Next-generation robotics in gastrointestinal surgery

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.

Clinical applications of robotic surgery platforms: a comprehensive review

Robotic surgery has expanded globally across various medical specialties since its inception more than 20 years ago. Accompanying this expansion were significant technological improvements, providing tremendous benefits to patients and allowing the surgeon to perform with more precision and accuracy. This review lists some of the different types of platforms available for use in various clinical applications. We performed a literature review of PubMed and Web of Science databases in May 2023, searching for all available articles describing surgical robotic platforms from January 2000 (the year of the first approved surgical robot, da Vinci® System, by Intuitive Surgical) until May 1st, 2023. All retrieved robotic platforms were then divided according to their clinical application into four distinct groups: soft tissue robotic platforms, orthopedic robotic platforms, neurosurgery and spine platforms, and endoluminal robotic platforms. Robotic surgical technology has undergone a rapid expansion over the last few years. Currently, multiple robotic platforms with specialty-specific applications are entering the market. Many of the fields of surgery are now embracing robotic surgical technology. We review some of the most important systems in clinical practice at this time.

Human robotic surgery with intraoperative tissue identification using rapid evaporation ionisation mass spectrometry

Instantaneous, continuous, and reliable information on the molecular biology of surgical target tissue could significantly contribute to the precision, safety, and speed of the intervention. In this work, we introduced a methodology for chemical tissue identification in robotic surgery using rapid evaporative ionisation mass spectrometry. We developed a surgical aerosol evacuation system that is compatible with a robotic platform enabling consistent intraoperative sample collection and assessed the feasibility of this platform during head and neck surgical cases, using two different surgical energy devices. Our data showed specific, characteristic lipid profiles associated with the tissue type including various ceramides, glycerophospholipids, and glycerolipids, as well as different ion formation mechanisms based on the energy device used. This platform allows continuous and accurate intraoperative mass spectrometry-based identification of ablated/resected tissue and in combination with robotic registration of images, time, and anatomical positions can improve the current robot-assisted surgical platforms and guide surgical strategy.

Global Cancer Surgery: pragmatic solutions to improve cancer surgery outcomes worldwide

The first Lancet Oncology Commission on Global Cancer Surgery was published in 2015 and serves as a landmark paper in the field of cancer surgery. The Commission highlighted the burden of cancer and the importance of cancer surgery, while documenting the many inadequacies in the ability to deliver safe, timely, and affordable cancer surgical care. This Commission builds on the first Commission by focusing on solutions and actions to improve access to cancer surgery globally, developed by drawing upon the expertise from cancer surgery leaders across the world. We present solution frameworks in nine domains that can improve access to cancer surgery. These nine domains were refined to identify solutions specific to the six WHO regions. On the basis of these solutions, we developed eight actions to propel essential improvements in the global capacity for cancer surgery. Our initiatives are broad in scope, pragmatic, affordable, and contextually applicable, and aimed at cancer surgeons as well as leaders, administrators, elected officials, and health policy advocates. We envision that the solutions and actions contained within the Commission will address inequities and promote safe, timely, and affordable cancer surgery for every patient, regardless of their socioeconomic status or geographic location.

Artificial intelligence in colorectal surgery: an AI-powered systematic review

Artificial intelligence (AI) has the potential to revolutionize surgery in the coming years. Still, it is essential to clarify what the meaningful current applications are and what can be reasonably expected. This AI-powered review assessed the role of AI in colorectal surgery. A Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-compliant systematic search of PubMed, Embase, Scopus, Cochrane Library databases, and gray literature was conducted on all available articles on AI in colorectal surgery (from January 1 1997 to March 1 2021), aiming to define the perioperative applications of AI. Potentially eligible studies were identified using novel software powered by natural language processing (NLP) and machine learning (ML) technologies dedicated to systematic reviews. Out of 1238 articles identified, 115 were included in the final analysis. Available articles addressed the role of AI in several areas of interest. In the preoperative phase, AI can be used to define tailored treatment algorithms, support clinical decision-making, assess the risk of complications, and predict surgical outcomes and survival. Intraoperatively, AI-enhanced surgery and integration of AI in robotic platforms have been suggested. After surgery, AI can be implemented in the Enhanced Recovery after Surgery (ERAS) pathway. Additional areas of applications included the assessment of patient-reported outcomes, automated pathology assessment, and research. Available data on these aspects are limited, and AI in colorectal surgery is still in its infancy. However, the rapid evolution of technologies makes it likely that it will increasingly be incorporated into everyday practice.

