Article

Supervised autonomous robotic soft tissue surgery

Authors:
To read the full-text of this research, you can request a copy directly from the authors.

Abstract

The current paradigm of robot-assisted surgeries (RASs) depends entirely on an individual surgeon's manual capability. Autonomous robotic surgery - removing the surgeon's hands - promises enhanced efficacy, safety, and improved access to optimized surgical techniques. Surgeries involving soft tissue have not been performed autonomously because of technological limitations, including lack of vision systems that can distinguish and track the target tissues in dynamic surgical environments and lack of intelligent algorithms that can execute complex surgical tasks. We demonstrate in vivo supervised autonomous soft tissue surgery in an open surgical setting, enabled by a plenoptic three-dimensional and near-infrared fluorescent (NIRF) imaging system and an autonomous suturing algorithm. Inspired by the best human surgical practices, a computer program generates a plan to complete complex surgical tasks on deformable soft tissue, such as suturing and intestinal anastomosis. We compared metrics of anastomosis - including the consistency of suturing informed by the average suture spacing, the pressure at which the anastomosis leaked, the number of mistakes that required removing the needle from the tissue, completion time, and lumen reduction in intestinal anastomoses - between our supervised autonomous system, manual laparoscopic surgery, and clinically used RAS approaches. Despite dynamic scene changes and tissue movement during surgery, we demonstrate that the outcome of supervised autonomous procedures is superior to surgery performed by expert surgeons and RAS techniques in ex vivo porcine tissues and in living pigs. These results demonstrate the potential for autonomous robots to improve the efficacy, consistency, functional outcome, and accessibility of surgical techniques.

No full-text available

Request Full-text Paper PDF

To read the full-text of this research,
you can request a copy directly from the authors.

... (1) Computer planned surgical path can be obtained by combining the experience of more than one expert surgeon. Their previous experience can be embedded in the difficult surgical conditions [2]. (2) During the training procedure, the novice surgeon can practice under the guidance of optimal planned surgical paths, which is conducive to the novice surgeon to learn the expert surgeons' experience [3]. ...
... Their previous experience can be embedded in the difficult surgical conditions [2]. (2) During the training procedure, the novice surgeon can practice under the guidance of optimal planned surgical paths, which is conducive to the novice surgeon to learn the expert surgeons' experience [3]. (3) The autonomy of current master-follower surgical robots [4,5] can be enhanced by autonomously tracking the planned surgical path. ...
... (3) The autonomy of current master-follower surgical robots [4,5] can be enhanced by autonomously tracking the planned surgical path. It has been demonstrated that the semiautonomous robot assisted surgery provides potential access to optimal surgical outcomes [2]. shapes, the vessel for instance. ...
Article
Full-text available
Automatic surgical path planning of the passive flexible tool encounters a prohibitive challenge, typically in endovascular surgery (ES). The key problem is that unstructured surgical environment and tools’ unpredictable motion is hard to be explicitly modeled. We propose a generative adversarial networks (GAN)-based framework (defined as surgical GAN) towards automatic guidewire path planning in real time for ES. A novel GAN architecture is proposed by combining convolutional neural networks (CNN) and long short-term memory networks (LSTM), which extracts and fuses the spatial features in medical images and temporal features of historical tool path as the conditional information. It inputs the surgical state information and continuously outputs the local future path of the guidewire tip. A training dataset (3.5*105 samples) is collected under laboratory conditions with 10 surgeons. Effects of different CNN architectures and path planning length on network performance are investigated. User experiments, with the tasks delivering the guidewire tip inside a vascular model (endovascular evaluator) from the aortic arch into the left common carotid artery (LCCA), left subclavian artery (LSCA), or brachiocephalic trunk, are conducted with 10 novice surgeons in an operating room. The results shows significant improvement of a path planning accuracy with surgical GAN compared with baseline networks (from 46.2%-69.78%) and the non-rigid registration method (72.94%). Results of user experiments demonstrate an overall better task performance with the guidance of planned surgical path. Collectively, surgical GAN can achieve real-time path planning of the guidewire in simulated ES, and holds great potential for novice training and robotic ES autonomy.
... The pre-operative image frames were then aligned with the navigation frames using the Iterative Closest Point algorithm. 21 In a follow-up study 22 in 2016, the research group improved the STAR by adding a plenoptic 3D and near-infrared fluorescent imaging system (see Figure 4E). The system has been proven to complete suturing tasks faster and more consistently than laparoscopic, and RAS approaches in a 1-week survival study on piglets. ...
... Standardisation of techniques will lead to reduced variation in clinical outcomes. 25 Automated handling of sensory information can provide more precision and less error than humans, 22 and human factors such as stress and fatigue would be minimised in long and intensive surgical situations. 26 All-in-all, including autonomy in surgery, can more consistently protect the health and safety of the patients, which is the ultimate goal of the operation. ...
... Despite all the benefits of autonomous surgical systems, the goal is not to replace surgeons but to improve safety and clinical outcomes by expanding human capability through enhanced vision, dexterity, and AI. 22 Even though there are currently some concerns related to autonomy in medical robotics, the future is still promising, and more and more research is making progress towards full autonomy. ...
Article
Full-text available
Background From traditional open surgery to laparoscopic surgery and robot-assisted surgery, advances in robotics, machine learning, and imaging are pushing the surgical approach to-wards better clinical outcomes. Pre-clinical and clinical evidence suggests that automation may standardise techniques, increase efficiency, and reduce clinical complications. Methods A PRISMA-guided search was conducted across PubMed and OVID. Results Of the 89 screened articles, 51 met the inclusion criteria, with 10 included in the final review. Automatic data segmentation, trajectory planning, intra-operative registration, trajectory drilling, and soft tissue robotic surgery were discussed. Conclusion Although automated surgical systems remain conceptual, several research groups have developed supervised autonomous robotic surgical systems with increasing consideration for ethico-legal issues for automation. Automation paves the way for precision surgery and improved safety and opens new possibilities for deploying more robust artificial intelligence models, better imaging modalities and robotics to improve clinical outcomes.
... Artificial Intelligence (AI) is a set of technologies to simulate human intelligence processes by machines. The AI covers a broad spectrum of applications such as automation of cars and industries (Shadrin et al. 2017;Hyder et al. 2019), Internet-ofthings (IoT) (Chiang and Zhang 2016), computer vision (Guo et al. 2016;Jiang et al. 2017;Caffe 2021;Abadi et al. 1603), Natural language processing (NLP) (Alshahrani and Kapetanios 2016;Sarrouti and Alaoui 2017a, b;Kim 2010), and robotics (Rath et al. 2018;Narayan et al. 2018Narayan et al. , 2020Shademan et al. 2016). Shadrin et al. (2017) designed an autonomous car maneuvering decision system based on AI to increase automation efficiency. ...
... NLP can be implemented to learn a foreign language in a computer-based learning module (Kim 2010). AI has also been implemented in humanoid robots (Rath et al. 2018), surgical robots (Narayan et al. 2018;Shademan et al. 2016), rehabilitation robots , and so on. ...
... AI-based question-answering systems (Sarrouti and Alaoui 2017a, b) and various other applications (Rodriguez-Esteban et al. 2006;Athenikos and Han 2010) of AI use data-mining of the medical database. AI systems can assist in surgeries for surgical procedures (e.g., stitching) (Shademan et al. 2016) and surgical robots (Attanasio et al. 2021). Neuro-prosthesis are designed to monitor urinary bladder volume in patients with neurological disorders (Mendez et al. 2013a, b). ...
Chapter
A phenomenal surge in data generation, accessibility, storage, and processing hardware capacitates the artificial intelligence (AI)-based learning algorithms to solve the nature-inspired complex problems in day-to-day life. Fine-tuned intelligent models can outperform human involvement in a repertoire of domains, significantly impacting performance and productivity metrics. AI technologies are being utilized nowadays in several fields of application in healthcare, such as predictive modeling for neurological disorders, bioinformatics, surgical procedures, physical rehabilitation, medical robots, and management of clinical data in hospitals. With the ever-evolving nature of state-of-the-art learning models, the influence of AI in healthcare is constantly changing. This necessitates the need for a comprehensive review of the current scenario of AI applications in healthcare. In this work, a systematic review of AI technologies in the different levels of healthcare, ranging from benign research to full-fledged clinical setups, has been carried out for the last 10 years. Primarily, the integration of AI tools in three broad categories of healthcare, i.e., clinical settings, biomedical computations, and pharmaceutical industries, is introduced. Thereafter, this work provides an overview of fundamental and advanced forms of different AI techniques with recent developments. A PRISMA statement is provided to show the inclusion and exclusion criteria of the articles reviewed while conducting the systematic review. Based on articles selected and reviewed, the application of AI in different clinical settings is presented in a comprehensive yet systematic manner. Furthermore, the ethical and legal issues about AI implementation in healthcare domains are reviewed. The challenges and possible opportunities of deploying AI in real-life settings are discussed. Finally, the conclusion of the current work is presented. This review will engage the researchers to understand the merits and demerits of applying AI for healthcare applications.
... LoA 1 is implemented in the form of shared control for reducing the complexity of steering flexible robotic endoscopes (23). The first demonstration of LoA 2 (task autonomy) via in vivo open surgeries (24) was enabled via a robotic suturing tool controlled by a robot arm and a dual-channel near-infrared (NIR) and plenoptic threedimensional (3D) camera that allowed the robot to detect the target tissue (stabilized outside of the body) and its landmarks, calculate a linear suture plan on the tissue, and execute the suture placement step by step under human supervision. Recent methods demonstrate LoA 2 laparoscopic in vivo hernia repair for porcine models (25). ...
... Although the system does require manual fine adjustment of the robot to correct positioning if a stitch is missed, more than 83% of the suturing task is completed autonomously using this workflow. In our previous work for open surgical intestinal anastomosis (24), the tissue tracking only considered a stationary tissue without the breathing motions, only one linear suture plan option without noise prefiltering and collision prevention was considered, autonomous replanning suggestions were not included, the operator needed to monitor each substep of the suturing procedure, and the tool failure monitoring and autonomous camera motion control were not implemented. Consequently, only 57.8% of the sutures were completed autonomously with no adjustments. ...
... For the STAR study group, an NIR marker tracking algorithm was used to trigger robot motion to the planned suture point and to enforce that suturing occurs during the rest phase of the breathing cycle. A target suture spacing of 3 mm was selected on the basis of our previous results in (24), which considers the tissue thickness T, bite depth H, and suture spacing S for a leak-free anastomosis [see figure 1G in (24)]. For the LAP and RAS study groups, surgeons were instructed to suture with the same spacing and consistency that they would perform in a human patient. ...
Article
Autonomous robotic surgery has the potential to provide efficacy, safety, and consistency independent of individual surgeon’s skill and experience. Autonomous anastomosis is a challenging soft-tissue surgery task because it requires intricate imaging, tissue tracking, and surgical planning techniques, as well as a precise execution via highly adaptable control strategies often in unstructured and deformable environments. In the laparoscopic setting, such surgeries are even more challenging because of the need for high maneuverability and repeatability under motion and vision constraints. Here we describe an enhanced autonomous strategy for laparoscopic soft tissue surgery and demonstrate robotic laparoscopic small bowel anastomosis in phantom and in vivo intestinal tissues. This enhanced autonomous strategy allows the operator to select among autonomously generated surgical plans and the robot executes a wide range of tasks independently. We then use our enhanced autonomous strategy to perform in vivo autonomous robotic laparoscopic surgery for intestinal anastomosis on porcine models over a 1-week survival period. We compared the anastomosis quality criteria—including needle placement corrections, suture spacing, suture bite size, completion time, lumen patency, and leak pressure—of the developed autonomous system, manual laparoscopic surgery, and robot-assisted surgery (RAS). Data from a phantom model indicate that our system outperforms expert surgeons’ manual technique and RAS technique in terms of consistency and accuracy. This was also replicated in the in vivo model. These results demonstrate that surgical robots exhibiting high levels of autonomy have the potential to improve consistency, patient outcomes, and access to a standard surgical technique.
