Society: ASGE

Background and Aims: To date, whole gastrointestinal capsule endoscopy from the esophagus to the colorectum has not been fully accomplished. We have developed the guiding device using neodymium magnet (L 139 mm X W 139 mm X H 30 mm, weight: 2.3 kg) by which a colon capsule endoscope (PillCam^TMCOLON2) can be manipulated 10 cm apart with 6.3-mN propulsion force exerted by 17-mT magnetic flux density in a single hand. We aim to determine the diagnostic yields of this magnetically-aided capsule endoscopy (MACE) for the esophageal, gastric and colorectal tumors in a randomized controlled trial.
Methods: Patients with superficial esophageal carcinomas (EC), gastric tumors (GT), and colorectal tumors (CRT) were randomly allocated to two groups: one group with a same-sized non-magnetic sham device (S group) and the other with the magnetic device (M group) (1:1; stratified by age, gender, and tumor location). CE was performed mainly in the stomach after ingesting polyethylene glycol-electrolyte lavage solution plus ascorbic acid and mineral water. Optical colonoscopy was performed after excreting CE or around 5 pm without excretion on the same examination day. The primary outcomes were detection rates for the documented tumors and unknown gastrointestinal lesions, based on esophagogastroduodenoscopic and colonoscopic findings. The secondary outcome was observation rates of each gastric part (jRCTs042180150).
Results: We randomly allocated 92 patients (74 men and 18 women, median age: 67, 20-78 y) to the S group (n= 45; 5 ECs, 22 GTs: 7 submucosal and 12 intramucosal carcinomas, and 3 dysplasias, 18 CRTs: 2 advanced carcinomas, 1 submucosal carcinoma, and 15 dysplasias) and the M group (n=47; 4 ECs, 25 GTs: 2 advanced, 1 submucosal, and 16 intramucosal carcinomas, 4 dysplasias, 1 MALToma, and 1 hamartoma, and 18 CRTs: 3 intramucosal carcinomas, 13 dysplasias, 1 hamartoma, and 1 serrated lesion). Examination time and excretion rates were 308 (74-533) m and 315 (84-867) m (P=0.0670), and 87% and 85% (P>0.9999) in the S and M groups, respectively. Detection rates for GTs in the S and M groups were 95% and 100% (P=0.4565), while those for unknown gastric lesions such as polyps and xanthomas were 73％ (47/64) and 100％(81/81, P＜0.0001), even though median numbers of recoding images in the stomach were 98,962 (3,054 - 233,406) and 94,301 (15,213 - 335,827, P=0.7821), respectively. Detection rates for CRTs were 100% and 94% (P>0.9999), and those for unknown colorectal lesions were 75％ and 68％ (P=0.3787); those for ECs were 60% and 75% (P>0.9999) in the S and M groups, respectively. Gastric observation rates were 85% and 97% (P< 0.0001) in the S and M groups, respectively, in which those of the fornix, lower body, and angle were significantly distinct.
Conclusions: This trial provides evidence supporting that MACE is feasible to undergo gastrointestinal tumor screening.

Background: Magnetically assisted capsule endoscopy (MACE) is emerging as an option to complement and replace the upper endoscopy. Three-dimension (3D) MACE system can reconstruct 3D images and improve image quality compared to conventional MACE. We decided to identify the performance and safety of novel 3D MACE and hand-held controller for upper gastrointestinal and small bowel examination.
Method: This study was organized as a prospective, single-center, sequential examination, and non-inferiority trial (KCT0007114). It was conducted on patients who visited Dongguk University Ilsan Hospital for upper endoscopy between April and June 2022. First, 3D MACE was performed for upper gastrointestinal examination. Then two hours later, a sedative upper endoscopy was performed to confirm the accuracy and safety of 3D MACE. Small bowel examination was performed simultaneously using 3D MACE. The primary outcome was to identify of major gastric structures: Esophagogastric junction, cardia/fundus, body, angle, antrum, and pylorus. The secondary outcomes included identification of major upper gastrointestinal structures (add esophagus and bulb from primary outcome), completion of small bowel examination, 3D image reconstruction of gastric lesion, and confirmation of 3D MACE safety.
Results: Upper gastrointestinal examination time was 14.84 ± 3.02 mins in the 3D MACE group and 5.22 ± 2.39 mins in the upper endoscopy. The success rate of identification of the six major gastric structures was 98.6% in 3D MACE and 100% in upper endoscopy. The success rate of identification of the eight major upper gastrointestinal structures was 99.1% in 3D MACE and 100% in upper endoscopy, showing similar performance (Figure 1). 3D reconstructed images were acquired for all lesions observed in 3D MACE using a reading viewer (Figure 2). A complete small bowel examination was confirmed in 52 of 55 patients (94.5%), and the mean small bowel transit time was 260.34 ± 101.14 minutes. For overall patient satisfaction based on a maximum of 10 points (the higher the better), 3D MACE was scored 9.55 ± 0.79 and upper endoscopy was scored 7.75 ± 2.34 (p<0.0001). No significant adverse event and capsule retention occurred in the 3D MACE system.
Conclusion: Novel 3D MACE with hand-held magnet controller is a non-inferior option for upper gastrointestinal examination compared to upper endoscopy. In addition, small bowel examination was possible simultaneously with upper gastrointestinal examination with 3D MACE.

