Application of small bowel capsule endoscopy in children with Meckel's diverticulum.

BACKGROUND: Meckel diverticulum (MD) is an important cause of gastrointestinal bleeding in children. Small bowel capsule endoscopy (SBCE) is a first-line examination method applied to patients with obscure gastrointestinal bleeding, but there are few studies on its application in children with MD. This article aims to provide evidence in favor of the auxiliary diagnosis of MD in children by analyzing its characteristics using SBCE. METHODS: We retrospectively collected the clinical data of patients with suspected MD. RESULTS: A total of 58 children were included in this study. All 58 children presented overt gastrointestinal bleeding (bloody stool or melena). Capsule endoscopy identified protruding lesions in 2 cases, double-lumen changes in 30 cases (all considered as MD), vascular lesions in 7 cases, intestinal mucosal inflammatory lesions in 3 cases, ulcers or erosion in 3 cases, and no obvious abnormalities in SBCE in 12 cases. Both SBCE and technetium-99 scans were performed for 24 cases, 22 of which were diagnosed MD by their combined results, giving a diagnostic coincidence rate of 91.7%. Eight cases were highly suspected as MD but were negative for the technetium-99 scan and positive for SBCE. CONCLUSION: SBCE has high accuracy in the diagnosis of MD in children, especially when performed in combination with a technetium-99 scan, which can greatly improve the diagnostic rate of MD in children.

Design of a Compact Circularly Polarized Implantable Antenna for Capsule Endoscopy Systems.

This research proposes a miniature circular polarization antenna used in a wireless capsule endoscopy system at 2.45 GHz for industrial, scientific, and medical bands. We propose a method of cutting a chamfer rectangular slot on a circular radiation patch and introducing a curved radiation structure into the centerline position of the chamfer rectangular slot, while a short-circuit probe is added to achieve miniaturization. Therefore, we significantly reduced the size of the antenna and made it exhibit circularly polarized radiation characteristics. A cross-slot is cut in the GND to enable the antenna to better cover the operating band while being able to meet the complex human environment. The effective axis ratio bandwidth is 120 MHz (2.38-2.50 GHz). Its size is π × 0.032λ02 × 0.007λ0 (where λ0 is the free-space wavelength of at 2.4 GHz). In addition, the effect of different organs such as muscle, stomach, small intestine, and big intestine on the antenna when it was embedded into the wireless capsule endoscopy (WCE) system was further discussed, and the results proved that the WCE system has better robustness in different organs. The antenna's specific absorption rate can follow the IEEE Standard Safety Guidelines (IEEE C95.1-1999). A prototype is fabricated and measured. The experimental results are consistent with the simulation results.

Efficacy and safety of three-dimensional magnetically assisted capsule endoscopy for upper gastrointestinal and small bowel examination.

BACKGROUND: Magnetically assisted capsule endoscopy (MACE) showed the feasibility for upper gastrointestinal examination. To further enhance the performance of conventional MACE, it is necessary to provide quality-improved and three-dimensional images. The aim of this clinical study was to determine the efficacy and safety of novel three-dimensional MACE (3D MACE) for upper gastrointestinal and small bowel examination at once. METHODS: This was a prospective, single-center, non-randomized, and sequential examination study (KCT0007114) at Dongguk University Ilsan Hospital. Adult patients who visited for upper endoscopy were included. The study protocol was conducted in two stages. First, upper gastrointestinal examination was performed using 3D MACE, and a continuous small bowel examination was performed by conventional method of capsule endoscopy. Two hours later, an upper endoscopy was performed for comparison with 3D MACE examination. The primary outcome was confirmation of major gastric structures (esophagogastric junction, cardia/fundus, body, angle, antrum, and pylorus). Secondary outcomes were confirmation of esophagus and duodenal bulb, accuracy for gastric lesions, completion of small bowel examination, 3D image reconstruction of gastric lesion, and safety. RESULTS: Fifty-five patients were finally enrolled. The examination time of 3D MACE was 14.84 ± 3.02 minutes and upper endoscopy was 5.22 ± 2.39 minutes. The confirmation rate of the six major gastric structures was 98.6% in 3D MACE and 100% in upper endoscopy. Gastric lesions were identified in 43 patients during 3D MACE, and 40 patients during upper endoscopy (Sensitivity 0.97). 3D reconstructed images were acquired for all lesions inspected by 3D MACE. The continuous small bowel examination by 3D MACE was completed in 94.5%. 3D MACE showed better overall satisfaction (3D MACE 9.55 ± 0.79 and upper endoscopy 7.75 ± 2.34, p<0.0001). There were no aspiration or significant adverse event or capsule retention in the 3D MACE examination. CONCLUSIONS: Novel 3D MACE system is more advanced diagnostic modality than the conventional MACE. And it is possible to perform serial upper gastrointestinal and small bowel examination as a non-invasive and one-step test. It would be also served as a bridge to pan-endoscopy.

