for improving training standards and ensuring the quality of primary care. This study aimed to develop a gradient boosting classification model (GBM) to classify surgical expertise into inexperienced, competent, and experienced levels in robot-assisted surgery (RAS) using visual metrics.

Methods

Eye gaze data were recorded from 11 participants performing four subtasks; blunt dissection, retraction, cold dissection, and hot dissection using live pigs and the da Vinci robot. Eye gaze data were used to extract the visual metrics. One expert RAS surgeon evaluated each participant's performance and expertise level using the modified Global Evaluative Assessment of Robotic Skills (GEARS) assessment tool. The extracted visual metrics were used to classify surgical skill levels and to evaluate individual GEARS metrics. Analysis of Variance (ANOVA) was used to test the differences for each feature across skill levels.

Results

Classification accuracies for blunt dissection, retraction, cold dissection, and burn dissection were 95%, 96%, 96%, and 96%, respectively. The time to complete only the retraction was significantly different among the 3 skill levels (p-value = 0.04). Performance was significantly different for 3 categories of surgical skill level for all subtasks (p-values<0.01). The extracted visual metrics were strongly associated with GEARS metrics (R2>0.7 for GEARS metrics evaluation models).

Conclusions

Machine learning (ML) algorithms trained by visual metrics of RAS surgeons can classify surgical skill levels and evaluate GEARS measures. The time to complete a surgical subtask may not be considered a stand-alone factor for skill level assessment.

Vibro-Acoustic Sensing of Instrument Interactions as a Potential Source of Texture-Related Information in Robotic Palpation

The direct tactile assessment of surface textures during palpation is an essential component of open surgery that is impeded in minimally invasive and robot-assisted surgery. When indirectly palpating with a surgical instrument, the structural vibrations from this interaction contain tactile information that can be extracted and analysed. This study investigates the influence of the parameters contact angle α and velocity v→ on the vibro-acoustic signals from this indirect palpation. A 7-DOF robotic arm, a standard surgical instrument, and a vibration measurement system were used to palpate three different materials with varying α and v→. The signals were processed based on continuous wavelet transformation. They showed material-specific signatures in the time-frequency domain that retained their general characteristic for varying α and v→. Energy-related and statistical features were extracted, and supervised classification was performed, where the testing data comprised only signals acquired with different palpation parameters than for training data. The classifiers support vector machine and k-nearest neighbours provided 99.67% and 96.00% accuracy for the differentiation of the materials. The results indicate the robustness of the features against variations in the palpation parameters. This is a prerequisite for an application in minimally invasive surgery but needs to be confirmed in realistic experiments with biological tissues.

Developing a Robotic Surgery Curriculum: Selection of Virtual Reality Drills for Content Alignment

INTRODUCTION

Despite the importance of simulation-based training for robotic surgery, there is no consensus about its training curricula. Recently, a virtual reality (VR) platform (SimNow, Intuitive, Inc) was introduced with 33 VR drills but without evidence of their validity. As part of our creating a new robotic VR curriculum, we assessed the drills' validity through content mapping and the alignment between learning goals and drill content.

METHODS

Three robotically trained surgeons content-mapped all 33 drills for how well the drills incorporated 15 surgery skills and also rated the drills' difficulty, usefulness, relevance, and uniqueness. Drills were added to the new curriculum based on consensus about ratings and historic learner data. The drills were grouped according to similar skill sets and arranged in order of complexity.

RESULTS

The 33 drills were judged to have 12/15 surgery skills as primary goals and 13/15 as secondary goals. Twenty of the 33 drills were selected for inclusion in the new curriculum; these had 11/15 skills as primary goals and 11/15 as secondary goals. However, skills regarding energy sources, atraumatic handling, blunt dissection, fine dissection, and running suturing were poorly represented in the drills. Three previously validated inanimate drills were added to the curriculum to address lacking skill domains.

CONCLUSIONS

We identified 20 of the 33 SimNow drills as a foundation for a robotic surgery curriculum based on content-oriented evidence. We added 3 other drills to address identified gaps in drill content.