Comparison of short-term outcomes between robotic and laparoscopic distal gastrectomy performed by the same surgical team during the same period

Objective

To evaluate the short-term outcomes of laparoscopic distal gastrectomy and robotic distal gastrectomy performed during the same period.

Methods

This study enrolled 46 cases of laparoscopic distal gastrectomy and 67 cases of robotic distal gastrectomy that were performed by a single surgeon between April 2020 to October 2021. Baseline characteristics and short-term outcomes of these two groups were then compared. Moreover, the robotic distal gastrectomy group was further divided into two subgroups according to the learning curve. Finally, the baseline characteristics and short-term outcomes of both subgroups were compared with the laparoscopic group, respectively.

Results

The baseline characteristics and short-term outcomes of the LDG group and RDG group were comparable. In contrast, the operation time in the laparoscopic group was significantly shorter than that in the early experience robotic group (191.3 ± 37.6 VS 225.1 ± 49, P=0.001). However, the operation time (191.3 ± 37.6 VS 185.3 ± 25.3, P=0.434) was comparable between the laparoscopic group and the late experience robotic group. Likewise, the bleeding volume was comparable between the laparoscopic and early experience robotic groups. However, bleeding volume was significantly lower in the late experience robotic group compared to that in the laparoscopic group (37.5 ± 18.8 VS 49.2 ± 29.0, P=0.049).

Conclusions

With surgeons stepping into the stable stage of the robotic learning curve, RDG showed a comparable operation time and lower volume of blood loss compared with LDG. Collectively, our study supports the application of robotic distal gastrectomy in patients diagnosed with gastric cancer.

Innovation in gastrointestinal surgery: the evolution of minimally invasive surgery-a narrative review

Background

Minimally invasive (MI) surgery has revolutionised surgery, becoming the standard of care in many countries around the globe. Observed benefits over traditional open surgery include reduced pain, shorter hospital stay, and decreased recovery time. Gastrointestinal surgery in particular was an early adaptor to both laparoscopic and robotic surgery. Within this review, we provide a comprehensive overview of the evolution of minimally invasive gastrointestinal surgery and a critical outlook on the evidence surrounding its effectiveness and safety.

Methods

A literature review was conducted to identify relevant articles for the topic of this review. The literature search was performed using Medical Subject Heading terms on PubMed. The methodology for evidence synthesis was in line with the four steps for narrative reviews outlined in current literature. The key words used were minimally invasive, robotic, laparoscopic colorectal, colon, rectal surgery.

Conclusion

The introduction of minimally surgery has revolutionised patient care. Despite the evidence supporting this technique in gastrointestinal surgery, several controversies remain. Here we discuss some of them; the lack of high level evidence regarding the oncological outcomes of TaTME and lack of supporting evidence for robotic colorectalrectal surgery and upper GI surgery. These controversies open pathways for future research opportunities with RCTs focusing on comparing robotic to laparoscopic with different primary outcomes including ergonomics and surgeon comfort.

Artificial intelligence-assisted selection and efficacy prediction of antineoplastic strategies for precision cancer therapy

The rapid development of artificial intelligence (AI) technologies in the context of the vast amount of collectable data obtained from high-throughput sequencing has led to an unprecedented understanding of cancer and accelerated the advent of a new era of clinical oncology with a tone of precision treatment and personalized medicine. However, the gains achieved by a variety of AI models in clinical oncology practice are far from what one would expect, and in particular, there are still many uncertainties in the selection of clinical treatment options that pose significant challenges to the application of AI in clinical oncology. In this review, we summarize emerging approaches, relevant datasets and open-source software of AI and show how to integrate them to address problems from clinical oncology and cancer research. We focus on the principles and procedures for identifying different antitumor strategies with the assistance of AI, including targeted cancer therapy, conventional cancer therapy, and cancer immunotherapy. In addition, we also highlight the current challenges and directions of AI in clinical oncology translation. Overall, we hope this article will provide researchers and clinicians with a deeper understanding of the role and implications of AI in precision cancer therapy, and help AI move more quickly into accepted cancer guidelines.

