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.

Importance of Prenatal Diagnosis of Ileal Atresia in Gestational Diabetes Cases.

BACKGROUND Maldevelopment of the fetal bowel can result in the rare condition of intestinal atresia, which results in congenital bowel obstruction. This report describes a case of prenatal diagnosis of fetal ileal atresia at 22 weeks' gestation. CASE REPORT Here, we present a 24-year old woman who was 22 weeks into her first pregnancy when she underwent routine fetal ultrasound. She was diagnosed with gestational diabetes mellitus. Her body mass index was normal and she had normal weight gain. The ultrasonographic examination performed revealed a hyperechoic bowel and a small dilatation of the bowel. The couple was counselled for possible intestinal atresia and its postnatal implications. At 33 weeks of gestation, polyhydramnios appeared, and the intestinal distension was much more pronounced, with hyperechoic debris in the intestinal lumen (succus-entericus). After birth, surgery was performed and we concluded the patient had type II atresia, which was surgically treated. CONCLUSIONS This report has highlighted the importance of antenatal ultrasound in detecting fetal abnormalities, and has shown that rare conditions such as intestinal atresia can be accurately diagnosed and successfully managed. Surgical correction, if implemented promptly after stabilizing the general condition, can have a relatively good prognosis. Coexisting fetal ileal atresia and gestational diabetes mellitus are rare occurrences, which can make each condition even more difficult to treat.

CT and MR Enterography in the Evaluation of Celiac Disease.

Celiac disease is a common inflammatory disease of the small bowel that induces mucosal intestinal lesions. The disease is mediated by an immune response and triggered by the ingestion of gluten in genetically predisposed individuals. Gluten contains gliadin, a component found mostly in wheat, barley, and rye. This process leads to gastrointestinal malabsorption with symptoms such as diarrhea, constipation, abdominal pain, and distention. It has a prevalence of 1%-2% in the general adult population, who present with symptoms at any age, but is more frequently found in adult women in the 3rd or 4th decade of life. Recognition of the disease has increased, but it remains a challenge to diagnose. CT and MR enterography are noninvasive studies used for evaluation of small bowel neoplasms and inflammatory small bowel pathologic conditions such as celiac disease. The authors review the spectrum of intestinal and extraintestinal findings of celiac disease at CT and MR enterography, as well as its complications, and the importance of recognizing certain imaging features that help in the diagnosis of celiac disease. More common and specific findings of celiac disease such as inversion of the jejunoileal fold pattern and mesenteric lymphadenopathy are reviewed. More uncommon entities that are more frequently associated with refractory or untreated celiac disease, such as ulcerative jejunoileitis, cavitary mesenteric lymph node syndrome, and malignancies including small bowel adenocarcinoma and lymphoma, are described. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material. The slide presentation from the RSNA Annual Meeting is available for this article.

Reading of small bowel capsule endoscopy after frame reduction using an artificial intelligence algorithm.

OBJECTIVES: Poorly visualized images that appear during small bowel capsule endoscopy (SBCE) can confuse the interpretation of small bowel lesions and increase the physician's workload. Using a validated artificial intelligence (AI) algorithm that can evaluate the mucosal visualization, we aimed to assess whether SBCE reading after the removal of poorly visualized images could affect the diagnosis of SBCE. METHODS: A study was conducted to analyze 90 SBCE cases in which a small bowel examination was completed. Two experienced endoscopists alternately performed two types of readings. They used the AI algorithm to remove poorly visualized images for the frame reduction reading (AI user group) and conducted whole frame reading without AI (AI non-user group) for the same patient. A poorly visualized image was defined as an image with < 50% mucosal visualization. The study outcomes were diagnostic concordance and reading time between the two groups. The SBCE diagnosis was classified as Crohn's disease, bleeding, polyp, angiodysplasia, and nonspecific finding. RESULTS: The final SBCE diagnoses between the two groups showed statistically significant diagnostic concordance (k = 0.954, p < 0.001). The mean number of lesion images was 3008.5 ± 9964.9 in the AI non-user group and 1401.7 ± 4811.3 in the AI user group. There were no cases in which lesions were completely removed. Compared with the AI non-user group (120.9 min), the reading time was reduced by 35.6% in the AI user group (77.9 min). CONCLUSIONS: SBCE reading after reducing poorly visualized frames using the AI algorithm did not have a negative effect on the final diagnosis. SBCE reading method integrated with frame reduction and mucosal visualization evaluation will help improve AI-assisted SBCE interpretation.

