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Background: Capsule endoscopy (CE) is a valuable tool for assessing inflammation in patients with Crohn's disease (CD). The current standard for evaluating inflammation are validated scores (and clinical laboratory values) like Lewis score (LS), Capsule Endoscopy Crohn's Disease Activity Index (CECDAI), and ELIAKIM. Recent advances in artificial intelligence (AI) have made it possible to automatically select the most relevant frames in CE. Objectives: In this proof-of-concept study, our objective was to develop an automated scoring system using CE images to objectively grade inflammation. Design: Pan-enteric CE videos (PillCam Crohn's) performed in CD patients between 09/2020 and 01/2023 were retrospectively reviewed and LS, CECDAI, and ELIAKIM scores were calculated. Methods: We developed a convolutional neural network-based automated score consisting of the percentage of positive frames selected by the algorithm (for small bowel and colon separately). We correlated clinical data and the validated scores with the artificial intelligence-generated score (AIS). Results: A total of 61 patients were included. The median LS was 225 (0–6006), CECDAI was 6 (0–33), ELIAKIM was 4 (0–38), and SB_AIS was 0.5659 (0–29.45). We found a strong correlation between SB_AIS and LS, CECDAI, and ELIAKIM scores (Spearman's r = 0.751, r = 0.707, r = 0.655, p = 0.001). We found a strong correlation between LS and ELIAKIM (r = 0.768, p = 0.001) and a very strong correlation between CECDAI and LS (r = 0.854, p = 0.001) and CECDAI and ELIAKIM scores (r = 0.827, p = 0.001). Conclusion: Our study showed that the AI-generated score had a strong correlation with validated scores indicating that it could serve as an objective and efficient method for evaluating inflammation in CD patients. As a preliminary study, our findings provide a promising basis for future refining of a CE score that may accurately correlate with prognostic factors and aid in the management and treatment of CD patients. Plain language summary: Artificial intelligence in Crohn's disease: the development of an automated score for disease activity evaluation This study introduces an innovative AI-based approach to evaluate Crohn's Disease. The AI system automatically analyzes images from capsule endoscopy, focusing on finding ulcers and erosions to measure disease activity. The research reveals a robust correlation between the AI-generated score assessing inflammation in the small bowel and traditional clinical scores. This suggests that the AI solution could be a quicker and more consistent way to evaluate Crohn's Disease, speeding up the evaluation process and reducing manual scoring variability. While promising, the study acknowledges limitations and emphasizes the need for further validation with larger groups of patients. Overall, it represents a crucial step toward integrating AI into gastroenterology, offering a glimpse into a future of more objective and personalized Crohn's Disease evaluation. [ABSTRACT FROM AUTHOR]

Background Inflammatory bowel disease (IBD) may be associated with a wide range of hepatobiliary manifestations. This study aimed to characterize the spectrum of hepatobiliary disorders in patients with IBD who underwent liver biopsy for sustained abnormal liver function tests (LFT). Method A retrospective study was performed of all patients with IBD who underwent liver biopsy between January 2010 and December 2020 for sustained abnormal LFT (at least 6-month duration). Results A total of 101 patients were included, mostly male (62.4%), with a mean age of 44.4±13.3 years. The most common IBD type was Crohn's disease (61.4%). Median time interval between abnormal LFT and biopsy was 14 (7-36) months. Abnormal LFT was predominantly hepatocellular in 40 patients (39.6%), cholestatic in 26 (25.7%) and mixed in 35 (34.7%). The most frequent diseases were nonalcoholic fatty liver disease (NAFLD) in 33 patients (32.7%), drug-induced liver disease (DILI) in 30 (29.7%), autoimmune hepatitis (AIH) in 13 (12.9%) and primary sclerosing cholangitis (PSC) in 13 (12.9%). Three patients had primary biliary cholangitis. Remarkably, 70 patients (69.3%) already had fibrosis by the time of liver biopsy and in 6 (5.9%) liver disease was already detected in the stage of cirrhosis. Conclusions Abnormal LFT in IBD patients had a wide range of etiologies and histology was often essential for reaching a correct diagnosis. NAFLD, DILI, AIH and PSC were the most common diagnoses and patients often presented in cirrhotic stage. Therefore, liver biopsy must be considered early in IBD patients with unexplained sustained abnormal LFT. [ABSTRACT FROM AUTHOR]