Lipidomic Profiling of Colorectal Lesions for Real-Time Tissue Recognition and Risk-Stratification Using Rapid Evaporative Ionization Mass Spectrometry

OBJECTIVE

Rapid evaporative ionization mass spectrometry (REIMS) is a metabolomic technique analyzing tissue metabolites, which can be applied intraoperatively in real-time. The objective of this study was to profile the lipid composition of colorectal tissues using REIMS, assessing its accuracy for real-time tissue recognition and risk-stratification.

SUMMARY BACKGROUND DATA

Metabolic dysregulation is a hallmark feature of carcinogenesis; however, it remains unknown if this can be leveraged for real-time clinical applications in colorectal disease.

METHODS

Patients undergoing colorectal resection were included, with carcinoma, adenoma and paired-normal mucosa sampled. Ex vivo analysis with REIMS was conducted using monopolar diathermy, with the aerosol aspirated into a Xevo G2S QToF mass spectrometer. Negatively charged ions over 600 to 1000 m/z were used for univariate and multivariate functions including linear discriminant analysis.

RESULTS

A total of 161 patients were included, generating 1013 spectra. Unique lipidomic profiles exist for each tissue type, with REIMS differentiating samples of carcinoma, adenoma, and normal mucosa with 93.1% accuracy and 96.1% negative predictive value for carcinoma. Neoplasia (carcinoma or adenoma) could be predicted with 96.0% accuracy and 91.8% negative predictive value. Adenomas can be risk-stratified by grade of dysplasia with 93.5% accuracy, but not histological subtype. The structure of 61 lipid metabolites was identified, revealing that during colorectal carcinogenesis there is progressive increase in relative abundance of phosphatidylglycerols, sphingomyelins, and mono-unsaturated fatty acid-containing phospholipids.

CONCLUSIONS

The colorectal lipidome can be sampled by REIMS and leveraged for accurate real-time tissue recognition, in addition to riskstratification of colorectal adenomas. Unique lipidomic features associated with carcinogenesis are described.

Intelligent oncology: The convergence of artificial intelligence and oncology

With increasingly explored ideologies and technologies for potential applications of artificial intelligence (AI) in oncology, we here describe a holistic and structured concept termed intelligent oncology. Intelligent oncology is defined as a cross-disciplinary specialty which integrates oncology, radiology, pathology, molecular biology, multi-omics and computer sciences, aiming to promote cancer prevention, screening, early diagnosis and precision treatment. The development of intelligent oncology has been facilitated by fast AI technology development such as natural language processing, machine/deep learning, computer vision, and robotic process automation. While the concept and applications of intelligent oncology is still in its infancy, and there are still many hurdles and challenges, we are optimistic that it will play a pivotal role for the future of basic, translational and clinical oncology.

Artificial intelligence and automation in endoscopy and surgery

Modern endoscopy relies on digital technology, from high-resolution imaging sensors and displays to electronics connecting configurable illumination and actuation systems for robotic articulation. In addition to enabling more effective diagnostic and therapeutic interventions, the digitization of the procedural toolset enables video data capture of the internal human anatomy at unprecedented levels. Interventional video data encapsulate functional and structural information about a patient's anatomy as well as events, activity and action logs about the surgical process. This detailed but difficult-to-interpret record from endoscopic procedures can be linked to preoperative and postoperative records or patient imaging information. Rapid advances in artificial intelligence, especially in supervised deep learning, can utilize data from endoscopic procedures to develop systems for assisting procedures leading to computer-assisted interventions that can enable better navigation during procedures, automation of image interpretation and robotically assisted tool manipulation. In this Perspective, we summarize state-of-the-art artificial intelligence for computer-assisted interventions in gastroenterology and surgery.

