A novel hybrid 3D endoscope zooming and repositioning system : design and feasibility study

Background: Manipulation of the endoscope during minimally invasive surgery is a major source of inconvenience and discomfort. This report elucidates the architecture of a novel one-hand controlled endoscope positioning device and presents a practicability evaluation. Methods and materials: Setup time and total surgery time, number and duration of the manipulations, side effects of three-dimensional (3D) imaging, and ergonomic complaints were assessed by three surgeons during cadaveric and in vivo porcine trials. Results: Setup was accomplished in an average (SD) of 230 (120) seconds. The manipulation time was 3.87 (1.77) seconds for angular movements and 0.83 (0.24) seconds for zooming, with an average (SD) of 30.5 (16.3) manipulations per procedure. No side effects of 3D imaging or ergonomic complaints were reported. Conclusions: The integration of an active zoom into a passive endoscope holder delivers a convenient synergy between a human and a machine-controlled holding device. It is shown to be safe, simple, and intuitive to use and allows unrestrained autonomic control of the endoscope by the surgeon

Prevalence of haptic feedback in robot-mediated surgery : a systematic review of literature

© 2017 Springer-Verlag. This is a post-peer-review, pre-copyedit version of an article published in Journal of Robotic Surgery. The final authenticated version is available online at: https://doi.org/10.1007/s11701-017-0763-4With the successful uptake and inclusion of robotic systems in minimally invasive surgery and with the increasing application of robotic surgery (RS) in numerous surgical specialities worldwide, there is now a need to develop and enhance the technology further. One such improvement is the implementation and amalgamation of haptic feedback technology into RS which will permit the operating surgeon on the console to receive haptic information on the type of tissue being operated on. The main advantage of using this is to allow the operating surgeon to feel and control the amount of force applied to different tissues during surgery thus minimising the risk of tissue damage due to both the direct and indirect effects of excessive tissue force or tension being applied during RS. We performed a two-rater systematic review to identify the latest developments and potential avenues of improving technology in the application and implementation of haptic feedback technology to the operating surgeon on the console during RS. This review provides a summary of technological enhancements in RS, considering different stages of work, from proof of concept to cadaver tissue testing, surgery in animals, and finally real implementation in surgical practice. We identify that at the time of this review, while there is a unanimous agreement regarding need for haptic and tactile feedback, there are no solutions or products available that address this need. There is a scope and need for new developments in haptic augmentation for robot-mediated surgery with the aim of improving patient care and robotic surgical technology further.Peer reviewe

Spider surgical system versus multiport laparoscopic surgery. Performance comparison on a surgical simulator

BACKGROUND: The rising interest towards minimally invasive surgery has led to the introduction of laparo-endoscopic single site (LESS) surgery as the natural evolution of conventional multiport laparoscopy. However, this new surgical approach is hampered with peculiar technical difficulties. The SPIDER surgical system has been developed in the attempt to overcome some of these challenges. Our study aimed to compare standard laparoscopy and SPIDER technical performance on a surgical simulator, using standardized tasks from the Fundamentals of Laparoscopic Surgery (FLS). METHODS: Twenty participants were divided into two groups based on their surgical laparoscopic experience: 10 PGY1 residents were included in the inexperienced group and 10 laparoscopists in the experienced group. Participants performed the FLS pegboard transfers task and pattern cutting task on a laparoscopic box trainer. Objective task scores and subjective questionnaire rating scales were used to compare conventional laparoscopy and SPIDER surgical system. RESULTS: Both groups performed significantly better in the FLS scores on the standard laparoscopic simulator compared to the SPIDER. Inexperienced group: Task 1 scores (median 252.5 vs. 228.5; p = 0.007); Task 2 scores (median 270.5 vs. 219.0; p = 0.005). Experienced group: Task 1 scores (median 411.5 vs. 309.5; p = 0.005); Task 2 scores (median 418.0 vs. 331.5; p = 0.007). Same aspects were highlighted for the subjective evaluations, except for the inexperienced surgeons who found both devices equivalent in terms of ease of use only in the peg transfer task. CONCLUSIONS: Even though the SPIDER is an innovative and promising device, our study proved that it is more challenging than conventional laparoscopy in a population with different degrees of surgical experience. We presume that a possible way to overcome such challenges could be the development of tailored training programs through simulation methods. This may represent an effective way to deliver training, achieve mastery and skills and prepare surgeons for their future clinical experience