... Robot-assisted surgery (RAS) has revolutionized the minimally invasive surgery by remarkably extending the dexterity and overall capability of surgeons. The robotic system controls the movement of surgical instruments, enabling efficient manipulation and vivid observation for many surgical tasks [1]- [3]. Intelligent parsing of such instruments, e.g., identifying their types or positions, is highly desired for promoting cognitive assistance to surgeon perception [4], operating workflow optimization [5], and skill assessment [6], [7]. ...
... Training. The time interval τ between prior frame and current frame is in the range of [1,10]. Our model is implemented in Pytorch and trained with a NVIDIA Titan Xp GPU. ...
Preprint
Full-text available
Surgical instrument segmentation -- in general a pixel classification task -- is fundamentally crucial for promoting cognitive intelligence in robot-assisted surgery (RAS). However, previous methods are struggling with discriminating instrument types and instances. To address the above issues, we explore a mask classification paradigm that produces per-segment predictions. We propose TraSeTR, a novel Track-to-Segment Transformer that wisely exploits tracking cues to assist surgical instrument segmentation. TraSeTR jointly reasons about the instrument type, location, and identity with instance-level predictions i.e., a set of class-bbox-mask pairs, by decoding query embeddings. Specifically, we introduce the prior query that encoded with previous temporal knowledge, to transfer tracking signals to current instances via identity matching. A contrastive query learning strategy is further applied to reshape the query feature space, which greatly alleviates the tracking difficulty caused by large temporal variations. The effectiveness of our method is demonstrated with state-of-the-art instrument type segmentation results on three public datasets, including two RAS benchmarks from EndoVis Challenges and one cataract surgery dataset CaDIS.
... Surgical suturing and knot tying is among one of these sub-tasks which is tedious yet important [14], [15], and it exists from in-vitro cuticle wound closure [13] to in-vivo transanal total mesorectal excision (taTME) [16], and from macro-scale suturing in laparoscopic hysterectomy [17] to micro-scale endoscopic vascular anastomosis [18]. To reduce fatigues from surgeons when conducting this manipulation, researchers put their attentions on developments of automation skills in the aspects of the task planning [19], [20], soft tissue manipulation [21], [22], hardware design [23], [24], learning-based robotic manipulations [25], [26], and etc. However, some of these on-the-shelf approaches only focused on generations of system level human-machine collaborative modes [23], [26] for surgical knot tying, in which the robot needs continuous supervision and control from human. ...
... To reduce fatigues from surgeons when conducting this manipulation, researchers put their attentions on developments of automation skills in the aspects of the task planning [19], [20], soft tissue manipulation [21], [22], hardware design [23], [24], learning-based robotic manipulations [25], [26], and etc. However, some of these on-the-shelf approaches only focused on generations of system level human-machine collaborative modes [23], [26] for surgical knot tying, in which the robot needs continuous supervision and control from human. In addition, other works focused on automating the sub-tasks of suture stitching [20], [24], [25] and its looping operations [13], [19]. ...
Article
To realize a higher-level autonomy of surgical knot tying in minimally invasive surgery (MIS), automated suture grasping, which bridges the suture stitching and looping procedures, is an important yet challenging task needs to be achieved. This paper presents a holistic framework with image-guided and automation techniques to robotize this operation even under complex environments. The whole task is initialized by suture segmentation, in which we propose a novel semi-supervised learning architecture featured with a suture-aware loss to pertinently learn its slender information using both annotated and unannotated data. With successful segmentation in stereo-camera, we develop a Sampling-based Sliding Pairing (SSP) algorithm to online optimize the suture's 3D shape. By jointly studying the robotic configuration and the suture's spatial characteristics, a target function is introduced to find the optimal grasping pose of the surgical tool with Remote Center of Motion (RCM) constraints. To compensate for inherent errors and practical uncertainties, a unified grasping strategy with a novel vision-based mechanism is introduced to autonomously accomplish this grasping task. Our framework is extensively evaluated from learning-based segmentation, 3D reconstruction, and image-guided grasping on the da Vinci Research Kit (dVRK) platform, where we achieve high performances and successful rates in perceptions and robotic manipulations. These results prove the feasibility of our approach in automating the suture grasping task, and this work fills the gap between automated surgical stitching and looping, stepping towards a higher-level of task autonomy in surgical knot tying.
... Robots could absorb activities currently carried out by professionals [22,24], which would challenge traditional healthcare practices [23,25]. To what extent is it possible to foresee a near-future scenario in which minor routine surgery is directed by robots? ...
... By doing so, RAS improves functional outcomes [26][27][28][29][30] and reduces morbidity rates for certain procedures [31,43]. Furthermore, RAS reduces the risk of surgery-related adverse events [43][44][45] by reducing operating times and technical errors, by improving access to areas of the body that are hard to reach, and by improving outcomes by eliminating (or minimising) the potential for human error, such as a surgeon's tremors and vulnerability to fatigue [25], thereby helping the patient to recover faster and ensuring that the patient's hospital stay is shorter [46][47][48]. This also leads to savings in the financial [27], time and psychological costs associated with the process [49][50][51]. ...
Article
Full-text available
1) Background: The goal of the paper was to establish the factors that influence how people feel about having a medical operation performed on them by a robot. (2) Methods: Data were obtained from a 2017 Flash Eurobarometer (number 460) of the European Commission with 27,901 citizens aged 15 years and over in the 28 countries of the European Union. Logistic regression (odds ratios, OR) to model the predictors of trust in robot-assisted surgery was calculated through moti-vational factors, using experience and sociodemographic independent variables. (3) Results: The results obtained indicate that, as the experience of using robots increases, the predictive coefficients related to information, attitude, and perception of robots become more negative. Furthermore, so-ciodemographic variables played an important predictive role. The effect of experience on trust in robots for surgical interventions was greater among men, people between 40 and 54 years old, and those with higher educational levels. (4) Conclusions: The results show that trust in robots goes beyond rational decision-making, since the final decision about whether it should be a robot that performs a complex procedure like a surgical intervention depends almost exclusively on the pa-tient's wishes.
... Automating monotonous and time consuming subtasks may decrease the cognitive load on the surgeon, who could then better focus on the more critical steps of the operation [10,11]. Currently, many research groups are working on this problem [12,13]; some groups chose to work in ex vivo (or rarely in vivo) [14,15] or realistic phantom environments [16], but simplified silicone phantoms are utilized mostly [15,[17][18][19][20][21]. In the most recent years, the automation of simple surgical training exercises on rigid [22][23][24][25][26][27][28] or deformable [29,30] phantoms tends to receive increasing attention. ...
... Nguyen et al. [30] measured the accuracy of pattern cutting next to autonomous tensioning. In the study of Shademan et al. [14], autonomous end-to-end anastomosis is presented and validated in vivo on porcine, where number of sutures, number of suturing mistakes, leak pressure, luminal diameter reduction, weight at surgery, and weight at sacrifice are measured and compared to manual execution. ...
Article
Full-text available
Robot-Assisted Minimally Invasive Surgery (RAMIS) has reshaped the standard clinical practice during the past two decades. Many believe that the next big step in the advancement of RAMIS will be partial autonomy, which may reduce the fatigue and the cognitive load on the surgeon by performing the monotonous, time-consuming subtasks of the surgical procedure autonomously. Although serious research efforts are paid to this area worldwide, standard evaluation methods, metrics, or benchmarking techniques are still not formed. This article aims to fill the void in the research domain of surgical subtask automation by proposing standard methodologies for performance evaluation. For that purpose, a novel characterization model is presented for surgical automation. The current metrics for performance evaluation and comparison are overviewed and analyzed, and a workflow model is presented that can help researchers to identify and apply their choice of metrics. Existing systems and setups that serve or could serve as benchmarks are also introduced and the need for standard benchmarks in the field is articulated. Finally, the matter of Human–Machine Interface (HMI) quality, robustness, and the related legal and ethical issues are presented.
... Medical robots enable enhanced precision, safety, and efficacy in various medical procedures that would otherwise be limited by human vision and dexterity [1,2]. Improvements in medical imaging, robotic control, and miniaturized computing have paved the way for the development of complex medical robots. ...
... Improvements in medical imaging, robotic control, and miniaturized computing have paved the way for the development of complex medical robots. These devices and technology have been implemented largely in the surgical field where accurate motion control and improved vision are key for achieving successful results [1,[3][4][5]. However, outside of the operating room, robotics has seen limited clinical use. ...
Article
Medical robots provide enhanced dexterity, vision, and safety for a broad range of procedures. In this paper, we present a hand-held, robotic device capable of performing peripheral catheter insertions with high accuracy and repeatability. The device utilizes a combination of ultrasound imaging, miniaturized robotics, and machine learning to safely and efficiently introduce a catheter sheath into a peripheral blood vessel. Here, we present the mechanical design and experimental validation of the device, known as VeniBot. Additionally, we present results on our ultrasound deep learning algorithm for vessel segmentation, and performance on tissue-mimicking phantom models that simulate difficult peripheral catheter placement. Overall, the device achieved first-attempt success rates of 97 ± 4% for vessel punctures and 89 ± 7% for sheath cannulations on the tissue mimicking models (n=240). The results from these studies demonstrate the viability of a hand-held device for performing semi-automated peripheral catheterization. In the future, the use of this device has the potential to improve clinical workflow and reduce patient discomfort by assuring a safe and efficient procedure.
... The same liability issue concerns the evolution and adoption of AI-based surgical robots. Such robots can already independently carry out parts of surgical operations like, for instance, performing intestinal anastomoses more precisely and faster than experienced surgeons [69]. The benefits of such robots have already been stated and measured, such as a more precise visualization of the operating field, better movements thanks to the articulating tools, the elimination of vibrations and fewer medical errors [29], leading to better outcomes both for the surgical patients as well as the hospital or institution adopting such a technology [70]. ...
Chapter
In the recent world, making the proper decisions in business is challenging and complicated, especially on sales data. Sales are the most valuable part of a business. Only the sales report of a business is not enough for today’s business development. The activity needs to get an insight into sales using data because data-driven decision is more impactful. The purpose of the research is to develop an affordable and approachable model to deliver a business insight that helps you to understand your business and support to make business decisions faster. In this piece of research work, a model is proposed to develop an affordable simple sales data insight, helping with business intelligence technique and cloud database. This model uses a set of data, with ad hoc query, statistical analysis, some mathematical equations, and data visualization is a key component to gain a proactive and data-driven solution. Using such methodologies and approaches, our model generated certain key performance indicators and a quick snapshot of the sales situation, allowing company owners to see trends and predict sales process weaknesses. Not only that proposed model also provides geolocations sales state and cross ponding sales preview on a visualization mode.
... Anthropologists have recorded ancient suture methods that include wound closure by allowing ants or beetles to bite opposing sides of a wound then detaching the insect's body, leaving the mandible stitch in place and the wound closed under the compression force of the bite [1]. Modern suturing is performed via manual or robotic suture needle manipulation, with minimally invasive surgeries (MIS) performed using robotic suturing instruments achieving increasing levels of autonomy in recent years [2]. Minimally invasive surgeries (MISs) currently involve inserting miniature manipulators into a patient via a single incision [3] or a natural orifice [4]. ...
Article
Full-text available
The application of force in surgical settings is typically accomplished via physical tethers to the surgical tool. While physical tethers are common and critical, some internal surgical procedures may benefit from a tetherless operation of needles, possibly reducing the number of ports in the patient or the amount of tissue damage caused by tools used to manipulate needles. Magnetic field gradients can dynamically apply kinetic forces to magnetizable objects free of such tethers, possibly enabling ultra-minimally invasive robotic surgical procedures. We demonstrate the untethered manipulation of a suture needle in vitro, exemplified by steering through narrow holes, as well as needle penetration through excised rat and human tissues. We present proof of principle manipulations for the fully untethered control of a minimally modified, standard stainless steel surgical suture needle.
... The same liability issue concerns the evolution and adoption of AI-based surgical robots. Such robots can already independently carry out parts of surgical operations like, for instance, performing intestinal anastomoses more precisely and faster than experienced surgeons [69]. The benefits of such robots have already been stated and measured, such as a more precise visualization of the operating field, better movements thanks to the articulating tools, the elimination of vibrations and fewer medical errors [29], leading to better outcomes both for the surgical patients as well as the hospital or institution adopting such a technology [70]. ...
