History of Computer-Assisted Surgery

State of the Art and Development Trend of Laparoscopic Surgical Robot and Master Manipulator

BACKGROUND

In recent years, laparoscopic surgical robots have rapidly developed. However, most focus on the overall robotic systems, with few summaries on the laparoscopic surgical robots and the master manipulators.

METHODS

This paper provides a summary and analysis of typical laparoscopic surgical robots, including the strengths and limitations of existing laparoscopic surgical robots. Additionally, the master manipulators are analysed and summarised from four aspects: structural design and optimization, time-varying delays, tremor suppression and force feedback. Further classification and summary are made based on the different methods used in each study.

RESULTS

Laparoscopic surgical robots and the master manipulators still have some limitations. Therefore, the development trends of the laparoscopic surgical robots and the master manipulators are discussed from four aspects: structural materials, remote surgery, intelligence and human-machine interaction.

CONCLUSION

With the continuous advancement of technology, laparoscopic surgical robots will play an increasingly important role in the field of surgery.

AI solutions for overcoming delays in telesurgery and telementoring to enhance surgical practice and education

Artificial intelligence (AI) has emerged as a transformative tool in surgery, particularly in telesurgery and telementoring. However, its potential to enhance data transmission efficiency and reliability in these fields remains unclear. While previous reviews have explored the general applications of telesurgery and telementoring in specific surgical contexts, this review uniquely focuses on AI models designed to optimise data transmission and mitigate delays. We conducted a comprehensive literature search on PubMed and IEEE Xplore for studies published in English between 2010 and 2023, focusing on AI-driven, surgery-related, telemedicine, and delay-related research. This review includes methodologies from journals, conferences, and symposiums. Our analysis identified a total of twelve AI studies that focus on optimising network resources, enhancing edge computing, and developing delay-robust predictive applications. Specifically, three studies addressed wireless network resource optimisation, two proposed low-latency control and transfer learning algorithms for edge computing, and seven developed delay-robust applications, five of which focused on motion data, with the remaining two addressing visual and haptic data. These advancements lay the foundation for a truly holistic and context-aware telesurgical experience, significantly transforming remote surgical practice and education. By mapping the current role of AI in addressing delay-related challenges, this review highlights the pressing need for collaborative research to drive the evolution of telesurgery and telementoring in modern robotic surgery.

MT-FiST: A Multi-Task Fine-Grained Spatial-Temporal Framework for Surgical Action Triplet Recognition

Surgical action triplet recognition plays a significant role in helping surgeons facilitate scene analysis and decision-making in computer-assisted surgeries. Compared to traditional context-aware tasks such as phase recognition, surgical action triplets, comprising the instrument, verb, and target, can offer more comprehensive and detailed information. However, current triplet recognition methods fall short in distinguishing the fine-grained subclasses and disregard temporal correlation in action triplets. In this article, we propose a multi-task fine-grained spatial-temporal framework for surgical action triplet recognition named MT-FiST. The proposed method utilizes a multi-label mutual channel loss, which consists of diversity and discriminative components. This loss function decouples global task features into class-aligned features, enabling the learning of more local details from the surgical scene. The proposed framework utilizes partial shared-parameters LSTM units to capture temporal correlations between adjacent frames. We conducted experiments on the CholecT50 dataset proposed in the MICCAI 2021 Surgical Action Triplet Recognition Challenge. Our framework is evaluated on the private test set of the challenge to ensure fair comparisons. Our model apparently outperformed state-of-the-art models in instrument, verb, target, and action triplet recognition tasks, with mAPs of 82.1% (+4.6%), 51.5% (+4.0%), 45.50% (+7.8%), and 35.8% (+3.1%), respectively. The proposed MT-FiST boosts the recognition of surgical action triplets in a context-aware surgical assistant system, further solving multi-task recognition by effective temporal aggregation and fine-grained features.

Fast and precise collision detection for detailed and complex physiological structures

BACKGROUND AND OBJECTIVES

Virtual reality has been proved indispensable in computer-assisted surgery, especially for surgical planning, and simulation systems. Collision detection is an essential part of surgery simulators and its accuracy and computational efficiency play a decisive role in the fidelity of simulations. Nevertheless, current collision detection methods in surgical simulation and planning struggle to meet precise requirements, especially for detailed and complex physiological structures. To address this, the primary objective of this study was to develop a new algorithm that enables fast and precise collision detection to facilitate the improvement of the realism of virtual reality surgical procedures.

METHODS

The method consists of two main parts, bounding spheres formation and two-level collision detection. A specified surface subdivision method is devised to reduce the radius of basic bounding spheres formed by circumcenters of underlying triangles. The spheres are then clustered and adjusted to obtain a compact personalized hierarchy whose position is updated in real time during surgical simulation, followed by two-level collision detection. Triangular facets with collision potential through interaction between hierarchies and then accurate results are obtained by means of precise detection phase. The effectiveness of the algorithm was evaluated in various models and surgical scenarios and was compared with prior relevant implementations.

