Technical and ethical considerations in telesurgery

Telesurgery, a cutting-edge field at the intersection of medicine and technology, holds immense promise for enhancing surgical capabilities, extending medical care, and improving patient outcomes. In this scenario, this article explores the landscape of technical and ethical considerations that highlight the advancement and adoption of telesurgery. Network considerations are crucial for ensuring seamless and low-latency communication between remote surgeons and robotic systems, while technical challenges encompass system reliability, latency reduction, and the integration of emerging technologies like artificial intelligence and 5G networks. Therefore, this article also explores the critical role of network infrastructure, highlighting the necessity for low-latency, high-bandwidth, secure and private connections to ensure patient safety and surgical precision. Moreover, ethical considerations in telesurgery include patient consent, data security, and the potential for remote surgical interventions to distance surgeons from their patients. Legal and regulatory frameworks require refinement to accommodate the unique aspects of telesurgery, including liability, licensure, and reimbursement. Our article presents a comprehensive analysis of the current state of telesurgery technology and its potential while critically examining the challenges that must be navigated for its widespread adoption.

A long distance telesurgical demonstration on robotic surgery phantoms over 5G

PURPOSE

Using robotic technology and communications infrastructure to remotely perform surgery has been a persistent goal in medical research in the past three decades. The recent deployment of the Fifth-Generation Wireless Networks has revitalized the research efforts in the telesurgery paradigm. Offering low latency and high bandwidth communication, they are well suited for applications that require real-time data transmission and can allow smoother communication between surgeon and patient, making it possible to remotely perform complex surgeries. In this paper, we investigate the effects of the 5 G network on surgical performance during a telesurgical demonstration where the surgeon and the robot are separated by nearly 300 km.

METHODS

The surgeon performed surgical exercises on a robotic surgery training phantom using a novel telesurgical platform. The master controllers were connected to the local site on a 5 G network, teleoperating the robot remotely in a hospital. A video feed of the remote site was also streamed. The surgeon performed various tasks on the phantom such as cutting, dissection, pick-and-place and ring tower transfer. To assess the usefulness, usability and image quality of the system, the surgeon was subsequently interviewed using three structured questionnaires.

RESULTS

All tasks were completed successfully. The low latency and high bandwidth of the network resulted into a latency of 18 ms for the motion commands while the video delay was about 350 ms. This enabled the surgeon to operate smoothly with a high-definition video from about 300 km away. The surgeon viewed the system's usability in a neutral to positive way while the video image was rated as of good quality.

CONCLUSION

5 G networks provide significant advancement in the field of telecommunications, offering faster speeds and lower latency than previous generations of wireless technology. They can serve as an enabling technology for telesurgery and further advance its application and adoption.

Cumulative sum analysis of the learning curve for robotic retroauricular thyroidectomy

Background

Remote-access robotic thyroid surgery enables avoiding a visible scar on the neck and allows precise manipulation through a magnified surgical view. The retroauricular approach has many advantages. This study aimed to evaluate the learning curve for robotic retroauricular thyroidectomy using cumulative sum analysis.

Methods

The medical records of 36 patients who underwent robotic retroauricular thyroidectomy between 2018 and 2021 were retrospectively reviewed. The clinical features and surgical outcomes were analyzed; the learning curve was evaluated using the cumulative sum analysis.

Results

The learning curve using cumulative sum analysis was divided into two phases based on 15 cases: phase I (first 15 cases) and phase II (remaining 21 cases). The total operation time was significantly shorter in phase II than that in phase I (161.9±23.4 vs. 199±41.0 min, P=0.002). The flap dissection and docking time (77.1±14.3 vs. 90.0±21.5 min, P=0.037) and console time (36.5±16.2 vs. 50.3±17.8 min, P=0.020) were significantly shorter in phase II than that in phase I. There was no significant difference between the two phases in the total amount of drainage, duration of hospital stay, and complications after the surgery.

Conclusions

The learning curve for robotic retroauricular thyroidectomy demonstrates that the operation time decreased rapidly after 15 cases. Proficiency in docking and manipulating the instruments accelerate the learning curve.

5G mobile communication applications for surgery: An overview of the latest literature

Fifth-generation wireless network, 5G, is expected to bring surgery to a next level. Remote surgery and telementoring could be enabled and be brought into routine medical care due to 5G characteristics, such as extreme high bandwidth, ultra-short latency, multiconnectivity, high mobility, high availability, and high reliability. This work explores the benefits, applications and demands of 5G for surgery. Therefore, the development of previous surgical procedures from using older networks to 5G is outlined. The current state of 5G in surgical research studies is discussed, as well as future aspects and requirements of 5G in surgery are presented.

