A systematic review of robotic surgery: From supervised paradigms to fully autonomous robotic approaches

Artificial intelligence in head and neck surgery: Potential applications and future perspectives

Artificial intelligence (AI) has the potential to improve the surgical treatment of patients with head and neck cancer. AI algorithms can analyse a wide range of data, including images, voice, molecular expression and raw clinical data. In the field of oncology, there are numerous AI practical applications, including diagnostics and treatment. AI can also develop predictive models to assess prognosis, overall survival, the likelihood of occult metastases, risk of complications and hospital length of stay.

Autonomous Magnetic Navigation in Endoscopic Image Mosaics

Endoscopes navigate within the human body to observe anatomical structures with minimal invasiveness. A major shortcoming of their use is their narrow field-of-view during navigation in large, hollow anatomical regions. Mosaics of endoscopic images can provide surgeons with a map of the tool's environment. This would facilitate procedures, improve their efficiency, and potentially generate better patient outcomes. The emergence of magnetically steered endoscopes opens the way to safer procedures and creates an opportunity to provide robotic assistance both in the generation of the mosaic map and in navigation within this map. This paper proposes methods to autonomously navigate magnetic endoscopes to 1) generate endoscopic image mosaics and 2) use these mosaics as user interfaces to navigate throughout the explored area. These are the first strategies, which allow autonomous magnetic navigation in large, hollow organs during minimally invasive surgeries. The feasibility of these methods is demonstrated experimentally both in vitro and ex vivo in the context of the treatment of twin-to-twin transfusion syndrome. This minimally invasive procedure is performed in utero and necessitates coagulating shared vessels of twin fetuses on the placenta. A mosaic of the vasculature in combination with autonomous navigation has the potential to significantly facilitate this challenging surgery.

The current state of autonomous suturing: a systematic review

BACKGROUND

Robotic technology is an important tool in surgical innovation, with robots increasingly being used in the clinical setting. Robots can be used to enhance accuracy, perform remote actions, or to automate tasks. One such surgical task is suturing, a repetitive, fundamental component of surgery that can be tedious and time consuming. Suturing is a promising automation target because of its ubiquity, repetitive nature, and defined constraints. This systematic review examines research to date on autonomous suturing.

METHODS

A systematic review of the literature focused on autonomous suturing was conducted in accordance with PRISMA guidelines.

RESULTS

6850 articles were identified by searching PubMed, Embase, Compendex, and Inspec. Duplicates and non-English articles were removed. 4389 articles were screened and 4305 were excluded. Of the 84 remaining, 43 articles did not meet criteria, leaving 41 articles for final review. Among these, 34 (81%) were published after 2014. 31 (76%) were published in an engineering journal9 in a robotics journal, and 1 in a medical journal. The great majority of articles (33, 80%) did not have a specific clinical specialty focus, whereas 6 (15%) were focused on applications in MIS/laparoscopic surgery and 2 (5%) on applications in ophthalmology. Several suturing subtasks were identified, including knot tying, suture passing/needle insertion, needle passing, needle and suture grasping, needle tracking/kinesthesia, suture thread detection, suture needle shape production, instrument assignment, and suture accuracy. 14 articles were considered multi-component because they referred to several previously mentioned subtasks.

CONCLUSION

In this systematic review exploring research to date on autonomous suturing, 41 articles demonstrated significant progress in robotic suturing. This summary revealed significant heterogeneity of work, with authors focused on different aspects of suturing and a multitude of engineering problems. The review demonstrates increasing academic and commercial interest in surgical automation, with significant technological advances toward feasibility.

Initial Experience With Robotic-Assisted Otologic and Lateral Skull Base Surgery

Robotic-assisted surgery has gained popularity for otolaryngology procedures. It provides high-definition images and surgical precision to perform diverse procedures. It is an alternative to the operating microscope, endoscope, or exoscope when reaching hidden anatomical structures in the ear. In this proof-of-concept study, we aim to demonstrate the possibility of using a robotic-assisted device to perform ear surgery in conjunction with the microscope or the endoscope. In total, there were 9 ear and lateral skull base procedures performed with the use of robotic-assisted surgery. All surgeons underwent surveys to assess the performance and workload of the device compared to the microscope or endoscope. There were no postoperative complications. Robotic-assisted surgery was optimal for providing high image quality, ergonomics, and maintaining surgical performance. The size of the device and mental demand were higher compared to the microscope or endoscope. Robotic-assisted surgery can be an adjuvant to perform otologic and neurotologic surgery.