Abdominal computed tomography scoring systems and experienced radiologists in the radiological diagnosis of small bowel and mesenteric injury.

PURPOSE: Blunt bowel and/or mesenteric injury requiring surgery presents a diagnostic challenge. Although computed tomography (CT) imaging is standard following blunt trauma, findings can be nonspecific. Most studies have focused on the diagnostic value of CT findings in identifying significant bowel and/or mesenteric injury (sBMI). Some studies have described scoring systems to assist with diagnosis. Little attention, has been given to radiologist interpretation of CT scans. This study compared the discriminative ability of scoring systems (BIPS and RAPTOR) with radiologist interpretation in identifying sBMI. METHODS: We conducted a retrospective chart review of trauma patients with suspected sBMI. CT images were reviewed in a blinded fashion to calculate BIPS and RAPTOR scores. Sensitivity and specificity were compared between BIPS, RAPTOR, and the admission CT report with respect to identifying sBMI. RESULTS: One hundred sixty-two patients were identified, 72 (44%) underwent laparotomy and 43 (26.5%) had sBMI. Sensitivity and specificity were: BIPS 49% and 87%, AUC 0.75 (0.67-0.81), P < 0.001; RAPTOR 46% and 82%, AUC 0.72 (0.64-0.79), P < 0.001; radiologist impression 81% and 71%, AUC 0.82(0.75-0.87), P < 0.001. The discriminative ability of the radiologist impression was higher than RAPTOR (P = 0.04) but not BIPS (P = 0.13). There was not a difference between RAPTOR vs. BIPS (P = 0.55). CONCLUSION: Radiologist interpretation of the admission CT scan was discriminative of sBMI. Although surgical vigilance, including evaluation of the CT images and patient, remains fundamental to early diagnosis, the radiologist's impression of the CT scan can be used in clinical practice to simplify the approach to patients with abdominal trauma.

Automatic detection of small bowel lesions with different bleeding risks based on deep learning models.

BACKGROUND: Deep learning provides an efficient automatic image recognition method for small bowel (SB) capsule endoscopy (CE) that can assist physicians in diagnosis. However, the existing deep learning models present some unresolved challenges. AIM: To propose a novel and effective classification and detection model to automatically identify various SB lesions and their bleeding risks, and label the lesions accurately so as to enhance the diagnostic efficiency of physicians and the ability to identify high-risk bleeding groups. METHODS: The proposed model represents a two-stage method that combined image classification with object detection. First, we utilized the improved ResNet-50 classification model to classify endoscopic images into SB lesion images, normal SB mucosa images, and invalid images. Then, the improved YOLO-V5 detection model was utilized to detect the type of lesion and its risk of bleeding, and the location of the lesion was marked. We constructed training and testing sets and compared model-assisted reading with physician reading. RESULTS: The accuracy of the model constructed in this study reached 98.96%, which was higher than the accuracy of other systems using only a single module. The sensitivity, specificity, and accuracy of the model-assisted reading detection of all images were 99.17%, 99.92%, and 99.86%, which were significantly higher than those of the endoscopists' diagnoses. The image processing time of the model was 48 ms/image, and the image processing time of the physicians was 0.40 ± 0.24 s/image (P < 0.001). CONCLUSION: The deep learning model of image classification combined with object detection exhibits a satisfactory diagnostic effect on a variety of SB lesions and their bleeding risks in CE images, which enhances the diagnostic efficiency of physicians and improves the ability of physicians to identify high-risk bleeding groups.

Prediction of bowel necrosis by reduced bowel wall enhancement in closed-loop small bowel obstruction: Quantitative methods.