Robotic wireless capsule endoscopy: recent advances and upcoming technologies.

Wireless capsule endoscopy (WCE) offers a non-invasive evaluation of the digestive system, eliminating the need for sedation and the risks associated with conventional endoscopic procedures. Its significance lies in diagnosing gastrointestinal tissue irregularities, especially in the small intestine. However, existing commercial WCE devices face limitations, such as the absence of autonomous lesion detection and treatment capabilities. Recent advancements in micro-electromechanical fabrication and computational methods have led to extensive research in sophisticated technology integration into commercial capsule endoscopes, intending to supersede wired endoscopes. This Review discusses the future requirements for intelligent capsule robots, providing a comparative evaluation of various methods' merits and disadvantages, and highlighting recent developments in six technologies relevant to WCE. These include near-field wireless power transmission, magnetic field active drive, ultra-wideband/intrabody communication, hybrid localization, AI-based autonomous lesion detection, and magnetic-controlled diagnosis and treatment. Moreover, we explore the feasibility for future "capsule surgeons".

Artificial intelligence in detection of small bowel lesions and their bleeding risk: A new step forward.

The present letter to the editor is related to the study with the title "Automatic detection of small bowel (SB) lesions with different bleeding risk based on deep learning models". Capsule endoscopy (CE) is the main tool to assess SB diseases but it is a time-consuming procedure with a significant error rate. The development of artificial intelligence (AI) in CE could simplify physicians' tasks. The novel deep learning model by Zhang et al seems to be able to identify various SB lesions and their bleeding risk, and it could pave the way to next perspective studies to better enhance the diagnostic support of AI in the detection of different types of SB lesions in clinical practice.

Capsule endoscopy and panendoscopy: A journey to the future of gastrointestinal endoscopy.

In 2000, the small bowel capsule revolutionized the management of patients with small bowel disorders. Currently, the technological development achieved by the new models of double-headed endoscopic capsules, as miniaturized devices to evaluate the small bowel and colon [pan-intestinal capsule endoscopy (PCE)], makes this non-invasive procedure a disruptive concept for the management of patients with digestive disorders. This technology is expected to identify which patients will require conventional invasive endoscopic procedures (colonoscopy or balloon-assisted enteroscopy), based on the lesions detected by the capsule, i.e., those with an indication for biopsies or endoscopic treatment. The use of PCE in patients with inflammatory bowel diseases, namely Crohn's disease, as well as in patients with iron deficiency anaemia and/or overt gastrointestinal (GI) bleeding, after a non-diagnostic upper endoscopy (esophagogastroduodenoscopy), enables an effective, safe and comfortable way to identify patients with relevant lesions, who should undergo subsequent invasive endoscopic procedures. The recent development of magnetically controlled capsule endoscopy to evaluate the upper GI tract, is a further step towards the possibility of an entirely non-invasive assessment of all the segments of the digestive tract, from mouth-to-anus, meeting the expectations of the early developers of capsule endoscopy.

Detachable string magnetically controlled capsule endoscopy for the noninvasive diagnosis of esophageal diseases: A prospective, blind clinical study.