Recent advances in surgical strategies and liver transplantation for hepatoblastoma

Hepatoblastoma (HB) is the most common malignant liver tumor in children. Although the development of treatment strategies with advances in chemotherapy has greatly improved the prognosis of HB, surgical resection and liver transplantation still play a vital role in the treatment of HB. In recent years, technological innovations have led to the development of new surgical approaches for HB. In this review, we describe the latest research on the surgical management of HB, including new imaging technologies, minimally invasive approaches, and the application of associating liver partition portal vein ligation for staged hepatectomy. We also discuss the current role of liver transplantation, use of ante-situm or ex-situ liver resection with auto-transplantation, and management of metastatic HB.

The RoboCOS Study: Development of an international core outcome set for the comprehensive evaluation of patient, surgeon, organisational and population level impacts of robotic assisted surgery

BACKGROUND

The introduction of robot-assisted surgery is costly and requires whole system transformation, which makes the assessment of benefits (or drawbacks) complex. To date, there has been little agreement on which outcomes should be used in this regard. The aim of the RoboCOS study was to develop a core outcome set for the evaluation of robot-assisted surgery that would account for its impact on the whole system.

METHODS

Identification of a long-list of potentially relevant outcomes through systematic review of trials and health technology assessments; interviews with individuals from a range of stakeholder groups (surgeons, service managers, policy makers and evaluators) and a focus group with patients and public; prioritisation of outcomes via a 2-round online international Delphi survey; consensus meeting.

RESULTS

721 outcomes were extracted from the systematic reviews, interviews and focus group which were conceptualised into 83 different outcome domains across four distinct levels (patient, surgeon, organisation and population) for inclusion in the international Delphi prioritisation survey (128 completed both rounds). The consensus meeting led to the agreement of a 10-item core outcome set including outcomes at: patient level (treatment effectiveness; overall quality of life; disease-specific quality of life; complications (including mortality); surgeon level (precision/accuracy; visualisation); organisation (equipment failure; standardisation of operative quality; cost-effectiveness); and population (equity of access).

CONCLUSION

The RoboCOS core outcome set, which includes the outcomes of importance to all stakeholders, is recommended for use in all future evaluations of robot-assisted surgery to ensure relevant and comparable reporting of outcomes.

A Delphi consensus statement for digital surgery

The use of digital technology is increasing rapidly across surgical specialities, yet there is no consensus for the term ‘digital surgery’. This is critical as digital health technologies present technical, governance, and legal challenges which are unique to the surgeon and surgical patient. We aim to define the term digital surgery and the ethical issues surrounding its clinical application, and to identify barriers and research goals for future practice. 38 international experts, across the fields of surgery, AI, industry, law, ethics and policy, participated in a four-round Delphi exercise. Issues were generated by an expert panel and public panel through a scoping questionnaire around key themes identified from the literature and voted upon in two subsequent questionnaire rounds. Consensus was defined if >70% of the panel deemed the statement important and <30% unimportant. A final online meeting was held to discuss consensus statements. The definition of digital surgery as the use of technology for the enhancement of preoperative planning, surgical performance, therapeutic support, or training, to improve outcomes and reduce harm achieved 100% consensus agreement. We highlight key ethical issues concerning data, privacy, confidentiality and public trust, consent, law, litigation and liability, and commercial partnerships within digital surgery and identify barriers and research goals for future practice. Developers and users of digital surgery must not only have an awareness of the ethical issues surrounding digital applications in healthcare, but also the ethical considerations unique to digital surgery. Future research into these issues must involve all digital surgery stakeholders including patients.

A computer-aid multi-task light-weight network for macroscopic feces diagnosis

The abnormal traits and colors of feces typically indicate that the patients are probably suffering from tumor or digestive-system diseases. Thus a fast, accurate and automatic health diagnosis system based on feces is urgently necessary for improving the examination speed and reducing the infection risk. The rarity of the pathological images would deteriorate the accuracy performance of the trained models. In order to alleviate this problem, we employ augmentation and over-sampling to expand the samples of the classes that have few samples in the training batch. In order to achieve an impressive recognition performance and leverage the latent correlation between the traits and colors of feces pathological samples, a multi-task network is developed to recognize colors and traits of the macroscopic feces images. The parameter number of a single multi-task network is generally much smaller than the total parameter number of multiple single-task networks, so the storage cost is reduced. The loss function of the multi-task network is the weighted sum of the losses of the two tasks. In this paper, the weights of the tasks are determined according to their difficulty levels that are measured by the fitted linear functions. The sufficient experiments confirm that the proposed method can yield higher accuracies, and the efficiency is also improved.