PURPOSE: To assess diagnostic performance and reproducibility of reduced bowel wall enhancement evaluated by quantitative methods using CT to identify bowel necrosis among closed-loop small bowel obstruction (CL-SBO) patients. METHODS: This retrospective single-center study included patients who diagnosed with CL-SBO caused by adhesion or internal hernia during January 2016 and May 2022. Patients were divided into necrotic group (n = 41) and non-necrotic group (n = 67) according to surgical exploration and postoperative pathology. Two doctors independently measured the attenuation of bowel wall and consensus was reached through panel discussion with a third gastrointestinal radiologist. Reduced bowel wall enhancement was assessed by four quantitative methods. Univariate analyses were used to evaluate the association between each method and bowel necrosis, and kappa/intraclass correlation coefficient values were used to assess interobserver agreement. Diagnostic performance parameters were calculated for each method. RESULTS: Reduced bowel wall enhancement in arterial phase (OR 8.98, P < 0.0001), reduced bowel wall enhancement in portal phase (OR 16.84, P < 0.001), adjusted reduced bowel wall enhancement in arterial phase (OR 29.48, P < 0.001), adjusted reduced bowel wall enhancement in portal phase (OR 145.69, P < 0.001) were significantly associated with bowel necrosis. Adjusted reduced bowel wall enhancement in portal phase had the best diagnostic performance (AUC: 0.92; Youden index: 0.84; specificity: 94.03 %) and interobserver agreement (kappa value of 0.59-0.73) to predict bowel necrosis. CONCLUSION: When assessing reduced bowel enhancement to predict bowel necrosis among CL-SBO patients, using unenhanced CT images and proximal dilated loop as standard references in portal phase is the most accurate quantitative method among those tested.

Automated classification of ulcerative lesions in small intestine using densenet with channel attention and residual dilated blocks.

Objective. Ulceration of the small intestine, which has a high incidence, includes Crohn's disease (CD), intestinal tuberculosis (ITB), primary small intestinal lymphoma (PSIL), cryptogenic multifocal ulcerous stenosing enteritis (CMUSE), and non-specific ulcer (NSU). However, the ulceration morphology can easily be misdiagnosed through enteroscopy.Approach. In this study, DRCA-DenseNet169, which is based on DenseNet169, with residual dilated blocks and a channel attention block, is proposed to identify CD, ITB, PSIL, CMUSE, and NSU intelligently. In addition, a novel loss function that incorporates dynamic weights is designed to enhance the precision of imbalanced datasets with limited samples. DRCA-Densenet169 was evaluated using 10883 enteroscopy images, including 5375 ulcer images and 5508 normal images, which were obtained from the Shanghai Changhai Hospital.Main results. DRCA-Densenet169 achieved an overall accuracy of 85.27% ± 0.32%, a weighted-precision of 83.99% ± 2.47%, a weighted-recall of 84.36% ± 0.88% and a weighted-F1-score of 84.07% ± 2.14%.Significance. The results demonstrate that DRCA-Densenet169 has high recognition accuracy and strong robustness in identifying different types of ulcers when obtaining immediate and preliminary diagnoses.

A newly developed deep learning-based system for automatic detection and classification of small bowel lesions during double-balloon enteroscopy examination.

BACKGROUND: Double-balloon enteroscopy (DBE) is a standard method for diagnosing and treating small bowel disease. However, DBE may yield false-negative results due to oversight or inexperience. We aim to develop a computer-aided diagnostic (CAD) system for the automatic detection and classification of small bowel abnormalities in DBE. DESIGN AND METHODS: A total of 5201 images were collected from Renmin Hospital of Wuhan University to construct a detection model for localizing lesions during DBE, and 3021 images were collected to construct a classification model for classifying lesions into four classes, protruding lesion, diverticulum, erosion & ulcer and angioectasia. The performance of the two models was evaluated using 1318 normal images and 915 abnormal images and 65 videos from independent patients and then compared with that of 8 endoscopists. The standard answer was the expert consensus. RESULTS: For the image test set, the detection model achieved a sensitivity of 92% (843/915) and an area under the curve (AUC) of 0.947, and the classification model achieved an accuracy of 86%. For the video test set, the accuracy of the system was significantly better than that of the endoscopists (85% vs. 77 ± 6%, p < 0.01). For the video test set, the proposed system was superior to novices and comparable to experts. CONCLUSIONS: We established a real-time CAD system for detecting and classifying small bowel lesions in DBE with favourable performance. ENDOANGEL-DBE has the potential to help endoscopists, especially novices, in clinical practice and may reduce the miss rate of small bowel lesions.

Primary small intestine angiosarcoma mimicking Crohn's disease.

