• Capsule endoscopy
• Colonic polyp
• Colonoscopy
• Colorectal cancer
• Endoscopy
• Robot-enhanced procedures

• Colonoscopes
• Colonoscopy
• Equipment Design
• Humans
• Robotic Surgical Procedures
• Robotics

• 27744 Cancer Research UK

The proliferation of video capsule endoscopy (VCE) would not have been possible without continued technological improvements in imaging and locomotion. Advancements in imaging include both software and hardware improvements but perhaps the greatest software advancement in imaging comes in the form of artificial intelligence (AI). Current research into AI in VCE includes the diagnosis of tumors, gastrointestinal bleeding, Crohn’s disease, and celiac disease. Other advancements have focused on the improvement of both camera technologies and alternative forms of imaging. Comparatively, advancements in locomotion have just started to approach clinical use and include onboard controlled locomotion, which involves miniaturizing a motor to incorporate into the video capsule, and externally controlled locomotion, which involves using an outside power source to maneuver the capsule itself. Advancements in locomotion hold promise to remove one of the major disadvantages of VCE, namely, its inability to obtain targeted diagnoses. Active capsule control could in turn unlock additional diagnostic and therapeutic potential, such as the ability to obtain targeted tissue biopsies or drug delivery. With both advancements in imaging and locomotion has come a corresponding need to be better able to process generated images and localize the capsule’s position within the gastrointestinal tract. Technological advancements in computation performance have led to improvements in image compression and transfer, as well as advancements in sensor detection and alternative methods of capsule localization. Together, these advancements have led to the expansion of VCE across a number of indications, including the evaluation of esophageal and colon pathologies including esophagitis, esophageal varices, Crohn’s disease, and polyps after incomplete colonoscopy. Current research has also suggested a role for VCE in acute gastrointestinal bleeding throughout the gastrointestinal tract, as well as in urgent settings such as the emergency department, and in resource-constrained settings, such as during the COVID-19 pandemic. VCE has solidified its role in the evaluation of small bowel bleeding and earned an important place in the practicing gastroenterologist’s armamentarium. In the next few decades, further improvements in imaging and locomotion promise to open up even more clinical roles for the video capsule as a tool for non-invasive diagnosis of lumenal gastrointestinal pathologies.

Conventional optical colonoscopy is considered the gold standard investigation for colorectal tract pathology including colorectal malignancy, polyps and inflammatory bowel disease. Inherent limitations exist with current generation endoscopic technologies, including, but not limited to, patient discomfort, endoscopist fatigue, narrow field of view and missed pathology behind colonic folds. Rapid developments in medical robotics have led to the emergence of a variety of next-generation robotically-augmented technologies that could overcome these limitations.

To provide a comprehensive summary of recent developments in the application of robotics in lower gastrointestinal tract endoscopy.

A systematic review of the literature was performed from January 1, 2000 to the January 7, 2021 using EMBASE, MEDLINE and Cochrane databases. Studies reporting data on the use of robotic technology in ex vivo or in vivo animal and human experiments were included. In vitro studies (studies using synthetic colon models), studies evaluating non-robotic technology, robotic technology aimed at the upper gastrointestinal tract or paediatric endoscopy were excluded. System ergonomics, safety, visualisation, and diagnostic/therapeutic capabilities were assessed.

Initial literature searching identified 814 potentially eligible studies, from which 37 were deemed suitable for inclusion. Included studies were classified according to the actuation modality of the robotic device(s) as electromechanical (EM) (n = 13), pneumatic (n = 11), hydraulic (n = 1), magnetic (n = 10) and hybrid (n = 2) mechanisms. Five devices have been approved by the Food and Drug Administration, however most of the technologies reviewed remain in the early phases of testing and development. Level 1 evidence is lacking at present, but early reports suggest that these technologies may be associated with improved pain and safety. The reviewed devices appear to be ergonomically capable and efficient though to date no reports have convincingly shown diagnostic or therapeutic superiority over conventional colonoscopy.

Significant progress in robotic colonoscopy has been made over the last couple of decades. Improvements in design together with the integration of semi-autonomous and autonomous systems over the next decade will potentially result in robotic colonoscopy becoming more commonplace.

• Robotics
• Colonoscopy
• Endoscopy
• Automation
• Actuation
• Propulsion

We developed a magnetic-assisted capsule colonoscope system with integration of computer vision-based object detection and an alignment control scheme. Two convolutional neural network models A and B for lumen identification were trained on an endoscopic dataset of 9080 images. In the lumen alignment experiment, models C and D used a simulated dataset of 8414 images. The models were evaluated using validation indexes for recall (R), precision (P), mean average precision (mAP), and F1 score. Predictive performance was evaluated with the area under the P-R curve. Adjustments of pitch and yaw angles and alignment control time were analyzed in the alignment experiment. Model D had the best predictive performance. Its R, P, mAP, and F1 score were 0.964, 0.961, 0.961, and 0.963, respectively, when the area of overlap/area of union was at 0.3. In the lumen alignment experiment, the mean degrees of adjustment for yaw and pitch in 160 trials were 21.70° and 13.78°, respectively. Mean alignment control time was 0.902 s. Finally, we compared the cecal intubation time between semi-automated and manual navigation in 20 trials. The average cecal intubation time of manual navigation and semi-automated navigation were 9 min 28.41 s and 7 min 23.61 s, respectively. The automatic lumen detection model, which was trained using a deep learning algorithm, demonstrated high performance in each validation index.