What are the key stability challenges in high-bandwidth, non-minimum phase systems with time-varying, and non-smooth delays?

The analysis and control of stability in high-bandwidth systems characterized by non-minimum phase delays represent a formidable challenge within the realm of control theory and engineering. This research aims to address the pivotal question of whether it is feasible to enhance the stability of such intricate systems. These systems inherently possess uncertain and swiftly changing delay characteristics, rendering them exceptionally demanding to control effectively. In the course of this investigation, we embark on a comprehensive exploration of the theoretical underpinnings of the stability of high-bandwidth, non-minimum phase delay systems. This encompassing inquiry encompasses a meticulous consideration of both derivative-delay and piecewise continuous delay components. To underpin our analysis, we judiciously incorporate feedback mechanisms, drawing upon mathematical tools such as the Jensen inequality and Lyapunov-based methodologies to rigorously establish stability conditions. Furthermore, our exploration extends to encompass the concept of input-output stability and complements it with the notion of asymptotic stability, thereby ensuring that the systems in question exhibit uniform stability across diverse temporal domains. The outcomes of our investigation furnish compelling evidence that by harnessing the power of discrete-time Lyapunov-Krasovskii functionals, it becomes conceivable to circumscribe the maximum delay within predefined thresholds. This achievement holds the promise of enhancing stability in non-minimum phase delay systems characterized by high bandwidth. These findings have far-reaching implications, profoundly influencing the design and control paradigms across a spectrum of engineering applications. Notably, this impact extends to areas such as communication networks, real-time control systems, and robotics, where the mitigation of instability due to non-minimum phase delays has been an enduring challenge.

Robotic assisted minimally invasive esophagectomy versus minimally invasive esophagectomy

Background

Esophagectomy is the gold standard treatment for resectable esophageal cancer; however, there is insufficient evidence to indicate potential advantages over standard minimally invasive esophagectomy (MIE) in treating thoracic esophageal cancer. Robot-assisted minimally invasive esophagectomy (RAMIE) bridges the gap between open and minimally invasive surgery. In this single-center retrospective review, we compare the clinical outcomes of EC patients treated with MIE and RAMIE.

Method

We retrospectively reviewed the clinical data of patients with esophageal cancer who underwent surgery at Qilu Hospital between August 2020 and August 2022, including 159 patients who underwent MIE and 35 patients who received RAMIE. The intraoperative, postoperative, and preoperative patient characteristics in both groups were evaluated.

Results

Except for height, the MIE and RAMIE groups showed no significant differences in preoperative features (P>0.05). Further, there were no significant differences in intraoperative indices, including TNM stage of the resected tumor, tumor tissue type, or ASA score, between the two groups. However, statistically significant differences were found in some factors; the RAMIE group had a shorter operative time, less intraoperative bleeding, and more lymph nodes removed compared to the MIE group. Patients in the RAMIE group reported less discomfort and greater chest drainage on the first postoperative day than patients in the MIE group; however, there were no differences in other features between the two datasets.

Conclusion

By comparing the clinical characteristics and outcomes of RAMIE with MIE, this study verified the feasibility and safety of RAMIE for esophageal cancer. Overall, RAMIE resulted in more complete lymph node clearance, shorter operating time, reduced surgical hemorrhage, reduced postoperative discomfort, and chest drainage alleviation in patients. To investigate the function of RAMIE in esophageal cancer, we propose undertaking a future clinical trial with long-term follow-up to analyze tumor clearance, recurrence, and survival after RAMIE.