A man in his 40s presented to an emergency department after experiencing worsening abdominal pain for 2 days. Contrast-enhanced CT of the abdomen and pelvis revealed circumferential mural thickening and luminal narrowing of the distal ileum and upstream dilatation of the small intestine, indicating small intestine obstruction. This prompted emergency laparotomy, where two lesions in the distal ileum were identified as the source of his bowel obstruction and resected. Immunohistochemistry of the resected segment revealed a primary small intestine angiosarcoma acting positively for vascular markers ERG and CD31. A subsequent positron emission tomography (PET) scan revealed positive mediastinal metastatic lymphadenopathy without organ metastases.Following his surgery, the patient recovered well and was promptly referred to an oncology unit at a specialised health centre for further treatment. Primary small intestine angiosarcoma is a rare entity in which patients present with non-specific symptoms requiring prompt tissue diagnosis to facilitate multidisciplinary management.

Device-assisted enteroscopy performance measures in the United Kingdom: DEEP-UK quality improvement project.

BACKGROUND: Device-assisted enteroscopy (DAE) has become a well-established diagnostic and therapeutic tool for the management of small-bowel pathology. We aimed to evaluate the performance measures for DAE across the UK against the quality benchmarks proposed by the European Society of Gastrointestinal Endoscopy (ESGE). METHODS: We retrospectively collected data on patient demographics and DAE performance measures from electronic endoscopy records of consecutive patients who underwent DAE for diagnostic and therapeutic purposes across 12 enteroscopy centers in the UK between January 2017 and December 2022. RESULTS: A total of 2005 DAE procedures were performed in 1663 patients (median age 60 years; 53% men). Almost all procedures (98.1%) were performed for appropriate indications. Double-balloon enteroscopy was used for most procedures (82.0%), followed by single-balloon enteroscopy (17.2%) and spiral enteroscopy (0.7%). The estimated depth of insertion was documented in 73.4% of procedures. The overall diagnostic yield was 70.0%. Therapeutic interventions were performed in 42.6% of procedures, with a success rate of 96.6%. Overall, 78.0% of detected lesions were marked with a tattoo. Patient comfort was significantly better with the use of deep sedation compared with conscious sedation (99.7% vs. 68.5%; P<0.001). Major adverse events occurred in only 0.6% of procedures. CONCLUSIONS: Performance measures for DAE in the UK meet the ESGE quality benchmarks, with high diagnostic and therapeutic yields, and a low incidence of major adverse events. However, there is room for improvement in optimizing sedation practices, standardizing the depth of insertion documentation, and adopting marking techniques to aid in the follow-up of detected lesions.

Cross-sectional imaging: current status and future potential in adult celiac disease.

Celiac disease (CD), triggered by exposure to gluten in genetically susceptible individuals, is an immune-mediated small bowel disease affecting about 1% of the population worldwide. But the prevalence of CD varies with age, sex, and location. A strict gluten-free diet remains the primary treatment for CD, currently. Most of patients with CD respond well to gluten-free diet with good prognosis, while some patients fail to get symptomatic relief or histological remission (e.g., nonresponsive or refractory CD). Because of heterogeneous clinical appearance, the diagnosis of CD is difficult. Moreover, malignant complications and poor outcomes accompanied with refractory CD present great challenges in disease management. Over the past three decades, cross-sectional imaging techniques (computed tomography [CT] and magnetic resonance imaging [MRI]) play an important role in small bowel inflammatory and neoplastic diseases. Compared with endoscopic techniques, cross-sectional imaging permits clearly presentation of both intraluminal and extraluminal abnormalities. It provides vascular and functional information, thus improving the possibility as diagnostic and follow-up tool. The value of cross-sectional imaging for patients with suspected or confirmed CD has been gradually demonstrated. Studies revealed that certain features suggested by cross-sectional imaging could help to establish the early diagnosis of CD. Besides, the potential contributions of cross-sectional imaging may lie in the evaluation of disease activity and severity, which helps guiding management strategies. The purpose of this review is to provide current overviews and future directions of cross-sectional imaging in adult CD, thus facilitating the understanding and application in clinical practice. CLINICAL RELEVANCE STATEMENT: In this review, we systematically summarized the existing knowledge of cross-sectional imaging in adult CD and analyzed their possible roles in clinical practice, including disease diagnosis, complication identification, treatment evaluation, and prognostic prediction. KEY POINTS: • Regarding a condition described as "celiac iceberg", celiac disease remains underdiagnosed and undertreated. • Cross-sectional imaging is helpful in clinical management of celiac disease, including disease diagnosis, complication identification, treatment evaluation, and prognostic prediction. • Cross-sectional imaging should be considered as the valuable examination in patients suspected from celiac disease.

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.