BACKGROUND: Traditional esophagogastroduodenoscopy (EGD), an invasive examination method, can cause discomfort and pain in patients. In contrast, magnetically controlled capsule endoscopy (MCE), a noninvasive method, is being applied for the detection of stomach and small intestinal diseases, but its application in treating esophageal diseases is not widespread. AIM: To evaluate the safety and efficacy of detachable string MCE (ds-MCE) for the diagnosis of esophageal diseases. METHODS: Fifty patients who had been diagnosed with esophageal diseases were prospectively recruited for this clinical study and underwent ds-MCE and conventional EGD. The primary endpoints included the sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy of ds-MCE for patients with esophageal diseases. The secondary endpoints consisted of visualizing the esophageal and dentate lines, as well as the subjects' tolerance of the procedure. RESULTS: Using EGD as the gold standard, the sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy of ds-MCE for esophageal disease detection were 85.71%, 86.21%, 81.82%, 89.29%, and 86%, respectively. ds-MCE was more comfortable and convenient than EGD was, with 80% of patients feeling that ds-MCE examination was very comfortable or comfortable and 50% of patients believing that detachable string v examination was very convenient. CONCLUSION: This study revealed that ds-MCE has the same diagnostic effects as traditional EGD for esophageal diseases and is more comfortable and convenient than EGD, providing a novel noninvasive method for treating esophageal diseases.

Patients on Antithrombotic Agents with Small Bowel Bleeding -Yield of Small Bowel Capsule Endoscopy and Subsequent Management.

BACKGROUND AND AIMS: Small bowel gastrointestinal bleeding (GIB) is associated with multiple blood transfusions, prolonged and/or multiple hospital admissions, utilization of significant healthcare resources, and negative effects on patient quality of life. There is a well-recognized association between antithrombotic medications and small bowel GIB. We aimed to identify the diagnostic yield of small bowel capsule endoscopy (SBCE) in patients on antithrombotic medications and the impact of SBCE on treatment course. METHODS: The electronic medical records of nineteen hundred eighty-six patients undergoing SBCE were retrospectively reviewed. RESULTS: The diagnostic yield for detecting stigmata of recent bleeding and/or actively bleeding lesions in SBCE was higher in patients that were on antiplatelet agents (21.6%), patients on anticoagulation (22.5%), and in patients that had their SBCE performed while they were inpatient (21.8%), when compared to the patients not on antiplatelet agents (12.1%), patients not on anticoagulation (13.5%), and with patients that had their SBCE performed in the outpatient setting (12%). Of 318 patients who had stigmata of recent bleeding and/or actively bleeding lesion(s) identified on SBCE, SBCE findings prompted endoscopic evaluation (small bowel enteroscopy, esophagogastroduodenoscopy (EGD), and/or colonoscopy) in 25.2%, with endoscopic hemostasis attempted in 52.5%. CONCLUSIONS: Our study, the largest conducted to date, emphasizes the importance of performing SBCE as part of the evaluation for suspected small bowel bleeding, particularly in patients taking antithrombotic therapy, and especially during their inpatient hospital stay.

AI-assisted capsule endoscopy reading in suspected small bowel bleeding: a multicentre prospective study.