RESULTS

Results on multiple models demonstrated that the method can generate a personalized hierarchy with fewer and smaller bounding spheres for tight wrapping. Simulation experiments proved that the proposed approach is significantly superior to comparable methods under the premise of error-free detection, even for severe model-model collision.

CONCLUSIONS

The algorithm proposed through this study enables higher numerical efficiency and detection accuracy, which is capable of significantly enlarging the fidelity/realism of haptic simulators and surgical planning methods.

Robotic Technology in Foot and Ankle Surgery: A Comprehensive Review

Recent developments in robotic technologies in the field of orthopaedic surgery have largely been focused on higher volume arthroplasty procedures, with a paucity of attention paid to robotic potential for foot and ankle surgery. The aim of this paper is to summarize past and present developments foot and ankle robotics and describe outcomes associated with these interventions, with specific emphasis on the following topics: translational and preclinical utilization of robotics, deep learning and artificial intelligence modeling in foot and ankle, current applications for robotics in foot and ankle surgery, and therapeutic and orthotic-related utilizations of robotics related to the foot and ankle. Herein, we describe numerous recent robotic advancements across foot and ankle surgery, geared towards optimizing intra-operative performance, improving detection of foot and ankle pathology, understanding ankle kinematics, and rehabilitating post-surgically. Future research should work to incorporate robotics specifically into surgical procedures as other specialties within orthopaedics have done, and to further individualize machinery to patients, with the ultimate goal to improve perioperative and post-operative outcomes.

A Novel Method for Digital Reconstruction of the Mucogingival Borderline in Optical Scans of Dental Plaster Casts

Adequate soft-tissue dimensions have been shown to be crucial for the long-term success of dental implants. To date, there is evidence that placement of dental implants should only be conducted in an area covered with attached gingiva. Modern implant planning software does not visualize soft-tissue dimensions. This study aims to calculate the course of the mucogingival borderline (MG-BL) using statistical shape models (SSM). Visualization of the MG-BL allows the practitioner to consider the soft tissue supply during implant planning. To deploy an SSM of the MG-BL, healthy individuals were examined and the intra-oral anatomy was captured using an intra-oral scanner (IOS). The empirical anatomical data was superimposed and analyzed by principal component analysis. Using a Leave-One-Out Cross Validation (LOOCV), the prediction of the SSM was compared with the original anatomy extracted from IOS. The median error for MG-BL reconstruction was 1.06 mm (0.49–2.15 mm) and 0.81 mm (0.38–1.54 mm) for the maxilla and mandible, respectively. While this method forgoes any technical work or additional patient examination, it represents an effective and digital method for the depiction of soft-tissue dimensions. To achieve clinical applicability, a higher number of datasets has to be implemented in the SSM.

Robotic Surgery: At the Crossroads of a Data Explosion

BACKGROUND

For the last 20 years, controversies in robotic surgery focused on cost reduction, development of new platforms and technologies, creation and validation of curriculum and virtual simulators, and conduction of randomized clinical trials to determine the best applications of robotics [Leal Ghezzi and Campos in World J Surg 40:2550-2557, 2016].

METHODS

This review explores the robotic systems which are currently indicated for use or development in gastrointestinal/abdominal surgery. These systems are reviewed and analyzed for clinical impact in these areas. In a MEDLINE search of articles with the search terms abdominal, gastrointestinal, review and robotic surgery, a total of 4306 total articles as of 2021 were assessed. Publicly available information, highest cited articles and reviews were assessed by the authors to determine the most significant regarding clinical outcomes.

RESULTS

Despite this increased number of articles related to robotic surgery, ongoing controversies have led to limitation in the use of current and future robotic surgery platforms [Connelly et al. in J Robotic Surg 14:155-165, 2020]. Newer robotic platforms have limited studies or analysis that would allow meaningful definite conclusions. A multitude of new scenarios are possible due to this limited information.

CONCLUSION

Robotic surgery is in evolution to a larger conceptual field of computationally enhanced surgery (CES). Various terms have been used in the literature including computer-assisted surgery or digital Surgery [Ranev and Teixeira in Surg Clin North Am 100:209-218, 2020]. With the growth of technological changes inherent in CES, the ability to validate these improvements in outcomes will require new metrics and analytic tools. This learning feedback and metric analysis will generate the new opportunities in simulation, training and application [Julian and Smith in Int J Med Robot 15:e2037, 2019].