Robotic versus Open Pancreatoduodenectomy for Pancreatic and Periampullary Tumors (PORTAL): a study protocol for a multicenter phase III non-inferiority randomized controlled trial

BACKGROUND

Pancreatoduodenectomy is a complex and challenging procedure that requires meticulous tissue dissection and proficient suturing skills. Minimally invasive surgery with the utilization of robotic platforms has demonstrated advantages in perioperative patient outcomes in retrospective studies. The development of robotic pancreatoduodenectomy (RPD) in specific has progressed significantly, since first reported in 2003, and high-volume centers in pancreatic surgery are reporting large patient series with improved pain management and reduced length of stay. However, prospective studies to assess objectively the feasibility and safety of RPD compared to open pancreatoduodenectomy (OPD) are currently lacking.

METHODS/DESIGN

The PORTAL trial is a multicenter randomized controlled, patient-blinded, parallel-group, phase III non-inferiority trial performed in seven high-volume centers for pancreatic and robotic surgery in China (> 20 RPD and > 100 OPD annually in each participating center). The trial is designed to enroll and randomly assign 244 patients with an indication for elective pancreatoduodenectomy for malignant periampullary and pancreatic lesions, as well as premalignant and symptomatic benign periampullary and pancreatic disease. The primary outcome is time to functional recovery postoperatively, measured in days. Secondary outcomes include postoperative morbidity and mortality, as well as perioperative costs. A sub-cohort of 128 patients with pancreatic adenocarcinoma (PDAC) will also be compared to assess the percentage of patients who undergo postoperative adjuvant chemotherapy within 8 weeks, in each arm. Secondary outcomes in this cohort will include patterns of disease recurrence, recurrence-free survival, and overall survival.

DISCUSSION

The PORTAL trial is designed to assess the feasibility and safety of RPD compared to OPD, in terms of functional recovery as described previously. Additionally, this trial will explore whether RPD allows increased access to postoperative adjuvant chemotherapy, in a sub-cohort of patients with PDAC.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04400357 . Registered on May 22, 2020.

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.

Market potentials of robotic systems in medical science: analysis of the Avatera robotic system

PURPOSE

To evaluate the potential opportunities and possible competitiveness of Avatera robotic system (ARS) (Avateramedical, Germany), and perform predictive cost-analysis for its implementation and dissemination.

MATERIAL AND METHODS

Our study employed a projective quantitative research design. SWOT (strengths, weaknesses, opportunities, threats) analysis was used to map ARS internal competencies towards external contexts, and potential opportunities and risks in the robotic market. The ARS purchase and procedural costs were evaluated in two different scenarios.

RESULTS

In the first scenario, setting the purchase cost of the Avatera at around $1.3-1.5 million, a total $400 procedural cost reduction compared to the RAS performed with the da Vinci Xi can be calculated. In the second scenario, with a purchase cos of the ARS of $700.000-800.000 and considering a 5-year period with an annual ARS volume of 500 procedures, only an additional $300 will be attributed to the robot itself. Our projections revealed that for an effective competition the purchase cost of ARS should range between $700.000 and $800.000 during the initial phase of market entry. The marketing strategy of the ARS should be oriented towards countries without any robotic system in operational use, followed by countries where the competition intensity in the marketplace is low.

CONCLUSION

The introduction of new robotic systems will greatly affect and reshape the market of robotic surgery. The ARS has all the technical capacity ensuring the performance of high-quality surgical procedures. A fast spread and implementation of the ARS could be expected should the purchase and maintenance costs be kept low.

The Application and Development of Deep Learning in Radiotherapy: A Systematic Review

With the massive use of computers, the growth and explosion of data has greatly promoted the development of artificial intelligence (AI). The rise of deep learning (DL) algorithms, such as convolutional neural networks (CNN), has provided radiation oncologists with many promising tools that can simplify the complex radiotherapy process in the clinical work of radiation oncology, improve the accuracy and objectivity of diagnosis, and reduce the workload, thus enabling clinicians to spend more time on advanced decision-making tasks. As the development of DL gets closer to clinical practice, radiation oncologists will need to be more familiar with its principles to properly evaluate and use this powerful tool. In this paper, we explain the development and basic concepts of AI and discuss its application in radiation oncology based on different task categories of DL algorithms. This work clarifies the possibility of further development of DL in radiation oncology.