BACKGROUND: Capsule endoscopy reading is time consuming, and readers are required to maintain attention so as not to miss significant findings. Deep convolutional neural networks can recognise relevant findings, possibly exceeding human performances and reducing the reading time of capsule endoscopy. Our primary aim was to assess the non-inferiority of artificial intelligence (AI)-assisted reading versus standard reading for potentially small bowel bleeding lesions (high P2, moderate P1; Saurin classification) at per-patient analysis. The mean reading time in both reading modalities was evaluated among the secondary endpoints. METHODS: Patients aged 18 years or older with suspected small bowel bleeding (with anaemia with or without melena or haematochezia, and negative bidirectional endoscopy) were prospectively enrolled at 14 European centres. Patients underwent small bowel capsule endoscopy with the Navicam SB system (Ankon, China), which is provided with a deep neural network-based AI system (ProScan) for automatic detection of lesions. Initial reading was performed in standard reading mode. Second blinded reading was performed with AI assistance (the AI operated a first-automated reading, and only AI-selected images were assessed by human readers). The primary endpoint was to assess the non-inferiority of AI-assisted reading versus standard reading in the detection (diagnostic yield) of potentially small bowel bleeding P1 and P2 lesions in a per-patient analysis. This study is registered with ClinicalTrials.gov, NCT04821349. FINDINGS: From Feb 17, 2021 to Dec 29, 2021, 137 patients were prospectively enrolled. 133 patients were included in the final analysis (73 [55%] female, mean age 66·5 years [SD 14·4]; 112 [84%] completed capsule endoscopy). At per-patient analysis, the diagnostic yield of P1 and P2 lesions in AI-assisted reading (98 [73·7%] of 133 lesions) was non-inferior (p<0·0001) and superior (p=0·0213) to standard reading (82 [62·4%] of 133; 95% CI 3·6-19·0). Mean small bowel reading time was 33·7 min (SD 22·9) in standard reading and 3·8 min (3·3) in AI-assisted reading (p<0·0001). INTERPRETATION: AI-assisted reading might provide more accurate and faster detection of clinically relevant small bowel bleeding lesions than standard reading. FUNDING: ANKON Technologies, China and AnX Robotica, USA provided the NaviCam SB system.

Automated detection of small bowel lesions based on capsule endoscopy using deep learning algorithm.

BACKGROUND: In order to overcome the challenges of lesion detection in capsule endoscopy (CE), we improved the YOLOv5-based deep learning algorithm and established the CE-YOLOv5 algorithm to identify small bowel lesions captured by CE. METHODS: A total of 124,678 typical abnormal images from 1,452 patients were enrolled to train the CE-YOLOv5 model. Then 298 patients with suspected small bowel lesions detected by CE were prospectively enrolled in the testing phase of the study. Small bowel images and videos from the above 298 patients were interpreted by the experts, non-experts and CE-YOLOv5, respectively. RESULTS: The sensitivity of CE-YOLOv5 in diagnosing vascular lesions, ulcerated/erosive lesions, protruding lesions, parasite, diverticulum, active bleeding and villous lesions based on CE videos was 91.9 %, 92.2 %, 91.4 %, 93.1 %, 93.3 %, 95.1 %, and 100 % respectively. Furthermore, CE-YOLOv5 achieved specificity and accuracy of more than 90 % for all lesions. Compared with experts, the CE-YOLOv5 showed comparable overall sensitivity, specificity and accuracy (all P > 0.05). Compared with non-experts, the CE-YOLOv5 showed significantly higher overall sensitivity (P < 0.0001) and overall accuracy (P < 0.0001), and a moderately higher overall specificity (P = 0.0351). Furthermore, the time for AI-reading (5.62 ± 2.81 min) was significantly shorter than that for the other two groups (both P < 0.0001). CONCLUSIONS: CE-YOLOv5 diagnosed small bowel lesions in CE videos with high sensitivity, specificity and accuracy, providing a reliable approach for automated lesion detection in real-world clinical practice.

Capsules for the Diagnosis and Treatment of Gastrointestinal Motility Disorders- A Game Changer.

PURPOSE OF REVIEW: Over the last few decades, there have been remarkable strides in endoscopy and radiological imaging that have advanced gastroenterology. However, the management of neurogastroenterological disorders has lagged behind, in part handicapped by the use of catheter-based manometry that is both non-physiological and uncomfortable. The advent of capsule technology has been a game changer for both diagnostic and therapeutic applications. RECENT FINDINGS: Here, we discuss several capsule devices that are available or under investigation. There are three technologies that are FDA approved. Wireless motility capsule measures pH and pressure and provides clinically impactful information regarding gastric, small intestine and colonic transit, without radiation that has been demonstrated to guide management of gastroparesis, dyspepsia and constipation. Wireless ambulatory pH monitoring capsule is currently the gold standard for assessing gastroesophageal acid reflux. In the therapeutics arena, an orally ingested vibrating capsule has been recently FDA approved for the treatment of chronic constipation, supported by a robust phase 3 clinical trial which showed significant improvement in constipation symptoms and quality of life. There are several capsules currently under investigation. Smart capsule bacterial detection system and Capscan® are capsules that can sample fluid in the small or large bowel and provide microbiome analysis for detection of small intestinal bacterial (SIBO) or fungal overgrowth (SIFO). Another investigational gas sensing capsule analyzing hydrogen, CO2, volatile fatty acids and capsule orientation, can measure regional gut transit time and luminal gas concentrations and assess gastroparesis, constipation or SIBO. Therapeutically, other vibrating capsules are in development. Innovations in capsule technology are poised to transform our ability to investigate gut function physiologically, and non-invasively deliver targeted treatment(s), thereby providing both accurate diagnostic information and luminally-directed, safe therapy.

