Multimodal Convolutional Neural Network-Based Algorithm for Real-Time Detection and Differentiation of Malignant and Inflammatory Biliary Strictures in Cholangioscopy: a Proof of Concept Study with Video.

BACKGROUND AND AIMS: Deep learning algorithms gained attention for detection (CADe) of biliary tract cancer (BTC) in digital single-operator cholangioscopy (dSOC). We developed a multimodal convolutional neural network (CNN) for detection (CADe) characterization and discriminating (CADx) between malignant, inflammatory and normal biliary tissue in raw dSOC videos. In addition, clinical metadata was included in the CNN algorithm to overcome limitations of image-only models. METHODS: Based on dSOC videos and images of 111 patients (total of 15,158 still frames), we developed and validated a real-time CNN-based algorithm for CADe and CADx. We established an image-only model and metadata injection approach. In addition, we validated frame-wise and case-based predictions on complete dSOC video sequences. Model embeddings were visualized and class-activation maps highlighted relevant image regions. RESULTS: The concatenation-based CADx approach achieved a per-frame AUC of 0.871, sensitivity of 0.809 (95% CI: [0.784-0.832]), specificity of 0.773 [0.761-0.785], PPV of 0.450 [0.423-0.467], and NPV of 0.946 [0.940-0.954] with respect to malignancy on 5,715 test frames from complete videos of 20 patients. For case-based diagnosis using average prediction scores, six out of eight malignant cases and all twelve benign cases were identified correctly. CONCLUSION: Our algorithm distinguishes malignant and inflammatory bile duct lesions in dSOC videos, indicating the potential of CNN-based diagnostic support systems for both, CADe and CADx. The integration of non-image data can improve CNN based support systems, targeting current challenges in the assessment of biliary strictures.

[Therapeutic regimens using monoclonal antibodies in gastroenterology]. / Therapie mit monoklonalen Antikörpern in der Gastroenterologie.

Therapeutic regimens using monoclonal antibodies have been implemented in clinical daily practice for various gastroenterological diseases, for therapeutic strategies in gastrointestinal (GI) oncology, and infectious diseases of the gastrointestinal tract. The main indications remain the therapy of chronic inflammatory bowel disease and in GI oncology. A new field has opened for targeted therapy with monoclonal antibodies of recurrent Clostridium difficile infection. In the nomenclature of monoclonal antibodies, the endings of the substances indicate the production or degree of "humanization" of the respective antibodies ("umab": fully human, recombinant antibody; "ximab": chimeric antibody with variable murine domain). For chronic inflammatory bowel disease, monoclonal antibodies has been developed to interfere with molecular targets of the inflammatory cascade in the underlying pathogenesis (tumor necrosis factor­α, interleukin-12 and -23; α4ß7-integrins). The development of targeted therapies in the treatment of GI malignancies, monoclonal antibodies has been developed to interfere with substantial pathways of proliferation and apoptosis as well as neoplastic vascularization and neovascularization (e.g., vascular endothelial growth factor [VEGF] and VEGF receptor antibodies, epidermal growth factor receptor antibodies, HER2/neu antibodies). In the current review, we provide a summary of the current applications of monoclonal antibodies in the therapeutic treatment of gastroenterological diseases.