Robotic versus laparoscopic distal pancreatectomies: A systematic review and meta-analysis on costs and perioperative outcome

AIM

The aim of this meta-analysis is to compare perioperative outcomes and costs of robotic and laparoscopic distal pancreatectomy (RDP and LDP).

MATERIAL AND METHODS

In accordance with the PRISMA guidelines, we searched Medline, EMBASE, Cochrane and Web of Science for reports published before December 2020.

RESULTS

The literature search identified 11 papers (1 187 patients). RDP showed a lower conversion rate (odds ratio: 2.56, 95% confidence intervals [CI]: 1.31 to 5.00) with no significant differences in bleeding and operative time, complications ≥ Clavien-Dindo grade III, pancreatic fistulas and length of stay. Despite RDP presenting higher costs in all included studies, none of these differences were significant. However, RDP showed higher total costs than LDP (standardized mean differences [SMD]: -1.18, 95% CI: -1.97 to -0.39). A subgroup analysis according to the continent of origin showed that studies coming from Asian research groups kept showing significant differences (SMD: -2.62, 95% CI: -3.38 to -1.85), while Western groups did not confirm these findings.

CONCLUSION

Based on low-quality evidence, despite some potential technical advantages, RDP still seems to be costlier than LDP.

Validation of Ultrasonic Harmonic Scalpel for Real-Time Tissue Identification Using Rapid Evaporative Ionization Mass Spectrometry

In this study, we integrate rapid evaporative ionization mass spectrometry (REIMS) with the Harmonic scalpel, an advanced laparoscopic surgical instrument that utilizes ultrasound energy to dissect and coagulate tissues. It provides unparalleled manipulation capability to surgeons and has superseded traditional electrosurgical tools particularly in abdominal surgery, but is yet to be validated with REIMS. The REIMS platform coupled with the Harmonic device was shown to produce tissue-specific lipid profiles through the analysis of porcine tissues in both negative and positive ionization modes. Comparison with other methods of electrosurgical dissection, such as monopolar electrosurgery and CO₂ laser, showed spectral differences in the profile dependent on the energy device used. The Harmonic device demonstrated major spectral differences in the phospholipid region of m/z 600–1000 compared with the monopolar electrosurgical and CO₂ laser-generated spectra. Within the Harmonic REIMS spectra, high intensities of diglycerides and triglycerides were observed. In contrast, monopolar electrosurgical and laser spectra demonstrated high abundances of glycerophospholipids. The Harmonic scalpel was able to differentiate between the liver, muscle, colon, and small intestine, demonstrating 100% diagnostic accuracy. The validation of the Harmonic device–mass spectrometry combination will allow the platform to be used safely and robustly for real-time in vivo surgical tissue identification in a variety of clinical applications.

State of the art in robotic rectal surgery: marginal gains worth the pain?

After their first introduction in the 1990s to overcome the limitations of conventional laparoscopic surgery, especially in confined spaces such as the pelvis, telemanipulators (i.e., master-slave manipulators) have gained popularity and acceptance among gastrointestinal surgeons. These complex, interventional surgical devices use multiple technologies, such as 3-D advanced imaging, tremor reduction and 7-degree movement. Superior instrument dexterity, stable precise vision and accessibility to narrow confined spaces make these devices well suited for colorectal surgery. The drive for innovations in the field of surgical robotics will leverage novel robots driven by data, image integration, and artificial intelligence. However, if this vision is to be realized, lessons must be learned from the current literature and clinical trials. The feasibility and safety of robotic rectal surgery is now well established; increasing evidence suggests that when compared to laparoscopic rectal surgery, robotic approaches might offer superior peri-operative outcomes. Notably, the marginal gains achieved with the use of robotics in rectal cancer surgery are linked with structured training and standardization of operative techniques. With decreasing costs and wider availability of new systems, it is foreseeable that robotic surgical systems will be an integral part of colorectal practice.