Chapter
There are many fascinating headings that can be investigated. Newspapers, blogs, articles print a lot of content and depict a lot about a person’s positive and negative aspects. In this chapter, we have explained how we can estimate those numbers of positivity, negativity, or neutrality about the product or services provided by an organization. This is the way toward recognizing and arranging sentiments communicated in a bit of content, particularly to decide if an author’s disposition toward a point/item is sure, negative, or impartial. It is utilized to check how positive or how negative an announcement is. This analysis is like manner called sentiment mining or opinion AI, is the path toward deciding if a touch of making is sure, negative, or unprejudiced. A run of the mill use case for this development is to discover how people feel about a subject. Sentiment analysis is broadly connected to audits and internet-based life for an assortment of utilizations. Sentiment analysis can be performed from various perspectives. Numerous brands and advertisers use watchword-based apparatuses that arrange information as positive/negative/impartial. Social media platforms play an important role in providing real time streaming data for such analysis. In this chapter we have tried to provide the complete pathway to do social media analytics.
... In comparison to manual laparoscopic surgery and clinically (using RAS approaches), the outcome of autonomous procedures was found superior to surgery performed by expert surgeons. The system received this despite dynamic scene changes and tissue movement during surgery [18]. ...
Preprint
Full-text available
Robotic surgery has increased the domain of surgeries possible. Several examples of partial surgical automation have been seen in the past decade. We break down the path of automation tasks into features required and provide a checklist that can help reach higher levels of surgical automation. Finally, we discuss the current challenges and advances required to make this happen.
... Different models, such as ZFNet [20], VGG [21], GoogLeNet [22], and Figure 3); correspondingly, that of humans was approximately 5%. It has dramatically improved tasks in different scientific and industrial fields including not only computer vision but also speech recognition, drug discovery, clinical surgery, and bioinformatics [24][25][26]. ...
Article
Full-text available
Deep learning has become an extremely popular method in recent years, and can be a powerful tool in complex, prior-knowledge-required areas, especially in the field of biomedicine, which is now facing the problem of inadequate medical resources. The application of deep learning in disease diagnosis has become a new research topic in dermatology. This paper aims to provide a quick review of the classification of skin disease using deep learning to summarize the characteristics of skin lesions and the status of image technology. We study the characteristics of skin disease and review the research on skin disease classification using deep learning. We analyze these studies using datasets, data processing, classification models, and evaluation criteria. We summarize the development of this field, illustrate the key steps and influencing factors of dermatological diagnosis, and identify the challenges and opportunities at this stage. Our research confirms that a skin disease recognition method based on deep learning can be superior to professional dermatologists in specific scenarios and has broad research prospects.
... Others have used a similar approach (avoiding prohibitively high costs) to develop master-slave systems working on the principle of semi-autonomous control (Bai et al., 2017;Zhou et al., 2018). Fully autonomous systems have also been developed, although human surgeon supervision may still be needed (Shademan et al., 2016). Fully autonomous unsupervised robotic systems for surgery would need to overcome safety concerns (Trevis et al., 2020). ...
Article
Full-text available
Background: Damaged cardiac tissues could potentially be regenerated by transplanting bioengineered cardiac patches to the heart surface. To be fully paradigm-shifting, such patches may need to be transplanted using minimally invasive robotic cardiac surgery (not only traditional open surgery). Here, we present novel robotic designs, initial prototyping and a new surgical operation for instruments to transplant patches via robotic minimally invasive heart surgery. Methods: Robotic surgical instruments and automated control systems were designed, tested with simulation software and prototyped. Surgical proof-of-concept testing was performed on a pig cadaver. Results: Three robotic instrument designs were developed. The first (called “Claw” for the claw-like patch holder at the tip) operates on a rack and pinion mechanism. The second design (“Shell-Beak”) uses adjustable folding plates and rods with a bevel gear mechanism. The third (“HeartStamp”) utilizes a stamp platform protruding through an adjustable ring. For the HeartStamp, rods run through a cylindrical structure designed to fit a uniportal Video-Assisted Thorascopic Surgery (VATS) surgical port. Designed to work with or without a sterile sheath, the patch is pushed out by the stamp platform as it protrudes. Two instrument robotic control systems were designed, simulated in silico and one of these underwent early ‘sizing and learning’ prototyping as a proof-of-concept. To reflect real surgical conditions, surgery was run “live” and reported exactly (as-it-happened). We successfully picked up, transferred and released a patch onto the heart using the HeartStamp in a pig cadaver model. Conclusion: These world-first designs, early prototypes and a novel surgical operation pave the way for robotic instruments for automated keyhole patch transplantation to the heart. Our novel approach is presented for others to build upon free from restrictions or cost—potentially a significant moment in myocardial regeneration surgery which may open a therapeutic avenue for patients unfit for traditional open surgery.
... Multi-sensor acquisition leads to a vast amount of sensor data that require efficient solutions for data compression, especially for haptic data [48]. Machine-learning approaches allow to model surgical skills based on annotated sensor data [16,49] and allow semi-automation of surgical skills such as knot-tying, suturing, laparoscope guidance, or sonography tasks [50][51][52][53]. ...
Article
Full-text available
In the early 2020s, the coronavirus pandemic brought the notion of remotely connected care to the general population across the globe. Oftentimes, the timely provisioning of access to and the implementation of affordable care are drivers behind tele-healthcare initiatives. Tele-healthcare has already garnered significant momentum in research and implementations in the years preceding the worldwide challenge of 2020, supported by the emerging capabilities of communication networks. The Tactile Internet (TI) with human-in-the-loop is one of those developments, leading to the democratization of skills and expertise that will significantly impact the long-term developments of the provisioning of care. However, significant challenges remain that require today’s communication networks to adapt to support the ultra-low latency required. The resulting latency challenge necessitates trans-disciplinary research efforts combining psychophysiological as well as technological solutions to achieve one millisecond and below round-trip times. The objective of this paper is to provide an overview of the benefits enabled by solving this network latency reduction challenge by employing state-of-the-art Time-Sensitive Networking (TSN) devices in a testbed, realizing the service differentiation required for the multi-modal human-machine interface. With completely new types of services and use cases resulting from the TI, we describe the potential impacts on remote surgery and remote rehabilitation as examples, with a focus on the future of tele-healthcare in rural settings.
... An entirely different situation arises in the case of so-called "robot surgeons," i.e., robots equipped with artificial intelligence sophisticated enough to enable them to perform operations autonomously. In 2016, researchers at the Children's National Health System in Washington DC designed a robot that could autonomously suture a pig intestine [49]. It is evident that when artificial intelligence is introduced, it is not always easy to attribute any error in the robot to the manufacturer, the programmer, or the certifying body. ...
Article
Full-text available
Telemedicine allows for the effective delivery of health care to patients at a distance through the application of information technology to the field of medicine. This is optimal during the COVID-19 pandemic to reduce interpersonal contact to mitigate contagion. Among the possible Telemedicine applications, there is Telesurgery, which involves more and more surgical specialties thanks to the numerous benefits in quality and cost containment. In the growing field of Telesurgery, its technical and legal implications must be considered. In this study, a traditional review of the scientific literature was carried out to identify the most relevant issues of interest in Telesurgery. The problematic legal aspects identified are mainly related to the difference in legislation between different geographical areas, which is critical in the case of malpractice. In addition, there is the possibility of a malicious hacker attack on the transmitted data stream either to steal sensitive data or to harm the patient. Finally, there are inherent difficulties with the technology used, such as latency issues in data transmission. All these critical issues are currently not adequately addressed by current legislation. Therefore, one can only hope for a legislative action to allow Telesurgery to be used safely.
... Artificial intelligence has made tremendous and remarkable progress in the health field [51], as it facilitates many of the problems related to filling out forms for admission in hospitals or clinics and preventing the surge of discounts at the reception desk. In recent times, the science of artificial intelligence has been able to contribute to the development of the healthcare system to be more effective in detecting diseases such as cancer [52], infections [53][54][55][56], and other diseases, in addition to the development of robots that perform surgeries and accurate diagnosis [57,58]. Recent statistics indicate that artificial intelligence developers have arrived at the stage of providing effective solutions to complex obstacles in healthcare management systems, thereby revolutionizing the medical field to eliminate inefficient systems prevailing in societies. ...
Article
Full-text available
In the modern era, many terms related to artificial intelligence, machine learning, and deep learning are widely used in domains such as business, healthcare, industries, and military. In these fields, the accurate prediction and analysis of data are crucial, regardless of how large the data are. However, using big data is confusing due to the rapid growth and massive development in public life, which requires a tremendous human effort in order to deal with such type of data and extract worthy information from it. Thus, the role of artificial intelligence begins in analyzing big data based on scientific techniques, especially in machine learning, whereby it can identify patterns of decision-making and reduce human intervention. In this regard, the significance role of artificial intelligence, machine learning and deep learning is growing rapidly. In this article, the authors decide to highlight these sciences by discussing how to develop and apply them in many decision-making domains. In addition, the influence of artificial intelligence in healthcare and the gains this science provides in the face of the COVID-19 pandemic are highlighted. This article concludes that these sciences have a significant impact, especially in healthcare, as well as the ability to grow and improve their methodology in decision-making. Additionally, artificial intelligence is a vital science, especially in the face of COVID-19.
... Previous works have tried to deal with the different sources of uncertainty in the surgical domain, e.g. implementing strategies for accurate instrument and anatomy localization [8], [9], online update of soft tissues models [10], [11], workflow recognition [12] and task model refinement [13], [14]. Model predictive control has also been exploited to deal with uncertainty at motion planning level [12], [15]. ...
Preprint
Full-text available
Autonomous robotic surgery requires deliberation, i.e. the ability to plan and execute a task adapting to uncertain and dynamic environments. Uncertainty in the surgical domain is mainly related to the partial pre-operative knowledge about patient-specific anatomical properties. In this paper, we introduce a logic-based framework for surgical tasks with deliberative functions of monitoring and learning. The DEliberative Framework for Robot-Assisted Surgery (DEFRAS) estimates a pre-operative patient-specific plan, and executes it while continuously measuring the applied force obtained from a biomechanical pre-operative model. Monitoring module compares this model with the actual situation reconstructed from sensors. In case of significant mismatch, the learning module is invoked to update the model, thus improving the estimate of the exerted force. DEFRAS is validated both in simulated and real environment with da Vinci Research Kit executing soft tissue retraction. Compared with state-of-the art related works, the success rate of the task is improved while minimizing the interaction with the tissue to prevent unintentional damage.
... An instance of explicit learning is represented by Smart Tissue Autonomous Robot (STAR) which performed better than human surgeons involved in an experimental anastomotic suturing study in a porcine model. This study has some limitations, however, and has not been reproduced [70]. ...
Article
Full-text available
Background Despite the extensive published literature on the significant potential of artificial intelligence (AI) there are no reports on its efficacy in improving patient safety in robot-assisted surgery (RAS). The purposes of this work are to systematically review the published literature on AI in RAS, and to identify and discuss current limitations and challenges. Materials and methods A literature search was conducted on PubMed, Web of Science, Scopus, and IEEExplore according to PRISMA 2020 statement. Eligible articles were peer-review studies published in English language from January 1, 2016 to December 31, 2020. Amstar 2 was used for quality assessment. Risk of bias was evaluated with the Newcastle Ottawa Quality assessment tool. Data of the studies were visually presented in tables using SPIDER tool. Results Thirty-five publications, representing 3436 patients, met the search criteria and were included in the analysis. The selected reports concern: motion analysis (n = 17), urology (n = 12), gynecology (n = 1), other specialties (n = 1), training (n = 3), and tissue retraction (n = 1). Precision for surgical tools detection varied from 76.0% to 90.6%. Mean absolute error on prediction of urinary continence after robot-assisted radical prostatectomy (RARP) ranged from 85.9 to 134.7 days. Accuracy on prediction of length of stay after RARP was 88.5%. Accuracy on recognition of the next surgical task during robot-assisted partial nephrectomy (RAPN) achieved 75.7%. Conclusion The reviewed studies were of low quality. The findings are limited by the small size of the datasets. Comparison between studies on the same topic was restricted due to algorithms and datasets heterogeneity. There is no proof that currently AI can identify the critical tasks of RAS operations, which determine patient outcome. There is an urgent need for studies on large datasets and external validation of the AI algorithms used. Furthermore, the results should be transparent and meaningful to surgeons, enabling them to inform patients in layman's words. Registration Review Registry Unique Identifying Number: reviewregistry1225.