Ethics and governance of trustworthy medical artificial intelligence

BACKGROUND

The growing application of artificial intelligence (AI) in healthcare has brought technological breakthroughs to traditional diagnosis and treatment, but it is accompanied by many risks and challenges. These adverse effects are also seen as ethical issues and affect trustworthiness in medical AI and need to be managed through identification, prognosis and monitoring.

METHODS

We adopted a multidisciplinary approach and summarized five subjects that influence the trustworthiness of medical AI: data quality, algorithmic bias, opacity, safety and security, and responsibility attribution, and discussed these factors from the perspectives of technology, law, and healthcare stakeholders and institutions. The ethical framework of ethical values-ethical principles-ethical norms is used to propose corresponding ethical governance countermeasures for trustworthy medical AI from the ethical, legal, and regulatory aspects.

RESULTS

Medical data are primarily unstructured, lacking uniform and standardized annotation, and data quality will directly affect the quality of medical AI algorithm models. Algorithmic bias can affect AI clinical predictions and exacerbate health disparities. The opacity of algorithms affects patients' and doctors' trust in medical AI, and algorithmic errors or security vulnerabilities can pose significant risks and harm to patients. The involvement of medical AI in clinical practices may threaten doctors 'and patients' autonomy and dignity. When accidents occur with medical AI, the responsibility attribution is not clear. All these factors affect people's trust in medical AI.

CONCLUSIONS

In order to make medical AI trustworthy, at the ethical level, the ethical value orientation of promoting human health should first and foremost be considered as the top-level design. At the legal level, current medical AI does not have moral status and humans remain the duty bearers. At the regulatory level, strengthening data quality management, improving algorithm transparency and traceability to reduce algorithm bias, and regulating and reviewing the whole process of the AI industry to control risks are proposed. It is also necessary to encourage multiple parties to discuss and assess AI risks and social impacts, and to strengthen international cooperation and communication.

Surgeon-Guided Robotic Arm Facilitates LIMA Takedown in MIDCAB Surgery

Left internal mammary artery (LIMA) to left anterior descending (LAD) coronary artery bypass has been scientifically proven to have the best patency and long-term results in myocardial revascularization. The latest guidelines suggest minimally invasive LIMA to LAD is the optimal therapy for isolated proximal LAD lesions. The start of a minimally invasive direct coronary artery bypass (MIDCAB) program can be quite challenging as robotic surgery demands high starting costs, while normal thoracoscopic techniques have a longer surgeon learning curve. In this article, we describe to the best of our knowledge the first use of surgeon-guided wristed instruments in LIMA harvesting for MIDCAB surgery. It allows for a facilitated LIMA harvest like in robotic surgery with the comfort of a surgeon constantly standing by the patient, allowing for a faster response time in case of an emergency or the need for instrument exchange. These features result in shorter operating times, lower costs compared with robotic surgery, and faster adoption of this technique for centers just starting MIDCAB surgery.

Deep causal learning for robotic intelligence

This invited Review discusses causal learning in the context of robotic intelligence. The Review introduces the psychological findings on causal learning in human cognition, as well as the traditional statistical solutions for causal discovery and causal inference. Additionally, we examine recent deep causal learning algorithms, with a focus on their architectures and the benefits of using deep nets, and discuss the gap between deep causal learning and the needs of robotic intelligence.

An Early Prospective Clinical Study to Evaluate the Safety and Performance of the Versius Surgical System in Robot-Assisted Cholecystectomy

OBJECTIVE

The aim of this study was to demonstrate the ability of the Versius Surgical System to successfully and safely complete cholecystectomy.

BACKGROUND

The system has been developed in-line with surgeon feedback to overcome limitations of conventional laparoscopy to enhance surgeon experience and patient outcomes. Here we present results from the cholecystectomy cohort from a completed early clinical trial, which was designed to broadly align with Stage 2b of the Idea, Development, Exploration, Assessment, Long-term follow-up framework for surgical innovation.