Robot Autonomy for Surgery

Autonomous surgery involves having surgical tasks performed by a robot operating under its own will, with partial or no human involvement. There are several important advantages of automation in surgery, which include increasing precision of care due to sub-millimeter robot control, real-time utilization of biosignals for interventional care, improvements to surgical efficiency and execution, and computer-aided guidance under various medical imaging and sensing modalities. While these methods may displace some tasks of surgical teams and individual surgeons, they also present new capabilities in interventions that are too difficult or go beyond the skills of a human. In this chapter, we provide an overview of robot autonomy in commercial use and in research, and present some of the challenges faced in developing autonomous surgical robots

ToolNet: Holistically-Nested Real-Time Segmentation of Robotic Surgical Tools

Real-time tool segmentation from endoscopic videos is an essential part of many computer-assisted robotic surgical systems and of critical importance in robotic surgical data science. We propose two novel deep learning architectures for automatic segmentation of non-rigid surgical instruments. Both methods take advantage of automated deep-learning-based multi-scale feature extraction while trying to maintain an accurate segmentation quality at all resolutions. The two proposed methods encode the multi-scale constraint inside the network architecture. The first proposed architecture enforces it by cascaded aggregation of predictions and the second proposed network does it by means of a holistically-nested architecture where the loss at each scale is taken into account for the optimization process. As the proposed methods are for real-time semantic labeling, both present a reduced number of parameters. We propose the use of parametric rectified linear units for semantic labeling in these small architectures to increase the regularization ability of the design and maintain the segmentation accuracy without overfitting the training sets. We compare the proposed architectures against state-of-the-art fully convolutional networks. We validate our methods using existing benchmark datasets, including ex vivo cases with phantom tissue and different robotic surgical instruments present in the scene. Our results show a statistically significant improved Dice Similarity Coefficient over previous instrument segmentation methods. We analyze our design choices and discuss the key drivers for improving accuracy.Comment: Paper accepted at IROS 201

Text Promptable Surgical Instrument Segmentation with Vision-Language Models

In this paper, we propose a novel text promptable surgical instrument segmentation approach to overcome challenges associated with diversity and differentiation of surgical instruments in minimally invasive surgeries. We redefine the task as text promptable, thereby enabling a more nuanced comprehension of surgical instruments and adaptability to new instrument types. Inspired by recent advancements in vision-language models, we leverage pretrained image and text encoders as our model backbone and design a text promptable mask decoder consisting of attention- and convolution-based prompting schemes for surgical instrument segmentation prediction. Our model leverages multiple text prompts for each surgical instrument through a new mixture of prompts mechanism, resulting in enhanced segmentation performance. Additionally, we introduce a hard instrument area reinforcement module to improve image feature comprehension and segmentation precision. Extensive experiments on several surgical instrument segmentation datasets demonstrate our model's superior performance and promising generalization capability. To our knowledge, this is the first implementation of a promptable approach to surgical instrument segmentation, offering significant potential for practical application in the field of robotic-assisted surgery. Code is available at https://github.com/franciszzj/TP-SIS

Design of Novel Sensors and Instruments for Minimally Invasive Lung Tumour Localization via Palpation

Minimally Invasive Thoracoscopic Surgery (MITS) has become the treatment of choice for lung cancer. However, MITS prevents the surgeons from using manual palpation, thereby often making it challenging to reliably locate the tumours for resection. This thesis presents the design, analysis and validation of novel tactile sensors, a novel miniature force sensor, a robotic instrument, and a wireless hand-held instrument to address this limitation. The low-cost, disposable tactile sensors have been shown to easily detect a 5 mm tumour located 10 mm deep in soft tissue. The force sensor can measure six degrees of freedom forces and torques with temperature compensation using a single optical fiber. The robotic instrument is compatible with the da Vinci surgical robot and allows the use of tactile sensing, force sensing and ultrasound to localize the tumours. The wireless hand-held instrument allows the use of tactile sensing in procedures where a robot is not available