Impact of network performance on remote robotic-assisted endovascular interventions in porcine model

Remote robotic-assisted endovascular interventions require real-time control of the robotic system to conduct precise device navigation. The delay (latency) between the input command and the catheter response can be affected by factors such as network speed and distance. This study evaluated the effect of network latency on robotic-assisted endovascular navigation in three vascular beds using in-vivo experimental model. Three operators performed femoral, carotid, and coronary endovascular robotic navigation blinded from the hybrid room with the prototype remote-enabled CorPath GRX system in a porcine model. Navigation was performed to different targets with randomly assigned network latencies from 0 to 1000 ms. Outcome measurements included navigation success, navigation time, perceived lag (1 = imperceptible, 5 = too long), and procedural impact scored by the operators (1 = no impact, 5 = unacceptable). Robotic-assisted remote endovascular navigation was successful in all 65 cases (9 femoral, 38 external carotid, 18 coronary). Guidewire times were not significantly different across the simulated network latency times. Compared to 0 ms added latency, both the procedural impact and perceived lag scores were significantly higher when the added latency was 400 ms or greater (< 0.01). Remote endovascular intervention was feasible in all studied anatomic regions. Network latency of 400 ms or above is perceptible, although acceptable to operators, which suggests that remote robotic-assisted femoral, carotid or coronary arterial interventions should be performed with network latency below 400 ms to provide seamless remote device control.

Using conditional generative adversarial networks to reduce the effects of latency in robotic telesurgery

The introduction of surgical robots brought about advancements in surgical procedures. The applications of remote telesurgery range from building medical clinics in underprivileged areas, to placing robots abroad in military hot-spots where accessibility and diversity of medical experience may be limited. Poor wireless connectivity may result in a prolonged delay, referred to as latency, between a surgeon's input and action which a robot takes. In surgery, any micro-delay can injure a patient severely and, in some cases, result in fatality. One way to increase safety is to mitigate the effects of latency using deep learning aided computer vision. While the current surgical robots use calibrated sensors to measure the position of the arms and tools, in this work, we present a purely optical approach that provides a measurement of the tool position in relation to the patient's tissues. This research aimed to produce a neural network that allowed a robot to detect its own mechanical manipulator arms. A conditional generative adversarial network (cGAN) was trained on 1107 frames of a mock gastrointestinal robotic surgery from the 2015 EndoVis Instrument Challenge and corresponding hand-drawn labels for each frame. When run on new testing data, the network generated near-perfect labels of the input images which were visually consistent with the hand-drawn labels and was able to do this in 299 ms. These accurately generated labels can then be used as simplified identifiers for the robot to track its own controlled tools. These results show potential for conditional GANs as a reaction mechanism, such that the robot can detect when its arms move outside the operating area in a patient. This system allows for more accurate monitoring of the position of surgical instruments in relation to the patient's tissue, increasing safety measures that are integral to successful telesurgery systems.

Telerobotic Spinal Surgery Based on 5G Network: The First 12 Cases

Objective

The purpose of this study was to determine the efficacy and feasibility of 5th generation wireless systems (5G) telerobotic spinal surgery in our first 12 cases.

Methods

A total of 12 patients (5 males, 7 females; age, 23–71 years) with spinal disorders (4 thoracolumbar fractures, 6 lumbar spondylolisthesis, 2 lumbar stenosis) were treated with 5G telerobotic spinal surgery. Sixty-two pedicle screws were implanted.

Results

All patients had substantial relief from their symptoms. Screw placements were classified using Gertzbein-Robbins criteria. There were 59 grade A, 3 grade B. Mean operation time was 142.5 ± 46.7 minutes. Mean guiding wire insertion time was 41.3 ± 9.8 minutes. The deviation between the planned and actual positions was 0.76 ± 0.49 mm. No intraoperative adverse event was found.

Conclusion

5G remote robot-assisted spinal surgery is accurate and reliable. We conclude that 5G telerobotic spinal surgery is both efficacious and feasible for the management of spinal diseases with safety.

[Exploration and prospect of 5G application in telemedicine]

The combination of network and medical field gave birth to telemedicine.The implementation of telemedicine can improve the uneven distribution of regional medical resources, reduce the working pressure of medical staff, shorten the distance between medical staff and patients and medical staff, and improve the timeliness of monitoring, diagnosis and treatment.The continuous development of telemedicine relies on the continuous innovation of network communication technology, the latest 5(th) generation wireless systems (5G) is bringing significant changes to mobile communication and other related industries by virtue of its advantages of high data rate and low latency. This paper reviews the development of telemedicine, introduces the characteristics of 5G technology, combines the research results of 5G technology applied in the medical field at home and abroad, and prospects the development of this field in the future.