... Similarly, Keller et al. [87] trained a policy with learning from demonstration and RL for a corneal needle to be autonomously guided with optical coherence tomography inside human cadaver corneas and showed superior path accuracy compared to manual insertion and path planning only. Baek et al. [88] used RL (Q-learning) for collision avoidance path planning in a very simplified cholecystectomy simulation. A policy was trained to move to the gallbladder while avoiding obstacles, achieving a notable learning curve over 5000 iterations in the simulation. ...
Article
Full-text available
Surgery faces a paradigm shift since it has developed rapidly in recent decades, becoming a high-tech discipline. Increasingly powerful technological developments such as modern operating rooms, featuring digital and interconnected equipment and novel imaging as well as robotic procedures, provide several data sources resulting in a huge potential to improve patient therapy and surgical outcome by means of Surgical Data Science. The emerging field of Surgical Data Science aims to improve the quality of surgery through acquisition, organization, analysis, and modeling of data, in particular using machine learning (ML). An integral part of surgical data science is to analyze the available data along the surgical treatment path and provide a context-aware autonomous action by means of ML methods. Autonomous actions related to surgical decision-making include preoperative decision support, intraoperative assistance functions, as well as robot-assisted actions. The goal is to democratize surgical skills and enhance the collaboration between surgeons and cyber-physical systems by quantifying surgical experience and making it accessible to machines, thereby improving patient therapy and outcome. The article introduces basic ML concepts as enablers for autonomous actions in surgery, highlighting examples for such actions along the surgical treatment path.
... Although commercially available robots with level 5 autonomy seem distant, some researchers already conceptualize them. Only performed on pigs so far (Greenemeier 2020), however, current robot surgeons cannot yet perform an entire surgery completely independent from the beginning to the end on humans [80]. The efforts to transit from the presently available level 3 robots towards level 4 robots indeed suggests that, in principle, the deployment of surgical robots with fully autonomous capabilities equivalent to level 5 is the ulterior motive of researchers and engineers working in this field [96]. ...
Article
Full-text available
Innovation in healthcare promises unparalleled potential in optimizing the production, distribution, and use of the health workforce and infrastructure, allocating system resources more efficiently, and streamline care pathways and supply chains. A recent innovation contributing to this is robot-assisted surgeries (RAS). RAS causes less damage to the patient's body, less pain and discomfort, shorter hospital stays, quicker recovery times, smaller scars, and less risk of complications. However, introducing a robot in traditional surgeries is not straightforward and brings about new risks that conventional medical instruments did not pose before. For instance, since robots are sophisticated machines capable of acting autonomously, the surgical procedure's outcome is no longer limited to the surgeon but may also extend to the robot manufacturer and the hospital. This article explores the influence of automation on stakeholder responsibility in surgery robotization. To this end, we map how the role of different stakeholders in highly autonomous robotic surgeries is transforming, explore some of the challenges that robot manufacturers and hospital management will increasingly face as surgical procedures become more and more automated, and bring forward potential solutions to ascertain clarity in the role of stakeholders before, during, and after robot-enabled surgeries (i.e. a Robot Impact Assessment (ROBIA), a Robo-Terms framework inspired by the international trade system 'Incoterms', and a standardized adverse event reporting mechanism). In particular, we argue that with progressive robot autonomy, performance, oversight, and support will increasingly be shared between the human surgeon, the support staff, and the robot (and, by extent, the robot manufacturer), blurring the lines of who is responsible if something goes wrong. Understanding the exact role of humans in highly autonomous robotic surgeries is essential to map liability and bring certainty concerning the ascription of responsibility. We conclude that the full benefits the use of robotic innovations and solutions in surgery could bring to healthcare providers and receivers cannot be realized until there is more clarity on the division of responsibilities channeling robot autonomy and human performance, support, and oversight; a transformation on the education and training of medical staff, and betterment on the complex interplay between manufacturers, healthcare providers, and patients.
... Conventional suturing relies on articulated tools and physical manipulation of the suturing device. Because of the large footprints of the manipulation tools, conventional suturing usually takes large surgical invasiveness, which will cause more tissue damage, longer recovery times, or other associated infections (37). Here, we demonstrate a wireless suture medical device performing wound suturing on a pigskin ex vivo. ...
Article
Wireless small-scale soft-bodied devices are capable of precise operation inside confined internal spaces, enabling various minimally invasive medical applications. However, such potential is constrained by the small output force and low work capacity of the current miniature soft actuators. To address this challenge, we report a small-scale soft actuator that harnesses the synergetic interactions between the coiled artificial muscle and radio frequency–magnetic heating. This wirelessly controlled actuator exhibits a large output force (~3.1 N) and high work capacity (3.5 J/g). Combining this actuator with different mechanical designs, its tensile and torsional behaviors can be engineered into different functional devices, such as a suture device, a pair of scissors, a driller, and a clamper. In addition, by assuming a spatially varying magnetization profile, a multilinked coiled muscle can have both magnetic field–induced bending and high contractile force. Such an approach could be used in various future untethered miniature medical devices.
... The ever-increasing availability of computational power has seen ML be applied across numerous disciplines in medicine, with surgery being no exception. ML and artificial intelligence (AI) has been used across diverse applications in surgery ranging from surgical workflow analysis 9 , to autonomous performance of simple tasks 10 , and postoperative mortality risk prediction 11 . This widespread use of ML has led to the development of the field of Surgical Data Science, which aims to improve the quality and value of surgery through data collection, organization, analysis, and modeling 12,13 . ...
Article
Full-text available
Accurate and objective performance assessment is essential for both trainees and certified surgeons. However, existing methods can be time consuming, labor intensive, and subject to bias. Machine learning (ML) has the potential to provide rapid, automated, and reproducible feedback without the need for expert reviewers. We aimed to systematically review the literature and determine the ML techniques used for technical surgical skill assessment and identify challenges and barriers in the field. A systematic literature search, in accordance with the PRISMA statement, was performed to identify studies detailing the use of ML for technical skill assessment in surgery. Of the 1896 studies that were retrieved, 66 studies were included. The most common ML methods used were Hidden Markov Models (HMM, 14/66), Support Vector Machines (SVM, 17/66), and Artificial Neural Networks (ANN, 17/66). 40/66 studies used kinematic data, 19/66 used video or image data, and 7/66 used both. Studies assessed the performance of benchtop tasks (48/66), simulator tasks (10/66), and real-life surgery (8/66). Accuracy rates of over 80% were achieved, although tasks and participants varied between studies. Barriers to progress in the field included a focus on basic tasks, lack of standardization between studies, and lack of datasets. ML has the potential to produce accurate and objective surgical skill assessment through the use of methods including HMM, SVM, and ANN. Future ML-based assessment tools should move beyond the assessment of basic tasks and towards real-life surgery and provide interpretable feedback with clinical value for the surgeon. PROSPERO: CRD42020226071
... Automated image analysis and segmentation [1], autonomous soft tissue suturing [2], and brain-machine interfaces [3]: these are technologies that until recently were only science fiction imaginings. They now all represent the state of the art in ML-based health care tools and all share one characteristic: all these systems are trained on patient data and can be quickly and automatically improved through retraining and on the basis of new patient data. ...
Article
Full-text available
One of the greatest strengths of artificial intelligence (AI) and machine learning (ML) approaches in health care is that their performance can be continually improved based on updates from automated learning from data. However, health care ML models are currently essentially regulated under provisions that were developed for an earlier age of slowly updated medical devices—requiring major documentation reshape and revalidation with every major update of the model generated by the ML algorithm. This creates minor problems for models that will be retrained and updated only occasionally, but major problems for models that will learn from data in real time or near real time. Regulators have announced action plans for fundamental changes in regulatory approaches. In this Viewpoint, we examine the current regulatory frameworks and developments in this domain. The status quo and recent developments are reviewed, and we argue that these innovative approaches to health care need matching innovative approaches to regulation and that these approaches will bring benefits for patients. International perspectives from the World Health Organization, and the Food and Drug Administration’s proposed approach, based around oversight of tool developers’ quality management systems and defined algorithm change protocols, offer a much-needed paradigm shift, and strive for a balanced approach to enabling rapid improvements in health care through AI innovation while simultaneously ensuring patient safety. The draft European Union (EU) regulatory framework indicates similar approaches, but no detail has yet been provided on how algorithm change protocols will be implemented in the EU. We argue that detail must be provided, and we describe how this could be done in a manner that would allow the full benefits of AI/ML-based innovation for EU patients and health care systems to be realized.
... T HE alignment of end-effector is required in robotic manipulation. In macroscale robotic manipulation, such as laundry folding [1] and tissue suturing [2], end-effector alignment is important for achieving desired contact between the end-effector and the manipulated object. End-effector alignment is also critical for micromanipulation with wide applications in microassembly [3], [4] and cell manipulation. ...
... Work on this topic extends from developing 2D and 3D computer vision techniques to detect and localize robotic tools (9) to learning from observation of surgical subtasks (10). It also includes semiautomated in vivo (11) suturing, although the technologies in these studies required simplified visual environments. The development of autonomy remains a very active research frontier. ...
Article
Robotics is a forward-looking discipline. Attention is focused on identifying the next grand challenges. In an applied field such as medical robotics, however, it is important to plan the future based on a clear understanding of what the research community has recently accomplished and where this work stands with respect to clinical needs and commercialization. This Review article identifies and analyzes the eight key research themes in medical robotics over the past decade. These thematic areas were identified using search criteria that identified the most highly cited papers of the decade. Our goal for this Review article is to provide an accessible way for readers to quickly appreciate some of the most exciting accomplishments in medical robotics over the past decade; for this reason, we have focused only on a small number of seminal papers in each thematic area. We hope that this article serves to foster an entrepreneurial spirit in researchers to reduce the widening gap between research and translation.
Article
Full-text available
Transthoracic esophagectomy is currently the predominant curative treatment option for resectable esophageal adenocarcinoma. The majority of carcinomas present as locally advanced tumors requiring multimodal strategies with either neoadjuvant chemoradiotherapy or perioperative chemotherapy alone. Minimally invasive, including robotic, techniques are increasingly applied with a broad spectrum of technical variations existing for the oncological resection as well as gastric reconstruction. At the present, intrathoracic esophagogastrostomy is the preferred technique of reconstruction (Ivor Lewis esophagectomy). With standardized surgical procedures, a complete resection of the primary tumor can be achieved in almost 95% of patients. Even in expert centers, postoperative morbidity remains high, with an overall complication rate of 50–60%, whereas 30- and 90-day mortality are reported to be <2% and <6%, respectively. Due to the complexity of transthoracic esophagetomy and its associated morbidity, esophageal surgery is recommended to be performed in specialized centers with an appropriate caseload yet to be defined. In order to reduce postoperative morbidity, the selection of patients, preoperative rehabilitation and postoperative fast-track concepts are feasible strategies of perioperative management. Future directives aim to further centralize esophageal services, to individualize surgical treatment for high-risk patients and to implement intraoperative imaging modalities modifying the oncological extent of resection and facilitating surgical reconstruction.