Research progress and development trend of surgical robot and surgical instrument arm

BACKGROUND

In recent years, surgical robots have become an indispensable part of the medical field. Surgical robots are increasingly being used in the areas of gynaecological surgery, urological surgery, orthopaedic surgery, general surgery and so forth. In this paper, the development of surgical robots in different operations is reviewed and analysed. In the type of master-slave surgical robotic system, the robotic surgical instrument arms were located in the execution terminal of a surgical robot system, as one of the core components, and directly contact with the patient during the operation, which plays an important role in the efficiency and safety of the operation. In clinical, the arm function and design in different systems varies. Furtherly, the current research progress of robotic surgical instrument arms used in different operations is analysed and summarised. Finally, the challenge and trend are concluded.

METHODS

According to the classification of surgical types, the development of surgical robots for laparoscopic surgery, neurosurgery, orthopaedics and microsurgery are analysed and summarised. Then, focusing on the research of robotic surgical instrument arms, according to structure type, the research and application of straight-rod surgical instrument arm, joint surgical instrument arm and continuous surgical instrument arm are analysed respectively.

RESULTS

According to the discussion and summary of the characteristics of the existing surgical robots and instrument arms, it is concluded that they still have a lot of room for development in the future. Therefore, the development trends of the surgical robot and instrument arm are discussed and analysed in the five aspects of structural materials, modularisation, telemedicine, intelligence and human-machine collaboration.

CONCLUSION

Surgical robots have shown the development trend of miniaturisation, intelligence, autonomy and dexterity. Thereby, in the field of science and technology, the research on the next generation of minimally invasive surgical robots will usher in a peak period of development.

Robotic Revisional Single Anastomosis Duodenoileal Bypass After Sleeve Gastrectomy

Introduction: Single anastomosis duodenoileal bypass with sleeve gastrectomy (SADI-S) is a metabolic operation emerging as an option for patients with morbid obesity. It is a promising revisional procedure for weight regain or suboptimal weight loss after sleeve gastrectomy (SG). Currently, there is limited literature describing robotic revisional SADI-S. This study describes the safety, feasibility, and early outcomes of robotic revisional SADI-S after previous SG. Methods: This is a retrospective review from May 26 2019 to January 31 2021. Perioperative outcomes were analyzed. Results: A total of 16 patients underwent the procedure. There were 11 females (69%) with a mean age of 39 ± 11 years. Mean body mass index (BMI) was 44.0 ± 5.1 kg/m² and median ASA was two. Comorbidities included hypertension (25%), hyperlipidemia (19%), and obstructive sleep apnea (13%). Mean interval from primary to revisional surgery among patients was 5.5 ± 1.4 years. Median operative console time was 110 minutes (IQR = 103-137). There were no intraoperative complications. The median hospital stay was 2 days (IQR = 2-3). Perioperative outcomes included no reoperations, perioperative complications, or deaths. There were two (12.5%) emergency department visits for wound checks without infection but no readmissions. At a median follow-up of 4.5 months (IQR = 1-10), patients had a mean BMI of 38.3 ± 7.3 kg/m² and a mean percent total body weight loss (%TBW) of 12.7%. Conclusions: Initial outcomes suggest that robotic revisional SADI-S after previous SG is feasible and safe. Future studies are needed to evaluate intermediate- and long-term postoperative outcomes.

Progress in robotics for combating infectious diseases

The world was unprepared for the COVID-19 pandemic, and recovery is likely to be a long process. Robots have long been heralded to take on dangerous, dull, and dirty jobs, often in environments that are unsuitable for humans. Could robots be used to fight future pandemics? We review the fundamental requirements for robotics for infectious disease management and outline how robotic technologies can be used in different scenarios, including disease prevention and monitoring, clinical care, laboratory automation, logistics, and maintenance of socioeconomic activities. We also address some of the open challenges for developing advanced robots that are application oriented, reliable, safe, and rapidly deployable when needed. Last, we look at the ethical use of robots and call for globally sustained efforts in order for robots to be ready for future outbreaks.

Five thousand years of minimal access surgery: 1990-present: organisational issues and the rise of the robots

The last 30 years have seen a revolution in the provision of minimal access surgery for many conditions, and technological advances are increasing exponentially. Many instruments are superseded by improved versions before the NHS and publicly funded health services can offer widespread coverage. Although we tend to think of minimal access surgery as a modern concept, Parts I and II of this series have shown that there is a 5000-year history to this specialty and our predecessors laid down many principles which still apply today. During the 19th and early 20th centuries, minimal access surgery was driven forward by visionary individuals, often in the face of opposition from colleagues and the medical establishment. However, in the last 30 years, innovation has been driven more in partnerships between healthcare, scientific, financial, educational and charitable organisations. There are far too many individuals involved to detail every contribution here, but this third part of the series will concentrate on some of the important themes in the development of minimal access surgery to its current status.