• 27744 Cancer Research UK
• P30 DK058404 NIDDK NIH HHS
• R01 EB018992 NIBIB NIH HHS

• depth map reconstruction
• monocular capsule endoscopy
• non-ideal Lambertian surface
• photometric stereo
• specular highlight

• Animals
• Capsule Endoscopy
• Image Processing, Computer-Assisted
• Swine

• 2019YFB1312400 National Key R&D Program of China

• comparative performance analysis
• magnetically-actuated colonoscope
• minimally invasive colonoscopy
• robotic colonoscopy
• soft-tethered capsule endoscope

• 688592 H2020 LEIT Information and Communication Technologies
• "Dipartimenti di Eccellenza ex. L.232/2016" to the Department of Surgical Sciences, University of Torino, Italy Ministero dell'Istruzione, dell'Università e della Ricerca

• artificial intelligence
• colorectal cancer screening
• computer-aided diagnosis for colonoscopy
• robotic colonoscopy
• robotics for medical distancing

• Capsule Colonoscopy
• Dynamic Control
• Magnetic Robots Control

• P30 DK058404 NIDDK NIH HHS
• R01 EB018992 NIBIB NIH HHS

• physical examination
• biomedical engineering
• polymers
• mechanical engineering

• Medical Robots and Systems
• Motion Control
• Nonholonomic Mechanisms and Systems
• Surgical Robotics: Steerable Catheters/Needles

• P30 DK058404 NIDDK NIH HHS
• R01 EB018992 NIBIB NIH HHS

• Medical robots and systems
• force control
• motion control

• P30 DK058404 NIDDK NIH HHS
• R01 EB018992 NIBIB NIH HHS

• Pose estimation
• capsule endoscopy
• localization
• magnetic actuation
• robotic endoscopy

• P30 DK058404 NIDDK NIH HHS
• R01 EB018992 NIBIB NIH HHS

• Capsule locomotion
• Capsule robots
• Drug delivery
• Remote controlled capsules
• Wireless capsule endoscopy

• Colon capsule endoscopy (CCE)
• adenomas
• colonoscopy
• colorectal cancer screening
• computer tomography colonography (CTC)
• inflammatory bowel disease (IBD)
• polyps
• review

Colon capsule endoscopy utilizing PillCam COLON 2 capsule allows for visualization potentially of the entire colon and is currently approved for patients who cannot withstand the rigors of traditional optical colonoscopy (OC) and associated sedation as well as those that had an OC that was incomplete for technical reasons other than a poor preparation. We will then describe the prior experience and current status of colon capsule endoscopy.

Digestive diseases are a major burden for society and healthcare systems, and with an aging population, the importance of their effective management will become critical. Healthcare systems worldwide already struggle to insure quality and affordability of healthcare delivery and this will be a significant challenge in the midterm future. Wireless capsule endoscopy (WCE), introduced in 2000 by Given Imaging Ltd., is an example of disruptive technology and represents an attractive alternative to traditional diagnostic techniques. WCE overcomes conventional endoscopy enabling inspection of the digestive system without discomfort or the need for sedation. Thus, it has the advantage of encouraging patients to undergo gastrointestinal (GI) tract examinations and of facilitating mass screening programmes. With the integration of further capabilities based on microrobotics, e.g. active locomotion and embedded therapeutic modules, WCE could become the key-technology for GI diagnosis and treatment. This review presents a research update on WCE and describes the state-of-the-art of current endoscopic devices with a focus on research-oriented robotic capsule endoscopes enabled by microsystem technologies. The article also presents a visionary perspective on WCE potential for screening, diagnostic and therapeutic endoscopic procedures.

• Digestive endoscopy
• Medical robots
• Microsystem technologies
• Robotic endoscopic capsules
• Wireless capsule endoscopy (WCE)

• Abdomen/surgery
• Humans
• Magnetic Phenomena
• Robotic Surgical Procedures/instrumentation
• Surgical Instruments

• Capsule endoscopy
• Capsule robot mobility
• Diagnostic capsule
• Magnetic capsule endoscopy
• Therapeutic capsule

• Animals
• Capsule Endoscopes
• Capsule Endoscopy/methods
• Drug Delivery Systems
• Equipment Design
• Humans
• Magnetics
• Peristalsis
• Robotics
• Video Recording

• R01 EB018992 NIBIB NIH HHS
• R01EB018992 NIBIB NIH HHS

• Image enhancement
• Localization
• Locomotion
• Magnetic manipulation
• Medical robotics

• R01 EB018992 NIBIB NIH HHS

• musculoskeletal injury
• ergonomics
• endoscopy
• cumulative trauma disorders
• occupational diseases

• Animals
• Capsule Endoscopes
• Capsule Endoscopy/instrumentation
• Capsule Endoscopy/methods
• Colonoscopes
• Colonoscopy/instrumentation
• Colonoscopy/methods
• Colorectal Neoplasms/diagnosis
• Colorectal Neoplasms/surgery
• Equipment Design
• Feasibility Studies
• Female
• Magnetics/instrumentation
• Models, Anatomic
• Pain/prevention & control
• Robotics/instrumentation
• Sus scrofa