Article
Full-text available
As novas tecnologias na área da saúde têm impactado profundamente a doutrina do consentimento informado do paciente, tornando necessária a presente investigação pormenorizada, sobre os contornos e a dinâmica deste novo modelo do paciente consentir a quaisquer tratamentos ou intervenções médicas. A digitalização do setor da saúde foi um fator determinante para se tornar possível a implementação da inteligência artificial no suporte à decisão clínica e na eficiência dos diagnósticos médicos, sobretudo na detecção precoce de doenças, tendo em vista a sua capacidade de processar e analisar rapidamente – e, tendencialmente, de maneira eficiente – grande quantidade de dados. Nos últimos anos, há expressiva expansão da inteligência artificial aliada à robótica, criando uma realidade de robôs de assistência inteligentes para os cuidados médicos. O mercado global de robôs cirúrgicos, que realizam procedimentos de forma presencial ou à distância (telecirurgia), também tem crescido rapidamente nos últimos anos. Por fim, a revolução tecnológica no setor da saúde vem permitido que médicos diagnostiquem, tratem e até realizem cirurgias em pacientes à distância, nos locais mais remotos do mundo, por meio de Telemedicina. Diante de todo o panorama atual da medicina digitalizada e novas tecnologias na área da saúde – telemedicina, medicina robótica e inteligência artificial –, pudemos observar, ao longo do presente trabalho, que o consentimento informado do paciente adquire certas peculiaridades, tendo em vista os diversos fatores aleatórios e riscos inerentes às características únicas e próprias de cada tecnologia. Em linhas conclusivas, constatamos que a moderna dogmática do consentimento informado engloba a ideia de escolha esclarecida, visto que o paciente deve estar em posse de todas as informações e elementos possíveis a sua compreensão. Em outras palavras, mais do que um direito à informação, o paciente tem direito à explicação e justificação, a fim de consentir de maneira livre e esclarecida.
Conference Paper
Surgical resection is the current clinical standard of care for treating squamous cell carcinoma. Maintaining an adequate tumor resection margin is the key to a good surgical outcome, but tumor edge delineation errors are inevitable with manual surgery due to difficulty in visualization and hand-eye coordination. Surgical automation is a growing field of robotics to relieve surgeon burdens and to achieve a consistent and potentially better surgical outcome. This paper reports a novel robotic supervised autonomous electrosurgery technique for soft tissue resection achieving millimeter accuracy. The tumor resection procedure is decomposed to the subtask level for a more direct understanding and automation. A 4-DOF suction system is developed, and integrated with a 6-DOF electrocautery robot to perform resection experiments. A novel near-infrared fluorescent marker is manually dispensed on cadaver samples to define a pseudotumor, and intraoperatively tracked using a dual-camera system. The autonomous dual-robot resection cooperation workflow is proposed and evaluated in this study. The integrated system achieves autonomous localization of the pseudotumor by tracking the near-infrared marker, and performs supervised autonomous resection in cadaver porcine tongues (N =3). The three pseudotumors were successfully removed from porcine samples. The evaluated average surface and depth resection errors are 1.19 and 1.83mm, respectively. This work is an essential step towards autonomous tumor resections.
Article
Bioengineering has been revolutionizing the production of biofunctional tissues for tackling unmet clinical needs. Bioengineers have been focusing their research in biofabrication, especially 3D bioprinting, providing cutting-edge approaches and biomimetic solutions with more reliability and cost–effectiveness. However, these emerging technologies are still far from the clinical setting and deep learning, as a subset of artificial intelligence, can be widely explored to close this gap. Thus, deep-learning technology is capable to autonomously deal with massive datasets and produce valuable outputs. The application of deep learning in bioengineering and how the synergy of this technology with biofabrication can help (more efficiently) bring 3D bioprinting to clinics, are overviewed herein.
Chapter
Given the great progress made in the field of cryopreservation and ovarian tissue transplantation, ovarian tissue cryopreservation and transplantation are no longer considered experimental by the American Society of Reproductive Medicine. However, these procedures still have numerous limitations. This chapter will examine the areas that need improvement while predicting future breakthroughs in the field of ovarian cryopreservation and autotransplantation. These include advances in vitrification techniques, robotic surgery, vascularization enhancing treatments, and whole ovarian tissue cryopreservation and transplantation. The current research on in vitro growth of the primordial follicles and de novo oocyte generation ovarian, embryonic, and induced pluripotent stem cells will also be evaluated.
Chapter
The revolution of minimally invasive procedures had a significant influence on surgical practice, opening the way to laparoscopic surgery, then evolving into robotics surgery. Teleoperated master-slave robots, such as the da Vinci Surgical System, has become a standard of care during the last few decades, performing over a million procedures per year worldwide. Many believe that the next big step in the evolution of surgery is partial automation, which would ease the cognitive load on the surgeon, making them possible to pay more attention on the critical parts of the intervention. Partial and sequential introduction and increase of autonomous capabilities could provide a safe way towards Surgery 4.0. Unfortunately, autonomy in the given environment, consisting mostly of soft organs, suffers from grave difficulties. In this chapter, the current research directions of subtask automation in surgery are to be presented, introducing the recent advances in motion planning, perception, and human-machine interaction, along with the limitations of the task-level autonomy.
Chapter
Despite significant advancements in diagnosis and disease management, cardiovascular (CV) disorders remain the No. 1 killer both in the United States and across the world, and innovative and transformative technologies such as artificial intelligence (AI) are increasingly employed in CV medicine. In this chapter, the authors introduce different AI and machine learning (ML) tools including support vector machine (SVM), gradient boosting machine (GBM), and deep learning models (DL), and their applicability to advance CV diagnosis and disease classification, and risk prediction and patient management. The applications include, but are not limited to, electrocardiogram, imaging, genomics, and drug research in different CV pathologies such as myocardial infarction (heart attack), heart failure, congenital heart disease, arrhythmias, valvular abnormalities, etc.
Chapter
Artificial Intelligence (AI) reshapes the global scenario and redefines development and service demand. AI stands as a disruptive technology that leads to numerous, more efficient activities, industrial processes, and new business models. The literature underlines that AI can be used in all aspects of organizations and individuals’ personal lives, and such nuances and potentials are still mostly unstudied, representing an interesting research gap. This chapter aims to emphasize the technologies and applications of AI to industries and services. Focusing then on the Portuguese context, this research’s main objective is to concentrate on AI to recognize state of the art and the main developments and trends in the industry and services and provide insights into AI policies.
Article
In this article, a shared-control system with skill-based share weight allocation is proposed for a robot-assisted minimally invasive surgery (MIS) procedure. A convolution neural network (CNN) is trained for online skill assessment, and the result is used to generate the share weights of robot autonomy and the user remote control. The control system can ensure synchronization of the two commands from the surgeon and robot autonomy and combine them to determine the motion of the surgical instrument. In this work, a contour-tracking task is handled by the suggested shared controller to simulate a surgical cutting operation. Experimental results on a lab-built robotic platform are presented to show the effectiveness of the proposed method. Multiple contour-tracking experiments have been tested to compare the tracking performances of pure manual remote control and the proposed shared-control method. Experimental results show that the shared controller achieved 34.5% improvement in tracking accuracy in comparison with pure manual control.
Chapter
Endorobots can empower the user’s perception by accessing the human body through natural orifices or small incisions. Improvements in new available technologies, in designing miniaturized sensors and actuators, in new smart materials, and in powerful computational units to implement complex real-time control strategies have paved the way to new design paradigms. This chapter discusses current challenges and future trends in endorobotics that will provide new solutions for the design of the next generation of endorobots. The chapter will discuss in the first section the evolution of medical devices; then, it presents the size requirement to access human organs, and in the last section, challenges ahead in designing the next generation of endorobots are presented.
Article
Full-text available
Today, the medical society is living in the era of artificial intelligence, which is developed and becomes more famous thanks to the coronavirus disease of 2019 (COVID-19) pandemic, which has given the space for artificial intelligence to appear more influential in analyzing medical data and providing very accurate results. This science has deservedly been able to achieve an excellent and vital position among healthcare workers, and it has become a necessary element of their work because of its a great potential for practical decision-making. The prospects of using intelligent systems in the medical field are deemed essential in the health division due to their ability to analyze big data and give exact results, aiming to improve the health of citizens and save their lives. In this article, a set of important information about the vital role of artificial intelligence in the medical field is highlighted. In addition, how this science does manage to confront SARS-CoV-2 by highlighting a set of investigations and analyses in predicting the spread of the virus, tracking infections, and diagnosis of cases through chest x-ray images of COVID-19 patients. The database of this article covered more than 40 studies between 2020 and 2021 and investigated the effects of utilizing artificial intelligence techniques in analyzing SARS-CoV-2 data. These studies are gathered from PubMed, NCBI, google scholar, Medrxiv and other sites. This article includes a plethora of information about artificial intelligence and SARS-CoV-2. The findings confirm that artificial intelligence has a significant role in the healthcare domain, and it is advised to utilize its applications in the decision-making method.
Article
Zusammenfassung Die roboterassistierte Chirurgie hat sich in den letzten Jahren deutlich weiterentwickelt und wurde in immer mehr Teilbereichen der Chirurgie als fester Bestandteil des operativen Spektrums implementiert. Dieser Beitrag legt den aktuellen Stand der roboterassistierten Chirurgie in Bereichen der Allgemein-, Viszeral- und Thoraxchirurgie unter Berücksichtigung der aktuellen Literatur dar.
Article
Video recording is widely available in modern operating rooms. Here, I argue that, if patient consent and suitable technology are in place, video recording of surgery is an ethical duty. I develop this as a duty to protect, arguing for professional and institutional duties, as distinguished for duties of rescue . A professional duty to protect is described in mental healthcare. Practitioners have to take reasonable steps to prevent serious, foreseeable harm to their clients and others, even if that entails a non-consensual breach of confidentiality. I argue surgeons have a similar duty to patients which means that, provided the patient consents, surgery should be routinely videoed. This avoids non-consensual breaches of patient confidentiality and is aligned with stated professional obligations. An institutional duty to protect means institutions have to take reasonable steps to prevent serious, foreseeable harm at the hands of their surgeons. Rulli and Millum highlighted how institutions can meet their duty using a more consequentialist approach that balances wider interests. To test the force and scope of such duties, I examine potential impacts of routine videoing on aspects of autonomy, justice, beneficence and non-maleficence. I find routine videoing can benefit areas including safety, candour, consent and fairness in access (to surgical careers and expertise). Countervailing claims, for example, on liability, confidentiality and privacy can be resisted—such that where consent and the technology are in place, routine videoing meets a duty of easy protection . In other words, its use should be standard of care.
Article
Topic Despite significant recent advances in artificial intelligence (AI) technology within several ophthalmic subspecialties, AI is underutilised in the diagnosis and management of cataract. In this article, we review AI technology that has been reported within research settings that may soon become central to the cataract surgical pathway, from diagnosis to completion of surgery. Clinical relevance This review describes recent advances of AI in the preoperative, intraoperative and postoperative phase of cataract surgery demonstrating its impact on the pathway and the surgical team. Methods A systematic search on PubMed has been conducted in order to identify relevant publications on the topic of Artificial Intelligence for cataract surgery. Articles of high quality and relevance to the topic have been selected. Results Preoperatively, diagnosis and grading of cataracts through AI based image analysis has been demonstrated in several research settings. Optimal IOL power to achieve the desired postoperative refraction can be calculated with a higher degree of accuracy using AI based modelling compared to traditional IOL formulae. Intraoperatively, innovative AI based video analysis tools are in development promoting a paradigm shift for documentation, storage and cataloguing libraries of surgical videos with applications for teaching and training, complication review and surgical research. Situation-aware computer-assisted devices can be connected to surgical microscopes for automated video capture and cloud storage upload. AI based software can provide workflow analysis, tool detection and video segmentation for skill evaluation by the surgeon and the trainee. Mixed reality features such as real-time intraoperative warnings may have a role in improving surgical decision making with the key aim of reducing complications by recognising surgical risks in advance and alerting the operator to them. For the management of patient flow through the pathway, AI-based mathematical models generating patient referral patterns are in development as are simulations to optimise operating room utilisation. In the postoperative phase, AI has been shown to predict the posterior capsule status with reasonable accuracy and therefore improve the triage pathway in the treatment of posterior capsular opacification. Conclusion AI for cataract surgery will be as relevant as in other subspecialties of ophthalmology and eventually constitute a future cornerstone for an enhanced cataract surgery pathway.
Article
This Technical Note presents an endoscopic robotic anterior axillary shoulder approach using of the DaVinci (Intuitive Surgical, Sunnyvale, CA) robot, which allows one to endoscopically access and harvest the latissimus dorsi tendon for occasions in which the patient presents an irreparable lesion of the subscapularis tendon. Harvesting the latissimus dorsi through an anterior axillary approach is specially desirable when one needs to access the anterior portion of the shoulder, as happens for subscapularis irreparable lesions.