METHODS

Procedures were performed between March 2019 and September 2020 by surgical teams consisting of a lead surgeon and operating room (OR) assistants. Male or female patients aged 18 years and over and requiring cholecystectomy were enrolled. The primary endpoint was the rate of unplanned conversion from robot-assisted surgery to conventional laparoscopic or open surgery. Adverse events (AEs) and serious AEs were adjudicated by video review of the surgery and patient study reports by an independent Clinical Expert Committee.

RESULTS

Overall, 134/143 (93.7%) cholecystectomies were successfully completed using the device. Of the 9 (6.3%) conversions to another surgical modality, 7 were deemed to be related to the device. A total of 6 serious AEs and 3 AEs occurred in 8 patients (5.6%), resulting in 4 (2.8%) readmissions to hospital within 30 days of surgery and 1 death.

CONCLUSIONS

This study demonstrates cholecystectomy performed using the device is as safe and effective as conventional laparoscopy and supports the implementation of the device on a wider scale, pending instrument modifications, in alignment with Idea, Development, Exploration, Assessment, Long-term follow-up Stage 3 (Assessment).

Advanced diagnostic and therapeutic strategies in nanotechnology for lung cancer

As a highly invasive thoracic malignancy with increasing prevalence, lung cancer is also the most lethal cancer worldwide due to the failure of effective early detection and the limitations of conventional therapeutic strategies for advanced-stage patients. Over the past few decades, nanotechnology has emerged as an important technique to obtain desired features by modifying and manipulating different objects on a molecular level and gained a lot of attention in many fields of medical applications. Studies have shown that in lung cancer, nanotechnology may be more effective and specific than traditional methods for detecting extracellular cancer biomarkers and cancer cells in vitro, as well as imaging cancer in vivo; Nanoscale drug delivery systems have developed rapidly to overcome various forms of multi-drug resistance and reduce detrimental side effects to normal tissues by targeting cancerous tissue precisely. There is no doubt that nanotechnology has the potential to enhance healthcare systems by simplifying and improving cancer diagnostics and treatment. Throughout this review, we summarize and highlight recent developments in nanotechnology applications for lung cancer in diagnosis and therapy. Moreover, the prospects and challenges in the translation of nanotechnology-based diagnostic and therapeutic methods into clinical applications are also discussed.

Safe design of surgical robots - a systematic approach to comprehensive hazard identification

OBJECTIVES

Since the 1980s, robotic arms have been transferred from industrial applications to orthopaedic surgical robotics. Adverse events are frequent and often associated with the adopted powerful and oversized anthropomorphic arms. The FDA's 510(k) pathway encourages building on such systems, leading to the adoption of hazards, which is known as "predicate creep". Additionally, the methodology of hazard identification for medical device development needs improvement.

METHODS

We present an approach to enhance general hazard identification and prevent hazards of predicate creep by using the integrative, scenario-based and multi-perspective Point-of-View (PoV) approach. We also present the Catalogue of Hazards (CoH) as an approach for collecting and systematising hazards for future risk analysis and robot development.

RESULTS

We applied seven predefined PoVs to the use case of robotic laminectomy and identified 133 hazards, mainly coming from HMI analysis and literature. By analysing the MAUDE and recalls databases of the FDA, we were able to classify historical hazards and adopt them into the use case.

CONCLUSIONS

The combination of PoV approach and CoH is suitable for integrating multiple established hazard identification methods, increasing comprehensiveness, and supporting the systematic and hazard-based development of surgical robots.

