1 introduction
Robotics are increasingly playing an important role in medicine and surgery. The importance of the integration of robotic technologies in the medical field has only been amplified by the COVVI-19 pandemic and the subsequent demand for socially care and teleoperative medical assistance. Many recent developments in related fields, including, but without limiting itself, artificial intelligence (AI), automatic learning, gentle robotics and continuum and teleoperation, allow potential complications.
A crucial question when you consider the medical intervention assisted by the robot is whether the robot system is as effective, or even more, than a human surgeon. The key indicators of this efficiency include, but without limiting themselves, operating time and complications rate. This research subject aimed at relying on existing developments of surgery assisted by robots by exploring the role of robot systems in the reduction of operating times and complications, by studying occurrences, causes and Results of surgical complications, and by discussing how the robotics industry can tackle these problems for the future.
2 contributions
This number includes five contributions which deal with the robot assisted surgery in different perspectives, aimed at improving surgical performance with new solutions for the automatic endoscope advice (Grujthuijsen et al.), preoperative planning (Lambrechts et al.), classification of clinical profiles (Barile et al.), positioning of the robot base (Sunday and al.) and mini-invasive ultrasound scanning (Marahrens et al.).
Grujthuijsen et al. Focus on bi-manual surgical operations, which generally require a second surgeon to maneuver an endoscope and provide visual feedback to the operational surgeon. While robotic endoscope holders have been proposed, existing prototypes impose an additional cognitive load on the now solo surgeon, hampering their clinical acceptance. Vice versa, Grujthuijsen et al. Offers a new approach that combines the location of the offense with the surgical segmentation of tools and the visual service providing a synergistic interaction between surgeons and robotic endoscope holders. The system is validated with a study of bi-manual surgery.
Lambrechts et al. Propose an AI -based tool to improve the surgeon and the default preoperative plans specific to patients for knee arthroplasty. Since generic preoperative plans require long changes from time to time, a predictive method reduced by almost 40% the average number of corrections necessary to adapt a generic plan to a specific patient. This study included more than 5,400 operating plans, corrected by 39 surgeons.
Barile et al. Use automatic learning techniques to discriminate clinical plaques clinical profiles through connecting data of the thickness of gray matter. From a set of data from 90 patients with multiple sclerosis with four separate clinical profiles, the proposed pipeline reaches a successful classification in more than 70% of cases using six global graph metrics extracted from the morphological connection of gray matter patients. These promising results show the potential and efficiency of the proposed method in relation to complex MRI techniques.
Sunday and al. Aim for improving the efficiency of the operation by optimizing the basic location of surgical robots. The proposed method, based on robot capacity cards, identifies the optimal positioning of a surgical robot by considering not only the kinematics of the robot but also environmental constraints such as available access ports (for example, for laparoscopy ). This algorithm reduces the installation time while improving the configuration itself, thus increasing the acceptance of surgery assisted by the robot by surgeons and clinical staff.
Marahrens et al. Address the invasiveness of robotic ultrasound digitization. The digitization of autonomous ultrasounds has been sought for more than 2 decades, but mini-invasive operations are intrinsically limited by the inaccurate detection of force and unreliable cutscenes. In this work, these challenges are met with a fusion scheme of attitude sensors for improved kinematic detection and a visual algorithm of deep remuneration to ensure contact between the ultrasonic probe and the target surface.
3 Perspectives
This collection confirms that the scientific community is actively working on robotics and AI for surgical procedures, thus producing a significant increase in the performance and efficiency of these technologies; In the broader context of health care, robotics and artificial intelligence offer a wide range of tools and methods, and other achievements will be granted in the next future by studying the appropriate combinations of results so different, integrating Both hardware and software solutions.
Contributions from authors
All the authors listed made a substantial, direct and intellectual contribution to the work and approved it for publication.
Thanks
This research subject was carried out in collaboration with Alfredo Moral Pinzon of the Harvard Medical School, United States.
Conflict of interest
The authors declare that research has been carried out in the absence of commercial or financial relations which could be interpreted as a potential conflict of interest.
Publisher’s note
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Keywords: Surgical robots, mini-invasive surgery, robot assisted surgery, complications rate, operating time
Quote: Cafolla D, Calimeri F, Cao H, Russo M, Sapey-Marinier D and Zaffino P (2022) Editorial: Hot Subject: Reduction of operating times and complications rate thanks to surgery assisted by the robot. In front. Robot. IA 9: 1046321. Doi: 10.3389 / Frobt. 2022.1046321
Received: September 16, 2022; Accepted: September 27, 2022;
Posted: October 10, 2022.
Edited and examined by:
Sanja DogramadziThe University of Sheffield, United Kingdom
Copyright © 2022 Cafolla, Calimeri, Cao, Russo, Sapey-Marinier and Zaffino. This is an article in free access distributed under the terms of the Creative commons attribution license (CC by). The use, distribution or reproduction in other forums is authorized, provided that the authors of origin and the copyright (s) are credited and that the original publication in this review is cited, in accordance with Academic practice accepted. No use, distribution or reproduction is authorized which does not respect these terms.
*Correspondence: Daniele Cafolla, Y29udgfjdebkyw5pzwxly2fmbb2xsys5ldayjedaymdbhow ==