Article
Full-text available
Intestinal anastomosis is a surgical procedure that restores bowel continuity after surgical resection to treat intestinal malignancy, inflammation, or obstruction. Despite the routine nature of intestinal anastomosis procedures, the rate of complications is high. Standard visual inspection cannot distinguish the tissue subsurface and small changes in spectral characteristics of the tissue, so existing tissue anastomosis techniques that rely on human vision to guide suturing could lead to problems such as bleeding and leakage from suturing sites. We present a proof-of-concept study using a portable multispectral imaging (MSI) platform for tissue characterization and preoperative surgical planning in intestinal anastomosis. The platform is composed of a fiber ring light-guided MSI system coupled with polarizers and image analysis software. The system is tested on ex vivo porcine intestine tissue, and we demonstrate the feasibility of identifying optimal regions for suture placement. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
Article
Full-text available
For many patients, rectal catheters are an effective means to manage bowel incontinence. Unfortunately, the incidence of catheter leakage in these patients remains troublingly high. Matching the mechanical properties of the catheter and the surrounding tissue may improve the catheter seal and reduce leakage. However, little data is available on the mechanical properties of colorectal tissue. Therefore, our group examined the mechanical properties of colorectal tissue obtained from both a common animal model and humans. Uniaxial tension tests were performed to determine the effects of location, orientation, and species (porcine and human) on bowel tissue tensile mechanical properties. Bowel tissue ultimate strength, elongation at failure, and elastic modulus were derived from these tests and statistically analyzed. Ultimate tensile strength (0.58 MPa, 0.87 MPa), elongation at failure (113.19%, 62.81%), and elastic modulus (1.83 MPa, 5.18 MPa) for porcine and human samples respectively exhibited significant differences based on species. Generally, human tissues were stronger and less compliant than their porcine counterparts. Furthermore, harvest site location and testing orientation significantly affected several mechanical properties in porcine derived tissues, but very few in human tissues. The data suggests that porcine colorectal tissue does not accurately model human colorectal tissue mechanical properties. Ultimately, the tensile properties reported herein may be used to help guide the design of next generation rectal catheters with tissue mimetic properties, as well as aid in the development of physical and computer based bowel models.
Article
Full-text available
Head and neck surgery can be fraught with difficulties in accessing the pharynx and larynx. Minimally invasive surgery has developed with the recent advances in technology. Currently, we have a variety of high-definition multichannel videoendoscopes and robots in our armamentarium. We present our experience in a new robotic surgical system-'The Medrobotics Flex™ System' at our tertiary referral unit. We aimed to assess the safety, functionality and ease of use of this new device in this prospective study. Thus far, this is the first study in live human subjects who have undergone surgery for the following conditions: (1) obstructive sleep apnoea involving the base of tongue, the tonsil and the velum; (2) vocal fold polyp; (3) carcinoma of the lateral edge of the tongue. There were no complications in our series and the system provided good visualisation and access to these subsites without compromising safety or success. In summary, we found the Medrobotics Flex™ System to have certain other advantages including ease of set up and use besides being reliable and safe.
Article
Full-text available
Background Intraoperative imaging disrupts the rhythm of surgery despite providing excellent opportunity for surgical monitoring and assessment. In order to allow surgery within real time images, neuroArm, a teleoperated surgical robotic system, was conceptualized. Objectives The objective was to design and manufacture a MR-compatible robot with a human machine interface that could reproduce some of the sight, sound, and touch of surgery at a remote workstation. Methods University of Calgary researchers worked with MacDonald Dettwiler and Associates engineers to produce a requirements document, preliminary design review, critical design review, followed by the manufacture, preclinical testing and clinical integration of neuroArm. Results During the preliminary design review, the scope of the neuroArm project changed to preforming microsurgery outside of the magnet and stereotaxy inside the bore. neuroArm was successfully manufactured and installed into an iMRI operating room. neuroArm was clinically integrated into 35 cases in a graded fashion. Based on this experience, neuroArm II is in development, and advances in technology will allow microsurgery within the bore of the magnet. Conclusion neuroArm represents a successful interdisciplinary collaboration. It has positive implications for the future of robotic technology in neurosurgery, as the precision and accuracy of robots will continue to augment human capability.
Article
Full-text available
Mechanical stapler is regarded as a good alternative to the hand sewing technique, when used in gastric reconstruction. The circular stapling method has been widely applied to gastrectomy (open orlaparoscopic), for gastric cancer. We illustrated and compared the hand-sutured method to the circular stapling method, for Billroth-II, in patients who underwent laparoscopy assisted distal gastrectomy for gastric cancer. Between April 2009 and May 2011, 60 patients who underwent laparoscopy assisted distal gastrectomy, with Billroth-II, were enrolled. Hand-sutured Billroth-II was performed in 40 patients (manual group) and circular stapler Billroth-II was performed in 20 patients (stapler group). Clinicopathological features and post-operative outcomes were evaluated and compared between the two groups. Nosignificant differences were observed in clinicopathologic parameters and post-operative outcomes, except in the operation times. Operation times and anastomosis times were significantly shorter in the stapler group (P=0.004 and P<0.001). Compared to the hand-sutured method, the circular stapling method can be applied safely and more efficiently, when performing Billroth-II anastomosis, after laparoscopy assisted distal gastrectomy in patients with gastric cancer.
Article
Full-text available
Autonomous control of surgical robotic platforms may offer enhancements such as higher precision, intelligent manoeuvres, tissue-damage avoidance, etc. Autonomous robotic systems in surgery are largely at the experimental level. However, they have also reached clinical application. A literature review pertaining to commercial medical systems which incorporate autonomous and semi-autonomous features, as well as experimental work involving automation of various surgical procedures, is presented. Results are drawn from major databases, excluding papers not experimentally implemented on real robots. Our search yielded several experimental and clinical applications, describing progress in autonomous surgical manoeuvres, ultrasound guidance, optical coherence tomography guidance, cochlear implantation, motion compensation, orthopaedic, neurological and radiosurgery robots. Autonomous and semi-autonomous systems are beginning to emerge in various interventions, automating important steps of the operation. These systems are expected to become standard modality and revolutionize the face of surgery.
Article
Full-text available
Unicompartmental knee arthroplasty (UKA) is a popular treatment for unicompartmental knee arthritis. Indications for UKA include mechanical axis of less than 10 degrees varus and less than 5 degrees valgus, intact anterior cruciate ligament (ACL), and absence of femorotibial subluxation. Appropriately selected patients can expect UKA to last at least 10 years. UKA failures are not common and involve technical errors that are thought to be corrected with use of newly developed robotic technology. The surgeon using this technology may be able to arrive at a set target, enhance surgical precision, and avoid outliers. Whether improved precision will result in improved long-term clinical outcome remains a subject of research. In this article, we describe the perioperative management of patients who undergo UKA whether with conventional techniques or robotic arm assistance. We also describe the distinct aspects of preoperative, intraoperative, and postoperative pain management and of intraoperative anesthesia and blood management.
Conference Paper
Full-text available
Despite many successes with teleoperated robotic surgical systems, some surgeons feel that the lack of haptic (force or tactile) feedback is detrimental in applications requiring fine suture manipulation. In this paper, we study the difference between applied suture forces in three knot tying exercises: hand ties, instrument ties (using needle drivers), and robot ties (using the da Vinci TM Surgical System from Intuitive Surgical, Inc.). Both instrument and robot-assisted ties differ from hand ties in accuracy of applied force. However, only the robot ties differ from hand ties in repeatability of applied force. Furthermore, comparison between artendings and residents revealed statistically significant differences in the forces used during hand ties, although artendings and residents perform similarly when comparing instrument and robot ties to hand ties. These results indicate that resolved force feedback would improve robot-assisted performance during complex surgical tasks such as knot tying with fine suture.
Chapter
Surgical robots are commonly utilized in multiple surgical specialties but have only relatively recently been used routinely in Otolaryngology—Head and Neck Surgery. The high levels of instrument maneuverability, magnification, and excellent visualization make modern surgical robots ideal for certain confined spaces of the head and neck including the oropharynx, hypopharynx, and larynx. This chapter outlines the basic principles of robotic surgery and technology and provides a brief history of the technological developments that led to the robotic devices currently in use. In addition, the use of robotics in specific head and neck subsites is reviewed including the oropharynx, larynx, thyroid, and skull base.
Book
This is a reference text for both the novice and the accomplished ophthalmic surgeon. In 15 richly illustrated chapters the book imparts basic information on tissue tactics and knot tying and demonstrates the applicability of these techniques to various microsurgical situations, in both the anterior and the posterior segment of the eye. The chapters have a uniform reader-friendly format starting with 'key points' to allow rapid reference to the information included in the chapter. Illustrated with photos and line drawings, each chapter contains sections on: Surgical indications, Instrumentation and equipment, Surgical technique, Complications and future challenges. Those who will benefit greatly from this excellent book include ophthalmic surgeons with widely varying levels of experience, from the resident to the experienced surgeon.
Conference Paper
This paper specifies and evaluates the accuracy of the Smart Tissue Anastomosis Robot (STAR). The STAR is a proof of concept vision-guided robotic system equipped with an actuated laparoscopic suturing tool and a multispectral vision system. The STAR supports image-based suturing commands and is capable of detecting near-infrared fluorescent (NIRF) markers that provide reliable visual segmentation and tracking. The paper reports the best case scenario accuracy specifications of the STAR as derived from its configuration and calibration parameters. We also evaluate experimentally the effects of overlaying NIRF markers on the accuracy of the STAR when these markers are used as the source of image-based commands and we compare these results to the accuracy of the STAR with image-based commands generated from plain color images. Our results demonstrate that the STAR is able to place sutures on a planar phantom with an average accuracy of 0.5 mm with a standard deviation of 0.2 mm and that NIRF markers have no statistically significant adverse effect on the accuracy.
Article
Purpose: To review past attempts, current innovations, and future goals of robotic eye surgery. Methods: A Medline literature search using the words “robot” and “ophthalmology” was performed to identify all relevant literature. Pertinent articles were reviewed and content summarized based on context. Results: Purported potential benefits of robotic-assisted eye surgery include improved precision, reduced tremor, amplified scale of motion, and the potential of automation and telesurgical operation. Several investigators have created devices capable of performing individual intraocular tasks, and efforts are underway to develop platforms designed to allow completion of entire ophthalmic procedures. Conclusion: Although obstacles such as cost and availability exist, prior successes and future benefits of robotic eye surgery are promising reasons for the continuation of research efforts.
Article
The observation and 3D quantification of arbitrary scenes using optical imaging systems is challenging, but increasingly necessary in many fields. This paper provides a technical basis for the application of plenoptic cameras in medical and medical robotics applications, and rigorously evaluates camera integration and performance in the clinical setting. It discusses plenoptic camera calibration and setup, assesses plenoptic imaging in a clinically relevant context, and in the context of other quantitative imaging technologies. We report the methods used for camera calibration, precision and accuracy results in an ideal and simulated surgical setting. Afterwards, we report performance during a surgical task. Test results showed the average precision of the plenoptic camera to be 0.90mm, increasing to 1.37mm for tissue across the calibrated FOV. The ideal accuracy was 1.14mm. The camera showed submillimeter error during a simulated surgical task.
Article
Automating repetitive surgical subtasks such as suturing, cutting and debridement can reduce surgeon fatigue and procedure times and facilitate supervised tele-surgery. Programming is difficult because human tissue is deformable and highly specular. Using the da Vinci Research Kit (DVRK) robotic surgical assistant, we explore a 'Learning By Observation' (LBO) approach where we identify, segment, and parameterize motion sequences and sensor conditions to build a finite state machine (FSM) for each subtask. The robot then executes the FSM repeatedly to tune parameters and if necessary update the FSM structure. We evaluate the approach on two surgical subtasks: debridement of 3D Viscoelastic Tissue Phantoms (3d-DVTP), in which small target fragments are removed from a 3D viscoelastic tissue phantom; and Pattern Cutting of 2D Orthotropic Tissue Phantoms (2d-PCOTP), a step in the standard Fundamentals of Laparoscopic Surgery training suite, in which a specified circular area must be cut from a sheet of orthotropic tissue phantom. We describe the approach and physical experiments with repeatability of 96% for 50 trials of the 3d-DVTP subtask and 70% for 20 trials of the 2d-PCOTP subtask. A video is available at: http://j.mp/Robot-Surgery-Video-Oct-2014.