Evolution of a surgical system using deep learning in minimally invasive surgery (Review)

Recently, artificial intelligence (AI) has been applied in various fields due to the development of new learning methods, such as deep learning, and the marked progress in computational processing speed. AI is also being applied in the medical field for medical image recognition and omics analysis of genomes and other data. Recently, AI applications for videos of minimally invasive surgeries have also advanced, and studies on such applications are increasing. In the present review, studies that focused on the following topics were selected: i) Organ and anatomy identification, ii) instrument identification, iii) procedure and surgical phase recognition, iv) surgery-time prediction, v) identification of an appropriate incision line, and vi) surgical education. The development of autonomous surgical robots is also progressing, with the Smart Tissue Autonomous Robot (STAR) and RAVEN systems being the most reported developments. STAR, in particular, is currently being used in laparoscopic imaging to recognize the surgical site from laparoscopic images and is in the process of establishing an automated suturing system, albeit in animal experiments. The present review examined the possibility of fully autonomous surgical robots in the future.

User interfaces for actuated scope maneuvering in surgical systems: a scoping review

Background

A variety of human computer interfaces are used by robotic surgical systems to control and actuate camera scopes during minimally invasive surgery. The purpose of this review is to examine the different user interfaces used in both commercial systems and research prototypes.

Methods

A comprehensive scoping review of scientific literature was conducted using PubMed and IEEE Xplore databases to identify user interfaces used in commercial products and research prototypes of robotic surgical systems and robotic scope holders. Papers related to actuated scopes with human–computer interfaces were included. Several aspects of user interfaces for scope manipulation in commercial and research systems were reviewed.

Results

Scope assistance was classified into robotic surgical systems (for multiple port, single port, and natural orifice) and robotic scope holders (for rigid, articulated, and flexible endoscopes). Benefits and drawbacks of control by different user interfaces such as foot, hand, voice, head, eye, and tool tracking were outlined. In the review, it was observed that hand control, with its familiarity and intuitiveness, is the most used interface in commercially available systems. Control by foot, head tracking, and tool tracking are increasingly used to address limitations, such as interruptions to surgical workflow, caused by using a hand interface.

Conclusion

Integrating a combination of different user interfaces for scope manipulation may provide maximum benefit for the surgeons. However, smooth transition between interfaces might pose a challenge while combining controls.

Review of Enhanced Handheld Surgical Drills

The handheld drill has been used as a conventional surgical tool for centuries. Alongside the recent successes of surgical robots, the development of new and enhanced medical drills has improved surgeon ability without requiring the high cost and consuming setup times that plague medical robot systems. This work provides an overview of enhanced handheld surgical drill research focusing on systems that include some form of image guidance and do not require additional hardware that physically supports or guides drilling. Drilling is reviewed by main contribution divided into audio-, visual-, or hardware-enhanced drills. A vision for future work to enhance handheld drilling systems is also discussed.

Effect of the Segmentation Threshold on Computed Tomography-Based Reconstruction of Skull Bones with Reference Optical Three-Dimensional Scanning

BACKGROUND

A variety of applications related to neurosurgical procedures, education, and training require accurate reconstruction of the involved structures from the medical images such as computed tomography (CT). This study evaluates the quality of CT-based reconstruction of dry skull bones for advanced neurosurgical applications. The accuracy and precision of these models were examined with reference optical scanning.

METHODS

Three consecutive CT and optical scans of different skull bones were acquired and used to develop three-dimensional models. The accuracy of three-dimensional models was examined by manual inspection of the defined anatomical landmarks of the skull. Reproducibility was examined by deviation analysis of the models developed from repeated CT and optical scans.

RESULTS

Precision was excellent in both the techniques with less than 0.1 mm deviation error. On the interscan evaluation of the CT versus optical scan model, deviations of more than 0.1 mm were observed in 16 out of 21 instances. CT reconstruction using standard segmentation algorithms results in missing bone portions while using the default bone segmentation threshold. The segmentation threshold was varied to construct missing bone regions, and its effect on the iso-surface generation was evaluated. The threshold variation led to increased mean deviations of surfaces up to 0.6 mm.

CONCLUSIONS

The study reveals that bone structure, complexity, and segmentation threshold lead to CT reconstruction variability. The trade-off between the desirable model and accepted mean deviation should be considered as per traits of the desired application.