Investigating the Ethical and Data Governance Issues of Artificial Intelligence in Surgery: Protocol for a Delphi Study

BACKGROUND

The rapid uptake of digital technology into the operating room has the potential to improve patient outcomes, increase efficiency of the use of operating rooms, and allow surgeons to progress quickly up learning curves. These technologies are, however, dependent on huge amounts of data, and the consequences of their mismanagement are significant. While the field of artificial intelligence ethics is able to provide a broad framework for those designing and implementing these technologies into the operating room, there is a need to determine and address the ethical and data governance challenges of using digital technology in this unique environment.

OBJECTIVE

The objectives of this study are to define the term digital surgery and gain expert consensus on the key ethical and data governance issues, barriers, and future research goals of the use of artificial intelligence in surgery.

METHODS

Experts from the fields of surgery, ethics and law, policy, artificial intelligence, and industry will be invited to participate in a 4-round consensus Delphi exercise. In the first round, participants will supply free-text responses across 4 key domains: ethics, data governance, barriers, and future research goals. They will also be asked to provide their understanding of the term digital surgery. In subsequent rounds, statements will be grouped, and participants will be asked to rate the importance of each issue on a 9-point Likert scale ranging from 1 (not at all important) to 9 (critically important). Consensus is defined a priori as a score of 7 to 9 by 70% of respondents and 1 to 3 by less than 30% of respondents. A final online meeting round will be held to discuss inclusion of statements and draft a consensus document.

RESULTS

Full ethical approval has been obtained for the study by the local research ethics committee at Imperial College, London (20IC6136). We anticipate round 1 to commence in January 2021.

CONCLUSIONS

The results of this study will define the term digital surgery, identify the key issues and barriers, and shape future research in this area.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/26552.

Robotic Liver Surgery - Current Standards and Future Perspectives

BACKGROUND

 Robotic liver surgery is emerging as the future of minimal invasive surgery. The robotic surgical system offers a stable camera platform, elimination of physiologic tremor, augmented surgical dexterity as well as improved ergonomics because of a seated operating position. Due to the theoretical advantages of the robotic assisted system, complex liver surgery might be an especially interesting indication for a robotic approach since it demands delicate tissue dissection, precise intracorporeal suturing as well as difficult parenchymal transection with subsequent need for meticulous hemostasis and biliostasis.

MATERIAL AND METHODS

 An analysis of English and German literature on open, laparoscopic and robotic liver surgery was performed and this review provides a general overview of the existing literature along with current standards and aims to specifically point out future directions of robotic liver surgery.

RESULTS

 Robotic liver surgery is safe and feasible compared to open and laparoscopic surgery, with improved short-term postoperative outcomes and at least non-inferior oncological outcomes.

CONCLUSION

 In complex cases including major hepatectomies, extended hepatectomies with biliary reconstruction and difficult segmentectomies of the posterior-superior segments, robotic surgery appears to emerge as a reasonable alternative to open surgery rather than being an alternative to laparoscopic procedures.

Robotic Surgery in Inflammatory Bowel Disease

BACKGROUND

Surgery is considered a cornerstone of inflammatory bowel disease (IBD) treatment. In the last years, robotic surgery has seen an increase in adoption rates for both benign and malignant diseases.

OBJECTIVE

This work aims to review the current applications of robotic surgery in IBD.

DISCUSSION AND CONCLUSION

Minimally-invasive techniques have been applied to the treatment of IBD for more than 20 years. Investments in surgical digital and robotic platforms are increasingly arising, with an estimate of getting doubled within the next 5 years. Robotic surgery represents the newest technology available to reduce the impact of surgery on patients affected by IBD, and may theoretically be even more effective than other minimally-invasive techniques given the lower rate of conversion to open surgery as compared to laparoscopy according to many large retrospective series. Data on robotic surgery applied to IBD are still scarce and initial experiences in high-volume centers from retrospective series suggested that robotic surgery may achieve similar results when compared to laparoscopy. A new wave of robotics incorporating artificial intelligence is awaited to empower the capability of IBD surgeon in terms of intraoperative decision-making beyond technical skill enhancement.