Article
Medical robots have been widely used to assist surgeons to carry out dexterous surgical tasks via various ways. Most of the tasks require surgeon's operation directly or indirectly. Certain level of autonomy in robotic surgery could not only free the surgeon from some tedious repetitive tasks, but also utilize the advantages of robot: high dexterity and accuracy. This paper presents a semi-autonomous neurosurgical procedure of brain tumor ablation using RAVEN Surgical Robot and stereo visual feedback. By integrating with the behavior tree framework, the whole surgical task is modeled flexibly and intelligently as nodes and leaves of a behavior tree. This paper provides three contributions mainly: (1) describing the brain tumor ablation as an ideal candidate for autonomous robotic surgery, (2) modeling and implementing the semi-autonomous surgical task using behavior tree framework, and (3) designing an experimental simulated ablation task for feasibility study and robot performance analysis.
Article
Hypothesis Although perceived as a more technically demanding and time-consuming technique, the hand-sewn gastrojejunostomy during laparoscopic Roux-en-Y gastric bypass (RYGB) is associated with fewer complications and lower costs than stapled techniques. Design A retrospective medical record review of prospectively collected data. Setting University hospital. Patients One hundred eight consecutive patients undergoing laparoscopic RYGB between January 1, 1999, and December 31, 2001. Intervention Three techniques were compared: hand-sewn anastomosis (HSA), circular-stapled anastomosis (CSA), and linear-stapled anastomosis (LSA). Main Outcome Measures Operative costs, including the cost of stapling devices, the cost of sutures, and operative times, were compared. Rates of anastomotic strictures, leaks, marginal ulcers, bleeding, and wound infections were determined. Results Eighty-seven patients underwent HSA; 13, CSA; and 8, LSA. Supply costs per patient were higher for CSA ($955) and LSA ($435) than for HSA ($2) (P<.001). The mean ± SEM operative time for laparoscopic RYGB was longer when performing CSA than HSA or LSA (285 ± 22 vs 215 ± 8 and 204 ± 28 minutes, respectively; P<.001). Stricture rates were higher after CSA than HSA and LSA (4 [31%] of 13 patients vs 3 [3%] of 87 patients and 0 of 8 patients, respectively; P<.01). The wound infection rate was higher after CSA than HSA and LSA (3 [23%] of 13 patients vs 1 [1%] of 87 patients and 0 of 8 patients, respectively; P<.001). There was no difference in anastomotic bleeding, and no anastomotic leaks occurred. Conclusions In this experience, hand-sewn gastrojejunostomy during laparoscopic RYGB reduced operating room supply costs and was completed faster than stapled techniques. However, these differences may reflect the learning curve because these techniques were used early in our experience. Lower postoperative stricture and wound infection rates seem to be the primary benefits of the HSA technique.
Article
Automating surgery using robots requires robust visual tracking. The surgical environment often has poor light conditions where several organs have similar visual appearances. In addition, the field of view might be occluded by blood or tissue. In this paper, the feasibility of near-infrared (NIR) fluorescent marking and imaging for vision-based robot control is studied. The NIR region of the spectrum has several useful properties including deep tissue penetration. We study the optical properties of a clinically-approved NIR fluorescent dye, indocyanine green (ICG), with different concentrations and quantify image positioning error of ICG marker when obstructed by tissue.
Article
This paper introduces the smart tissue anastomosis robot (STAR). Currently, the STAR is a proof-of-concept for a vision-guided robotic system featuring an actuated laparoscopic suturing tool capable of executing running sutures from image-based commands. The STAR tool is designed around a commercially available laparoscopic suturing tool that is attached to a custom-made motor stage and the STAR supervisory control architecture that enables a surgeon to select and track incisions and the placement of stitches. The STAR supervisory-control interface provides two modes: A manual mode that enables a surgeon to specify the placement of each stitch and an automatic mode that automatically computes equally-spaced stitches based on an incision contour. Our experiments on planar phantoms demonstrate that the STAR in either mode is more accurate, up to four times more consistent and five times faster than surgeons using state-of-the-art robotic surgical system, four times faster than surgeons using manual Endo360 $^circ$$^textregistered$ , and nine times faster than surgeons using manual laparoscopic tools.
Article
Vesicourethral reconstruction is the most critical and time-consuming step of laparoscopic radical prostatectomy, We describe the use of two hemicircumferential running sutures that has significantly simplified the procedure in our last 30 patients. The vesicourethral reconstruction took 31 minutes on average. Six months postoperatively, 84% of the patients were fully continent, and no bladder neck stenosis had occurred, The economy of intracorporeal suturing provided by this novel method, together with geometric factors such as the optimal position of the trocars, contributes to the improvement of ergonomy, allowing the surgeon to decrease operating times.
Article
: The first United States 201 cobalt-60 source gamma knife for stereotactic radiosurgery of brain tumors and arteriovenous malformations became operational at the University of Pittsburgh on August 14, 1987. Four and one-half years of intensive planning, regulatory agency review, and analysis of published results preceded the first radiosurgical procedure. Installation of this 18,000-kg device and loading of the 201 cobalt-60 sources posed major challenges in engineering, architecture, and radiophysics. In the first 4 months of operation, we treated 52 patients (29 with arteriovenous malformations, 19 with extra-axial neoplasms of the skull base, and 4 with intra-axial malignant tumors). Most patients either had lesions considered "inoperable" or had residual lesions after attempted surgical resection. Neither surgical mortality nor significant morbidity was associated with gamma knife radiosurgery. As compared with treatment by conventional intracranial surgery (craniotomy), the average length of stay for radiosurgery was reduced by 4 to 14 days, and hospital charges were reduced by as much as 65%. Based on both the previously published results of treatment of more than 2,000 patients worldwide and on our initial clinical experience, we believe that gamma knife stereotactic radiosurgery is a therapeutically effective and economically sound alternative to more conventional neurosurgical procedures, in selected cases. (Neurosurgery 24:151-159, 1989) Copyright (C) by the Congress of Neurological Surgeons
Article
Background: Surgeons have rapidly adopted minimally invasive surgical (MIS) techniques for a wide range of applications since the first laparoscopic appendectomy was performed in 1983. At the helm of this MIS shift has been laparoscopy, with robotic surgery also gaining ground in a number of areas. Methods: Researchers estimated national volumes, growth forecasts, and MIS adoption rates for the following procedures: cholecystectomy, appendectomy, gastric bypass, ventral hernia repair, colectomy, prostatectomy, tubal ligation, hysterectomy, and myomectomy. MIS adoption rates are based on secondary research, interviews with clinicians and administrators involved in MIS, and a review of clinical literature, where available. Overall volume estimates and growth forecasts are sourced from The Advisory Board Company's national demand model which provides current and future utilization rate projections for inpatient and outpatient services. The model takes into account demographics (growth and aging of the population) as well as non demographic factors such as inpatient to outpatient shift, increase in disease prevalence, technological advancements, coverage expansion, and changing payment models. Results: Surgeons perform cholecystectomy, a relatively simple procedure, laparoscopically in 96 % of the cases. Use of the robot as a tool in laparoscopy is gaining traction in general surgery and seeing particular growth within colorectal surgery. Surgeons use robotic surgery in 15 % of colectomy cases, far behind that of prostatectomy but similar to that of hysterectomy, which have robotic adoption rates of 90 and 20 %, respectively. Conclusions: Surgeons are using minimally invasive surgical techniques, primarily laparoscopy and robotic surgery, to perform procedures that were previously done as open surgery. As risk-based pressures mount, hospital executives will increasingly scrutinize the cost of new technology and the impact it has on patient outcomes. These changing market dynamics may thwart the expansion of new surgical techniques and heighten emphasis on competency standards.
Article
Robotic surgical assistants offer the possibility of automating portions of a task that are time consuming and tedious in order to reduce the cognitive workload of a surgeon. This paper proposes using programming by demonstration to build generative models and generate smooth trajectories that capture the underlying structure of the motion data recorded from expert demonstrations. Specifically, motion data from Intuitive Surgical's da Vinci Surgical System of a panel of expert surgeons performing three surgical tasks are recorded. The trials are decomposed into subtasks or surgemes, which are then temporally aligned through dynamic time warping. Next, a Gaussian Mixture Model (GMM) encodes the experts' underlying motion structure. Gaussian Mixture Regression (GMR) is then used to extract a smooth reference trajectory to reproduce a trajectory of the task. The approach is evaluated through an automated skill assessment measurement. Results suggest that this paper presents a means to (i) extract important features of the task, (ii) create a metric to evaluate robot imitative performance (iii) generate smoother trajectories for reproduction of three common medical tasks.
Article
Patients with inflammatory and ischaemic bowel diseases seem to tolerate narrowing of the gut lumen to a critical degree of stenosis without obstructive symptoms. To determine the physical factors involved in bowel occlusion, we created an experimental model using New Zealand rabbits in acute experiments under general anaesthesia. At operation a loop of small bowel was isolated and canulated, proximally for perfusion and pressure recording and distally to monitor flow. Having established the physiological pressure and flow conditions in a normal loop of gut, a stenosis was created using circular adjustable rings of determined widths. Pressure and flow were measured constantly and the variables studied were luminal diameter, stenosis length, and perfusate viscosity. This experimental model was reproduced using resected segments of human small bowel. We found a critical point- at 60% of the original diameter-down to which the small bowel is able to maintain normal flow. At a diameter smaller than this, the physiological parameters are rapidly altered up to the point of complete obstruction. In the rabbit model bowel rupture occurs at 30% of the initial size. Increased viscosity of the fluid and length of the stenosis alter this critical point inducing a larger critical diameter. We did not observe any cumulative effect of multiple identical stenoses.
Article
The first United States 201 cobalt-60 source gamma knife for stereotactic radiosurgery of brain tumors and arteriovenous malformations became operational at the University of Pittsburgh on August 14, 1987. Four and one-half years of intensive planning, regulatory agency review, and analysis of published results preceded the first radiosurgical procedure. Installation of this 18,000-kg device and loading of the 201 cobalt-60 sources posed major challenges in engineering, architecture, and radiophysics. In the first 4 months of operation, we treated 52 patients (29 with arteriovenous malformations, 19 with extra-axial neoplasms of the skull base, and 4 with intra-axial malignant tumors). Most patients either had lesions considered "inoperable" or had residual lesions after attempted surgical resection. Neither surgical mortality nor significant morbidity was associated with gamma knife radiosurgery. As compared with treatment by conventional intracranial surgery (craniotomy), the average length of stay for radiosurgery was reduced by 4 to 14 days, and hospital charges were reduced by as much as 65%. Based on both the previously published results of treatment of more than 2,000 patients worldwide and on our initial clinical experience, we believe that gamma knife stereotactic radiosurgery is a therapeutically effective and economically sound alternative to more conventional neurosurgical procedures, in selected cases.
Article
An ultrasonic technique and microtensile testing were used to determine the Young's modulus of individual trabeculae and micro-specimens of cortical bone cut to similar size as individual trabeculae. The average trabecular Young's modulus measured ultrasonically and mechanically was 14.8 GPa (S.D. 1.4) and 10.4 (S.D. 3.5) and the average Young's modulus of microspecimens of cortical bone measured ultrasonically and mechanically was 20.7 GPa (S.D. 1.9) and 18.6 GPa (S.D. 3.5). With either testing technique the mean trabecular Young's modulus was found to be significantly less than that of cortical bone (p < 0.0001). However, the specimens were dried before microtensile testing so Young's modulus values may have been greater than those of trabeculae in vivo. Using Young's modulus measurements obtained from 450 cubes of cancellous bone and 256 cubes of cortical bone, Wolff's hypothesis that cortical bone is simply dense cancellous bone was tested. A multiple regression analysis that controlled for group membership showed that Young's modulus of cortical bone cannot be extrapolated from the Young's modulus vs density relationship for cancellous bone, yet the Young's modulus of trabeculae can be predicted by extrapolation from the relationship between Young's modulus vs density of the cancellous bone. These results suggest that when considered mechanically, cortical and trabecular bone are not the same material.