An ingestible near-infrared fluorescence capsule endoscopy for specific gastrointestinal diagnoses.

Early diagnosis of gastrointestinal (GI) diseases is important to effectively prevent carcinogenesis. Capsule endoscopy (CE) can address the pain caused by wired endoscopy in GI diagnosis. However, existing CE approaches have difficulty effectively diagnosing lesions that do not exhibit obvious morphological changes. In addition, the current CE cannot achieve wireless energy supply and attitude control at the same time. Here, we successfully developed a novel near-infrared fluorescence capsule endoscopy (NIFCE) that can stimulate and capture near-infrared (NIR) fluorescence images to specifically identify subtle mucosal microlesions and submucosal lesions while capturing conventional white light (WL) images to detect lesions with significant morphological changes. Furthermore, we constructed the first synergetic system that simultaneously enables multi-attitude control in NIFCE and supplies long-term power, thus addressing the issue of excessive power consumption caused by the NIFCE emitting near-infrared light (NIRL). We performed in vivo experiments to verify that the NIFCE can specifically "light up" tumors while sparing normal tissues by synergizing with probes actively aggregated in tumors, thus realizing specific detection and penetration. The prototype NIFCE system represents a significant step forward in the field of CE and shows great potential in efficiently achieving early targeted diagnosis of various GI diseases.

Development and validation of a deep learning system for detection of small bowel pathologies in capsule endoscopy: a pilot study in a Singapore institution.

INTRODUCTION: Deep learning models can assess the quality of images and discriminate among abnormalities in small bowel capsule endoscopy (CE), reducing fatigue and the time needed for diagnosis. They serve as a decision support system, partially automating the diagnosis process by providing probability predictions for abnormalities. METHODS: We demonstrated the use of deep learning models in CE image analysis, specifically by piloting a bowel preparation model (BPM) and an abnormality detection model (ADM) to determine frame-level view quality and the presence of abnormal findings, respectively. We used convolutional neural network-based models pretrained on large-scale open-domain data to extract spatial features of CE images that were then used in a dense feed-forward neural network classifier. We then combined the open-source Kvasir-Capsule dataset (n = 43) and locally collected CE data (n = 29). RESULTS: Model performance was compared using averaged five-fold and two-fold cross-validation for BPMs and ADMs, respectively. The best BPM model based on a pre-trained ResNet50 architecture had an area under the receiver operating characteristic and precision-recall curves of 0.969±0.008 and 0.843±0.041, respectively. The best ADM model, also based on ResNet50, had top-1 and top-2 accuracies of 84.03±0.051 and 94.78±0.028, respectively. The models could process approximately 200-250 images per second and showed good discrimination on time-critical abnormalities such as bleeding. CONCLUSION: Our pilot models showed the potential to improve time to diagnosis in CE workflows. To our knowledge, our approach is unique to the Singapore context. The value of our work can be further evaluated in a pragmatic manner that is sensitive to existing clinician workflow and resource constraints.

Application of artificial intelligence in gastrointestinal endoscopy.

Endoscopy is an important method for diagnosing gastrointestinal (GI) diseases. In this study, we provide an overview of the advances in artificial intelligence (AI) technology in the field of GI endoscopy over recent years, including esophagus, stomach, large intestine, and capsule endoscopy (small intestine). AI-assisted endoscopy shows high accuracy, sensitivity, and specificity in the detection and diagnosis of GI diseases at all levels. Hence, AI will make a breakthrough in the field of GI endoscopy in the near future. However, AI technology currently has some limitations and is still in the preclinical stages.