Background and Objectives: Device-assisted enteroscopy (DAE) has a significant role in approaching enteric lesions. Endoscopic observation of ulcers or erosions is frequent and can be associated with many nosological entities, namely Crohn's disease. Although the application of artificial intelligence (AI) is growing exponentially in various imaged-based gastroenterology procedures, there is still a lack of evidence of the AI technical feasibility and clinical applicability of DAE. This study aimed to develop and test a multi-brand convolutional neural network (CNN)-based algorithm for automatically detecting ulcers and erosions in DAE. Materials and Methods: A unicentric retrospective study was conducted for the development of a CNN, based on a total of 250 DAE exams. A total of 6772 images were used, of which 678 were considered ulcers or erosions after double-validation. Data were divided into a training and a validation set, the latter being used for the performance assessment of the model. Our primary outcome measures were sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), and an area under the curve precision–recall curve (AUC-PR). Results: Sensitivity, specificity, PPV, and NPV were respectively 88.5%, 99.7%, 96.4%, and 98.9%. The algorithm's accuracy was 98.7%. The AUC-PR was 1.00. The CNN processed 293.6 frames per second, enabling AI live application in a real-life clinical setting in DAE. Conclusion: To the best of our knowledge, this is the first study regarding the automatic multi-brand panendoscopic detection of ulcers and erosions throughout the digestive tract during DAE, overcoming a relevant interoperability challenge. Our results highlight that using a CNN to detect this type of lesion is associated with high overall accuracy. The development of binary CNN for automatically detecting clinically relevant endoscopic findings and assessing endoscopic inflammatory activity are relevant steps toward AI application in digestive endoscopy, particularly for panendoscopic evaluation. [ABSTRACT FROM AUTHOR]

Leukocytoclastic vasculitis is a single-organ, skin-isolated small vessel vasculitis. It can be a side effect of many common drugs, including biological agents. Unlike with other drugs, leukocytoclastic vasculitis induced by biological agents may have a prolonged latency period. We report the first case of ustekinumab-induced leukocytoclastic vasculitis in a patient with inflammatory bowel disease. [ABSTRACT FROM AUTHOR]

Abstract: Immunosuppressive treatments used in the management of Inflammatory Bowel Disease, namely steroids, thiopurines and anti-TNF drugs, raise the risk of acquiring opportunistic infections. However, most of these infections are mild and self-limited, not requiring specific therapy or suspension of the immunosuppressors. We report a case of disseminated cutaneous herpes simplex infection in a patient with Crohn's disease under steroids and azathioprine. [Copyright &y& Elsevier]

A response from the authors of the article "Is It Possible to Change Phenotype Progression in Crohn's Disease in the Era of Immunomodulators? Predictive Factors of Phenotype Progression" published in the journal in 2014 is presented.

A response from authors of the article "Is it possible to change phenotype progression in Crohn's disease in the era of immuno-modulators? Predictive factors of phenotype progression" in a 2014 issue is presented.

Background: The treatment goal of Crohn's disease (CD) has moved towards achieving mucosal healing, resolution of transmural inflammation, and normalization of biomarkers. The purpose of this study was to evaluate how well computed tomography enterography (CTE) and fecal calprotectin (FC) correlated with endoscopic activity in newly diagnosed patients with CD and after 1 year of therapy. Methods: Consecutive patients with newly diagnosed CD were evaluated by endoscopy, CTE, and FC at diagnosis and 12 months after beginning immunosuppression. Endoscopic severity was assessed using the Simplified Endoscopic Score for Crohn's Disease (SES-CD). Biomarkers, clinical indexes, and FC were recorded on the day of ileocolonoscopy at diagnosis and 1 year after diagnosis. We adapted a CTE score for disease activity based on radiological signs of inflammation (i.e. mural thickness, mural hyperenhancement, mesenteric fat proliferation, mesenteric fat densification, comb sign, presence of strictures, fistulas, abscesses, ascites, and lymphadenopathy). Correlations between endoscopy, CTE, and FC were assessed using Spearman's rank correlation. Results: A total of 29 patients (48% women; median age 30 (24.5–35.5) years) were included in this prospective cohort. CTE findings significantly correlated with endoscopic findings. Endoscopic remission (ER) at 1-year follow up significantly correlated with improvement in mural hyperenhancement (p = 0.004), mesenteric fat densification (p = 0.001), comb sign (p = 0.004), and strictures (p = 0.008) in CTE. None of the CTE findings improved in patients without ER. FC correlated with SES-CD (rs = 0.696, p < 0.001) and with CTE features of inflammation (rs = 0.596, p < 0.001). A cut-off of 100 µg/g predicted ER with 92% sensitivity, 65% specificity, and 83% accuracy (area under curve 0.878, p < 0.001). Conclusions: CTE findings and FC levels correlated with endoscopic activity in CD both at diagnosis and at 1-year follow up. These two noninvasive markers of disease activity may be used as an alternative to endoscopy to monitor disease response to therapy. [ABSTRACT FROM AUTHOR]