Helical micro-swimmer: hierarchical tail design and propulsive motility

Helical micro-swimmers have markedly extended the reach of human beings in numerous fields, ranging from in vitro tasks in lab-on-a-chip to in vivo applications for minimally invasive medicine. The previous studies on the propulsive motility optimization of the micro-swimmers mainly focused on the distinct actuation principles (e.g., chemically powered, magnetic- or ultrasound energy-driven) and paid little attention to the structural design of these swimming machines themselves. The improvements of the structures can assist the externally powered motors in providing propulsion in a tiny scale and satisfy the agile locomotion demands. This paper presents the design, mechanics modeling and available experiments of a novel type of hierarchical helical swimming robot that significantly enhances the motility of the helix-based swimmers. Validated by the resistive force theory, our numerical model can well analyze the mechanical properties with a variety of geometric parameters. The motion performance of the hierarchical and conventional helical structures in low Reynolds regimes is presented, highlighting the advantages of hierarchical swimmers over the existing typical swimmers. In addition, the stability and resilience of the hierarchical swimmers can be maintained at a decent level. Moreover, the variable forward velocity resulting from the combined hierarchical structures is investigated here, which can thereby serve as a reliable design strategy. The proposed hierarchical helical design enables enticing opportunities for various device systems of medical robots and bio-integrated electronics.

Conversions in pediatric robot-assisted laparoscopic surgery

BACKGROUND

New technology attracts necessary concerns regarding safety and effectiveness, including the risk and circumstances of conversions. This study analyses our 11-year experience of conversions from a dedicated pediatric robot-assisted laparoscopic surgery service.

METHODS

Consecutive patients were evaluated from a prospective database for the period March 2006 to May 2017. Descriptive and quantitative data for conversions were analysed. Variables were investigated including year of surgery, patient age, operation type, surgeon, and experience.

RESULTS

A total of 539 children underwent 601 procedures. There were 45 different types of procedures. Mean (± SD) age was 7.0 ± 5.2 years, and youngest 4 weeks old. There were 31 conversions (5.8%). Conversion rates were significantly higher in younger children, with rates of 10.0%, 6.1% and 4.2% for age groups 0-2, 2-6, and 6-18 years respectively (p = 0.01). There was a significant difference in conversion rates amongst procedures (p<0.001). Intravesical (9/26, 34.6%), liver cyst (2/8, 25.0%) and choledochal cyst (8/60, 13.3%) procedures were the highest. The most frequent reason for conversion was anesthetic related issues caused by dilated intestine and/or inadequate muscle relaxation (16/31, 52%). Three conversions were attributable to mechanical failures, none attributed to intraoperative complication.

CONCLUSIONS

Conversion rates are low even in the learning phase and comparable favourably to conventional laparoscopy, supporting the safety and effectiveness of robot-assisted technology for advanced laparoscopy in children. The importance of optimization of surgical conditions cannot be overemphasised.

Reporting and grading of complications for intracorporeal robot-assisted radical cystectomy: an in-depth short-term morbidity assessment using the novel Comprehensive Complication Index®

OBJECTIVE

To assess suitability of Comprehensive Complication Index (CCI^®) vs. Clavien-Dindo classification (CDC) to capture 30-day morbidity after robot-assisted radical cystectomy (RARC).

MATERIALS AND METHODS

A total of 128 patients with bladder cancer (BCa) undergoing intracorporeal RARC with pelvic lymph node dissection between 2015 and 2021 were included in a retrospective bi-institutional study, which adhered to standardized reporting criteria. Thirty-day complications were captured according to a procedure-specific catalog. Each complication was graded by the CDC and the CCI^®. Multivariable linear regression (MVA) was used to identify predictors of higher morbidity.

RESULTS

381 complications were identified in 118 patients (92%). 55 (43%), 43 (34%), and 20 (16%) suffered from CDC grade I-II, IIIa, and ≥ IIIb complications, respectively. 16 (13%), 27 (21%), and 2 patients (1.6%) were reoperated, readmitted, and died within 30 days, respectively. 31 patients (24%) were upgraded to most severe complication (CCI^® ≥ 33.7) when calculating morbidity burden compared to corresponding CDC grade accounting only for the highest complication. In MVA, only age was a positive estimate (0.44; 95% CI = 0.03-0.86; p = 0.04) for increased cumulative morbidity.

CONCLUSION

The CCI^® estimates of 30-day morbidity after RARC were substantially higher compared to CDC alone. These measurements are a prerequisite to tailor patient counseling regarding surgical approach, urinary diversion, and comparability of results between institutions.