Article
The Cyberknife is a unique instrument for performing frameless stereotactic radiosurgery. Rather than using rigid immobilization, the Cyberknife relies on an image-to-image correlation algorithm for target localization. Furthermore, the system utilizes a novel, light-weight, high-energy radiation source. The authors describe the technical specifications of the Cyberknife and summarize the initial clinical experience.
Article
The goal of this animal experiment was to demonstrate the feasibility of laparoscopic end-to-side aortic anastomosis, which is mandatory in certain cases presenting with aortoiliac occlusive disease. Six piglets were submitted to laparoscopic approach of the aortoiliac vessels using the "apron" technique. After clamping the infrarenal aorta with a laparoscopic Satinsky clamp, a 3-cm end-to-side laparoscopic aortic anastomosis was constructed. Mean operative and dissection times were 198 (170-240) and 92 (75-105) min, respectively, with a mean blood loss of 86 (50-120) mL. Mean preoperative and postoperative hematocrits were 38 (3448) and 38 (34-46). Aortic cross-clamp and anastomotic times were 51 (40-65) and 44 (35-60) min, respectively. No extra sutures were needed to secure the anastomoses. At autopsy, all the anastomoses were patent without stenoses. Results indicate the feasibility of laparoscopic aortobifemoral bypass with an end-to-side aortic anastomosis.
Article
Previous descriptions of a laparoscopic Roux-en-Y gastric bypass, using a circular stapler to perform the gastrojejunal anastomosis, have employed the esophagus as a conduit to introduce the anvil of the stapling device into the stomach. The authors believe that the risk of injury to the esophagus, as well as the difficulty in maneuvering the anvil from the pharynx to the proximal part of the stomach, make this technique less than optimal. In other descriptions (in a porcine model) the anvil has been guided into position through a distal gastrotomy by attaching it to a Prolene suture on a straight needle and directing the needle toward a chosen site. Although the authors prefer this method because it avoids potential esophageal injury, they sought a technique that would be even more precise in anvil placement and would avoid pushing a needle across gastric mucosa. The authors have developed a method that is totally intra-abdominal and does not risk injury to the esophagus. The circular stapler is still used, thus giving a consistent, small opening through the gastrojejunal anastomosis. Over a 1-year period, 49 (of 50) patients underwent laparoscopic Roux-en-Y gastric bypass with the described method. The average body mass index dropped from 42.63 to 34.12 over the first postoperative 3 months, with an average loss in excess body weight of 38.5%. The length of hospitalization following the procedure averaged 3.8 days, and the time to return to work (where applicable) was 11.9 days. This totally intra-abdominal laparoscopic technique is feasible and advantageous.
Article
Laparoscopic Roux-en-Y gastric bypass was recently introduced as an alternative surgical treatment for morbid obesity. The technique involves placement of a 21-mm anvil transorally down to the gastric pouch for creation of the gastroenterostomy anastomosis using an EEA stapler placed transabdominally. Esophageal injury is a theoretical concern with transoral manipulation of the anvil. The authors present a case of hypopharyngeal perforation after an attempted transoral insertion of an EEA anvil. The perforation was treated with neck exploration and drainage. We discuss the mechanism of injury and alternative method for placement of the gastric anvil.
Article
Vesicourethral reconstruction is the most critical and time-consuming step of laparoscopic radical prostatectomy. We describe the use of two hemicircumferential running sutures that has significantly simplified the procedure in our last 30 patients. The vesicourethral reconstruction took 31 minutes on average. Six months postoperatively, 84% of the patients were fully continent, and no bladder neck stenosis had occurred. The economy of intracorporeal suturing provided by this novel method, together with geometric factors such as the optimal position of the trocars, contributes to the improvement of ergonomy, allowing the surgeon to decrease operating times.
Article
Limitations of minimally invasive pediatric surgery include the inability to perform precise anastomoses of 2 to 15 mm. Robotic technology facilitates the performance of endoscopic microsurgical procedures. This study examined the technical feasibility of performing an enteroenterostomy in piglets utilizing ZEUS robotic technology. Ten piglets (6.5 to 8.5 kg) underwent enteroenterostomy. Standard laparoscopic techniques were used in the control group (n = 5), and ZEUS robotic technology was used in the experimental group (n = 5). AESOP controlled the camera in both groups. Anesthesia time; surgery time; robotic set-up time; and anastomotic time, patency, diameter, and integrity were compared. No statistical difference existed between the means of the control and experimental groups for anesthesia time (176.0 v 154.0 minute; P =.63), surgery time (143.0 v 139.2 minute; P =.92), anastomosis time (109.4 v 93.0 minutes; P =.56), AESOP set-up time (4.2 v 7.0 minutes; P =.51), and anastomotic diameter (7.062 v 7.362 mm; P =.62). All anastomoses were patent without narrowing. The ZEUS cases averaged 14 minutes faster than the standard laparoscopic cases, even with the ZEUS set-up time included. These data supports the hypothesis that robotic-assisted enteroenterostomy is technically feasible. ZEUS robotic technology will potentially play an important role in expanding the applications of minimally invasive pediatric surgery.
Article
Although perceived as a more technically demanding and time-consuming technique, the hand-sewn gastrojejunostomy during laparoscopic Roux-en-Y gastric bypass (RYGB) is associated with fewer complications and lower costs than stapled techniques. A retrospective medical record review of prospectively collected data. University hospital. One hundred eight consecutive patients undergoing laparoscopic RYGB between January 1, 1999, and December 31, 2001. Three techniques were compared: hand-sewn anastomosis (HSA), circular-stapled anastomosis (CSA), and linear-stapled anastomosis (LSA). Operative costs, including the cost of stapling devices, the cost of sutures, and operative times, were compared. Rates of anastomotic strictures, leaks, marginal ulcers, bleeding, and wound infections were determined. Eighty-seven patients underwent HSA; 13, CSA; and 8, LSA. Supply costs per patient were higher for CSA ($955) and LSA ($435) than for HSA ($2) (P<.001). The mean +/- SEM operative time for laparoscopic RYGB was longer when performing CSA than HSA or LSA (285 +/- 22 vs 215 +/- 8 and 204 +/- 28 minutes, respectively; P<.001). Stricture rates were higher after CSA than HSA and LSA (4 [31%] of 13 patients vs 3 [3%] of 87 patients and 0 of 8 patients, respectively; P<.01). The wound infection rate was higher after CSA than HSA and LSA (3 [23%] of 13 patients vs 1 [1%] of 87 patients and 0 of 8 patients, respectively; P<.001). There was no difference in anastomotic bleeding, and no anastomotic leaks occurred. In this experience, hand-sewn gastrojejunostomy during laparoscopic RYGB reduced operating room supply costs and was completed faster than stapled techniques. However, these differences may reflect the learning curve because these techniques were used early in our experience. Lower postoperative stricture and wound infection rates seem to be the primary benefits of the HSA technique.
Article
As part of a Food and Drug Administration trial, mitral repairs were performed in 38 patients using the robotic da Vinci surgical system (Intuitive Surgical, Inc, Mountain View, CA). Prospectively, we evaluated safety and efficacy in performing both simple and complex mitral repairs. Eligible patients had nonischemic moderate to severe mitral insufficiency. Operative techniques included peripheral cardiopulmonary perfusion, a 4- to 5-cm mini-thoracotomy, transthoracic aortic occlusion, and antegrade blood cardioplegia. Transesophageal echocardiograms were done intraoperatively with three-dimensional reconstructions. Successful repairs were defined as mild or less residual regurgitation. Enhanced three-dimensional visualization of mitral leaflets and the subvalvar apparatus allowed safe, dexterous intracardiac tissue manipulation. All patients had successful valve repairs including quadrangular resections, sliding plasties, and edge-to-edge approximations, as well as both chordal transfers and replacements. There were no operative deaths, strokes, or device-related complications. One patient required valve replacement for hemolysis and 1 was reexplored for bleeding. There were no incisional conversions. Both robotic repair and total operating times decreased significantly from 1.9 +/- 0.1 and 5.1 +/- 0.1 hours (mean +/- standard error of the mean) for the first 19 patients to 1.5 +/- 0.1 (p = 0.002) and 4.4 +/- 0.1 hours (p = 0.04) for the last 19 operations, respectively. Total hospital length of stay for patients was 3.8 +/- 0.6 days. Of all patients, 31 (82%) had a 4-day or less length of stay. Seven patients (18%) had stays between 5 and 9 days (6.4 +/- 1.0). This study shows that the da Vinci surgical system (Intuitive Surgical, Inc) has few limitations in performing complex valve repairs. Articulated wrist-like instruments and three-dimensional visualization enabled precise tissue telemanipulation. Future robotic design advances and adjunctive suture technologies may promote continuing evolution of robotic cardiac operations.
Article
Robotic surgery offers all the advantages of laparoscopy with additional increased accuracy. The use of robotic surgery has increased in the past 5 years. It has proven particularly useful in complex surgical procedures such as intracorporeal intestinal anastomosis. As the prevalence of robotic surgery increases, so will the need for residents to be able to perform surgery using the robotic system. Our goal was to compare hand-sewn, laparoscopic, and robotic suturing techniques performed by midlevel residents using a porcine intestinal model. Fifteen residents unfamiliar with the robotic suturing technique participated in performing an initial hand-sewn suture line and then were randomized with cross-over to laparoscopic or robotic suturing. Completion time, leak pressure, number of sutures per cm, and difficulty level were assessed. The mean leak pressure for hand-sewn, laparoscopic, and robotic suturing was 9.5, 3.2, and 11.4 mm Hg, respectively. The laparoscopic group had 6 and the robotic group had 1 suture line that was inadequate for testing. Suture breakage was common in the robotic group. The anastomosis was considered hard by 92% in the laparoscopic group versus 17% in the robotic group. The time it took to complete 1 cm of anastomosis was .9, 8.7, and 8.3 minutes for hand-sewn, laparoscopic, and robotic suturing, respectively. The robotic suture line performed by midlevel residents was superior to laparoscopy, although the time for anastomosis was equivalent.
Article
The single stapling technique (SST) and the double stapling technique (DST) are common anastomoses for rectal cancer. Although many mechanical devices have been developed, the best choice remains unclear. In this study we examined the strength of anastomoses by determining their bursting pressures using an animal model. The intestines of pigs were used. In experiment 1, we compared the bursting pressures for Endo GIA 60 blue, Endo GIA 60 green, and GIA 60 blue. In experiment 2, the bursting pressures of a buttressed cutting site and a nonbuttressed cutting site were measured. In experiment 3, the SST, DST, and DST with buttress using PCEEA were performed and the bursting pressures and points of these anastomoses were examined. The bursting pressure of Endo GIA 60 blue (80.3 +/- 10.5 mmHg) was significantly higher than that of Endo GIA 60 green (37.3 +/- 4.2 mmHg) and GIA 60 blue (31.7 +/- 5.8 mmHg) (p < 0.01). When a cut end was buttressed, the bursting pressure (149.6 +/- 37.6 mmHg) was significantly higher than that of the nonbuttressed end (75.3 +/- 25.1 mmHg) (p < 0.01). The bursting pressure among SST, DST, and DST with buttress was not significantly different. Only one bursting point was the crossing point of the PCEEA and Endo GIA and the bursting pressure of this point was much lower than that of the others. Endo GIA was most suitable for DST. The SST, DST, and DST with buttress had almost the same strength. The crossing point of PCEEA and Endo GIA may be a dangerous point for DST.
Article
The modern-day urologist is continually armed with new instruments and technology aimed at decreasing the overall invasiveness of urologic procedures. Robotic technology is aimed at improving clinical outcomes by correcting human technical inadequacies such as hand tremors and imprecise suturing. The first reported use of robotics to assist with surgery was in 1985, and the first use of robotics in urology was published in 1989. The currently utilized master-slave system (da Vinci Robotic Platform), Intuitive Surgical, Sunnyvale, CA) has popularized robotic surgery for use in numerous urologic conditions including prostate cancer, bladder cancer, renal cancer, uretero-pelvic junction obstruction, and pelvic prolapse. New developments in robotic technology may revolutionize many other aspects of urology including percutaneous renal access and rounding on patients after surgery. This review provides a brief overview of the history of robotics in urology, a description of the da Vinci surgical system and its current utiliz