Deep learning in negative small-bowel capsule endoscopy improves small-bowel lesion detection and diagnostic yield.

OBJECTIVES: Although several studies have shown the usefulness of artificial intelligence to identify abnormalities in small-bowel capsule endoscopy (SBCE) images, few studies have proven its actual clinical usefulness. Thus, the aim of this study was to examine whether meaningful findings could be obtained when negative SBCE videos were reanalyzed with a deep convolutional neural network (CNN) model. METHODS: Clinical data of patients who received SBCE for suspected small-bowel bleeding at two academic hospitals between February 2018 and July 2020 were retrospectively collected. All SBCE videos read as negative were reanalyzed with the CNN algorithm developed in our previous study. Meaningful findings such as angioectasias and ulcers were finally decided after reviewing CNN-selected images by two gastroenterologists. RESULTS: Among 202 SBCE videos, 103 (51.0%) were read as negative by humans. Meaningful findings were detected in 63 (61.2%) of these 103 videos after reanalyzing them with the CNN model. There were 79 red spots or angioectasias in 40 videos and 66 erosions or ulcers in 35 videos. After reanalysis, the diagnosis was changed for 10 (10.3%) patients who had initially negative SBCE results. During a mean follow-up of 16.5 months, rebleeding occurred in 19 (18.4%) patients. The rebleeding rate was 23.6% (13/55) for patients with meaningful findings and 16.1% (5/31) for patients without meaningful findings (P = 0.411). CONCLUSION: Our CNN algorithm detected meaningful findings in negative SBCE videos that were missed by humans. The use of deep CNN for SBCE image reading is expected to compensate for human error.

Comparison of clinical utility of deep learning-based systems for small-bowel capsule endoscopy reading.

BACKGROUND AND AIM: Convolutional neural network (CNN) systems that automatically detect abnormalities from small-bowel capsule endoscopy (SBCE) images are still experimental, and no studies have directly compared the clinical usefulness of different systems. We compared endoscopist readings using an existing and a novel CNN system in a real-world SBCE setting. METHODS: Thirty-six complete SBCE videos, including 43 abnormal lesions (18 mucosal breaks, 8 angioectasia, and 17 protruding lesions), were retrospectively prepared. Three reading processes were compared: (A) endoscopist readings without CNN screening, (B) endoscopist readings after an existing CNN screening, and (C) endoscopist readings after a novel CNN screening. RESULTS: The mean number of small-bowel images was 14 747 per patient. Among these images, existing and novel CNN systems automatically captured 24.3% and 9.4% of the images, respectively. In this process, both systems extracted all 43 abnormal lesions. Next, we focused on the clinical usefulness. The detection rates of abnormalities by trainee endoscopists were not significantly different across the three processes: A, 77%; B, 67%; and C, 79%. The mean reading time of the trainees was the shortest during process C (10.1 min per patient), followed by processes B (23.1 min per patient) and A (33.6 min per patient). The mean psychological stress score while reading videos (scale, 1-5) was the lowest in process C (1.8) but was not significantly different between processes B (2.8) and A (3.2). CONCLUSIONS: Our novel CNN system significantly reduced endoscopist reading time and psychological stress while maintaining the detectability of abnormalities. CNN performance directly affects clinical utility and should be carefully assessed.

Prospective study of diagnostic yields of flexible spectral imaging color enhancement installed in colon capsule endoscopy for colorectal polyps and tumors.