<b>Figure 1. The major upper gastrointestinal structures identified in 3D MACE examination</b>. (A) esophagus, (B) esophagogastric junction, (C) cardia and fundus, (D) body, (E) gastric angle, (F) antrum, (G) pylorus, (H) duodenal bulb.

Figure 1. The major upper gastrointestinal structures identified in 3D MACE examination. (A) esophagus, (B) esophagogastric junction, (C) cardia and fundus, (D) body, (E) gastric angle, (F) antrum, (G) pylorus, (H) duodenal bulb.

<b>Figure 2. Abnormal lesion detection and 3D image reconstruction using 3D MACE system.</b> [A] Elevated erosion (top image) and ulceration (bottom image) were observed during 3D MACE examination. [B] The images of the lesion were 3D reconstructed and rotated using a reading viewer. [C] Erosion and ulceration were also observed by an upper endoscopy in the same location. The images of lesion obtained by 3D MACE and upper endoscopy were almost identical.

Figure 2. Abnormal lesion detection and 3D image reconstruction using 3D MACE system. [A] Elevated erosion (top image) and ulceration (bottom image) were observed during 3D MACE examination. [B] The images of the lesion were 3D reconstructed and rotated using a reading viewer. [C] Erosion and ulceration were also observed by an upper endoscopy in the same location. The images of lesion obtained by 3D MACE and upper endoscopy were almost identical.

BACKGROUND & AIMS: During wireless capsule endoscopy, real-time localization of the capsule endoscope in the alimentary tract depends on visual inspection of endoscopic images, which is a laborious task. To date, computer-aided diagnosis (CAD) systems to localize the capsule endoscope have not been realized in clinical practice. In this study, a CAD system for localization of the capsule endoscope based on endoscopic images was developed and its diagnostic performance evaluated.
METHODS: A total of 199 capsule endoscopic videos consecutively recorded from October 2010 through August 2021 in one institution were assigned as training data (n=172), validation data (n=7), and testing data (n=20). Still images (stomach 22640, small intestine 24140, and colon 24842) were randomly extracted from training data, and preprocessed using data augmentation to improve data versatility. Feature extraction was performed by a deep neural network (SwinTransformer) to construct a CAD system that discriminates images of the stomach, small intestine (including duodenum) and colon. The reference standard for localization is based on visual inspection by physicians. The CAD system was trained to classify the location of endoscopy images, and the corresponding accuracy was evaluated using still images extracted from validation videos. Random errors of image classification were further removed by an isolation tree, an unsupervised tree-based algorithm for anomaly detection. The performance of the final CAD system was evaluated using 19502 video clips (stomach 1907, small intestine 15494, large intestine 2101) from 20 testing videos. Each video clip consisted of 200 consecutive frame images, and neighboring clips have an overlap of 100 images. The average classification result of all frame images in a video clip was calculated for final determination of the location. Diagnostic performance is described as value [95% confidence interval].
RESULTS: The classification accuracies of video clips were 96.4% [95.4-97.2], 99.3% [99.2-99.4], and 99.8% [99.5-99.9] for stomach, small intestine, and colon, respectively, and the overall accuracy is 99.1% [98.9-99.2]. A detailed review of misdiagnosed video clips revealed that the stomach was misidentified as small intestine in 3.6% [2.8-4.6]; small intestine was misidentified as the stomach in 0.34% [0.26-0.45] and large intestine in 0.39% [0.30-0.50]; large intestine mucosa was misidentified as small intestine in 0.19% [0.05-0.49]. The misidentified video clips tended to have more residue and mucus in the lumen.
CONCLUSIONS: The CAD system developed here provides information to localize the capsule endoscope with high accuracy based on endoscopic images, warranting clinical implementation.

Kenichi Utano

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