BACKGROUND AND AIMS: We prospectively determined the efficacy of flexible spectral imaging color enhancement (FICE) used with second-generation colon capsule endoscopy (CCE) for colorectal polyps and tumors (CRTs). METHODS: This study included optical colonoscopy within 4 months after CCE. Two colonoscopists independently reviewed CCE using white-light images (CCE-WL) and CCE using FICE images (CCE-FICE), respectively. Based on colonoscopic findings as the criterion standard, the diagnostic accuracy for CRTs was compared between CCE-WL and CCE-FICE. RESULTS: Of 89 enrolled patients (65 men and 24 women; 75 with CRTs including 36 with serrated lesions, 63 with adenomas, and 9 with adenocarcinomas), the per-patient detectability of CCE-FICE for the representative CRTs was significantly higher than that of CCE-WL: overall CRTs (CCE-WL, 79%; CCE-FICE, 88%; P = .0001), 6- to 9-mm CRTs (CCE-WL, 63%; CCE-FICE, 94%; P = .0055), and ≥6-mm CRTs (CCE-WL, 78%; CCE-FICE, 93%; P = .0159). The per-lesion sensitivity of CCE-FICE was significantly higher than that of CCE-WL for CRTs: overall (CCE-WL, 61%; CCE-FICE, 79%; P < .0001), <6 mm (CCE-WL, 53%; CCE-FICE, 69%; P < .0001), 6- to 9-mm CRTs (CCE-WL, 65%; CCE-FICE, 93%; P = .0007), slightly elevated CRTs (CCE-WL, 53%; CCE-FICE, 75%; P < .0001), tubular adenomas (CCE-WL, 61%; CCE-FICE, 79%; P < .0001), and serrated polyps (CCE-WL, 57%; CCE-FICE, 74%; P = .0022). Both modes detected all adenocarcinomas. No significant differences were found between CCE-WL and CCE-FICE of the per-lesion sensitivity for ≥10-mm CRTs (CCE-WL, 81%; CCE-FICE, 94%; P = .1138) or protruding CRTs (CCE-WL, 77%; CCE-FICE, 86%; P = .0614). Kappa coefficients for overall CRTs for CCE-WL and CCE-FICE were .66 and .64, respectively, which indicated substantial agreement. CONCLUSIONS: CCE-FICE improved the detection rates for all CRTs except adenocarcinomas, ≥10-mm polyps, and protruding polyps when compared with CCE-WL. (Clinical trial registration number: UMIN 000021125.).

Active distance control in multi-capsule endoscopy via closed loop electromagnetic force between capsules.

Capsule endoscopy offers a non-invasive and patient-friendly method for imaging the gastrointestinal tract, boasting superior tissue accessibility compared to traditional endoscopy and colonoscopy. While advances have led to capsules capable of drug delivery, tactile sensing, and biopsy, size constraints often limit a single capsule from having multifunctionality. In response, we introduce multi-capsule endoscopy, where individually ingested capsules, each with unique functionalities, work collaboratively. However, synchronized navigation of these capsules is essential for this approach. In this paper, we present an active distance control strategy using a closed-loop system. This entails equipping one capsule with a sphere permanent magnet and the other with a solenoid. We utilized a Simulink model, incorporating (i) the peristalsis motion on the primary capsule, (ii) a PID controller, (iii) force dynamics between capsules through magnetic dipole approximation, and (iv) position tracking of the secondary capsule. For practical implementation, Hall effect sensors determined the inter-capsule distance, and a PID controller adjusted the solenoid's current to maintain the desired capsule spacing. Our proof-of-concept experiments, conducted on phantoms and ex vivo bovine tissues, pulled the leading capsule mimicking a typical human peristalsis speed of 1 cm/min. Results showcased an inter-capsule distance of 1.94 mm ± 0.097 mm for radii of curvature at 500 mm, 250 mm, and 100 mm, aiming for a 2-mm capsule spacing. For ex vivo bovine tissue, the achieved distance was 0.97 ± 0.28 mm against a target inter-capsule distance of 1 mm. Through the successful demonstration of precise inter-capsule control, this study paves the way for the potential of multi-capsule endoscopy in future research.

Rotational Platform for Real-Time Localization for Active Implantable Medical Devices.

This paper presents a sensor based localization system to localize active implantable medical devices i.e., Wireless Capsule Endoscopy (WCE). The importance of localizing the capsule arises once the images from the capsule detect the abnormalities in the Gastrointestinal tract (GI). A successful system can determine the location that associated with the abnormality for further medical investigation or treatment. The system proposed in this paper comprises a rotational platform that consists of magnetic sensors to detect the position of the embedded magnet in the capsule. The rotational platform provides advantageousness in terms of reducing the number of the sensors and increasing the monitoring accuracy during the real time movement.