Various embodiments disclosed relate to drug-coated balloon catheters for treating, preventing, or reducing the recurrence of a stricture and/or cancer, or for treating benign prostatic hyperplasia (BPH), in a non-vascular body lumen and methods of using the same. A drug-coated balloon catheter for delivering a therapeutic agent to a target site of a body lumen stricture includes an elongated balloon having a main diameter. The balloon catheter includes a coating layer overlying an exterior surface of the balloon. The coating layer includes one or more water-soluble additives and an initial drug load of a therapeutic agent. In some embodiments, the balloon catheter includes a length-control mechanism which stretches and elongates the balloon when it is in a deflated state, giving the balloon a smaller cross-sectional deflated profile for tracking through the body lumen and for removal after treatment.

The application relates to devices and methods for analysing a colonoscopy video or a portion thereof, and for assessing the severity of ulcerative colitis in a subject by analysing a colonoscopy video obtained from the subject. Analysing a colonoscopy video comprises using a first deep neural network classifier to classify image data from the subject colonoscopy video or portion thereof into at least a first severity class (more severe endoscopic lesions) and a second severity class (less severe endoscopic lesions), wherein the first deep neural network has been trained at least in part in a weakly supervised manner using training image data from a plurality of training colonoscopy videos, the training image data comprising multiple sets of consecutive frames from the plurality of training colonoscopy videos, wherein frames in a set have the same severity class label. Devices and methods for providing a tool for analysing colonoscopy videos are also described.

The application relates to devices and methods for analysing a colonoscopy video or a portion thereof, and for assessing the severity of ulcerative colitis in a subject by analysing a colonoscopy video obtained from the subject. Analysing a colonoscopy video comprises using a first deep neural network classifier to classify image data from the subject colonoscopy video or portion thereof into at least a first severity class (more severe endoscopic lesions) and a second severity class (less severe endoscopic lesions), wherein the first deep neural network has been trained at least in part in a weakly supervised manner using training image data from a plurality of training colonoscopy videos, the training image data comprising multiple sets of consecutive frames from the plurality of training colonoscopy videos, wherein frames in a set have the same severity class label. Devices and methods for providing a tool for analysing colonoscopy videos are also described.

A method of applying pressure and support to a patient's abdomen during an endoscopy procedure including applying a primary wrap comprising a band of elastic material to an abdomen of a patient and maintaining tension in the band in order to apply constant pressure and the support to the patient's abdomen through a contraction of the primary wrap in connection with an advancement or a withdrawal of an endoscope during an enteroscopy procedure. The method includes adjusting at least one of the primary wrap or at least one secondary strap extending from the primary wrap to adjust compression and support the advancement or the withdrawal of the endoscope through the contraction of the primary wrap and the at least one secondary strap.

A method of applying pressure and support to a patient's abdomen during an endoscopy procedure including applying a primary wrap comprising a band of elastic material to an abdomen of a patient and maintaining tension in the band in order to apply constant pressure and the support to the patient's abdomen through a contraction of the primary wrap in connection with an advancement or a withdrawal of an endoscope during an enteroscopy procedure. The method includes adjusting at least one of the primary wrap or at least one secondary strap extending from the primary wrap to adjust compression and support the advancement or the withdrawal of the endoscope through the contraction of the primary wrap and the at least one secondary strap.

A hollow probe enabling insertion and accommodation of endoscopic and other instruments advancing within a lumen includes a central valve unit featuring a central bore and at least one valve for controlling the introduction and withdrawal of fluid into the central bore. A sliding tubular sheath is movably disposed inside the central valve unit. An impermeable flexible sleeve is sealingly anchored to the central valve unit and folds over to cover both the inside and outside of the sheath to sealingly envelop the sheath and contain the fluid, together with the valve unit, while allowing sliding of the sleeve-covered-sheath. An endoscope adapter is mountable to the proximal end of the sleeve-covered-sheath, for allowing insertion of the endoscope through the adapter into the sleeve-covered-sheath, includes at least one gasket for sealing at least one gap between the endoscope and the sleeve-covered-sheath for withholding fluids from escaping.

A hollow probe enabling insertion and accommodation of endoscopic and other instruments advancing within a lumen includes a central valve unit featuring a central bore and at least one valve for controlling the introduction and withdrawal of fluid into the central bore. A sliding tubular sheath is movably disposed inside the central valve unit. An impermeable flexible sleeve is sealingly anchored to the central valve unit and folds over to cover both the inside and outside of the sheath to sealingly envelop the sheath and contain the fluid, together with the valve unit, while allowing sliding of the sleeve-covered-sheath. An endoscope adapter is mountable to the proximal end of the sleeve-covered-sheath, for allowing insertion of the endoscope through the adapter into the sleeve-covered-sheath, includes at least one gasket for sealing at least one gap between the endoscope and the sleeve-covered-sheath for withholding fluids from escaping.

There is provided a method, comprising: feeding 2D image(s) of an internal surface of a colon captured by an endoscopic camera, into a machine learning model, wherein the 2D image(s) excludes a depiction of an external measurement tool, wherein the machine learning model is trained on records, each including 2D images of the internal surface of the colon of a respective subject labelled with ground truth labels of respective bounding boxes enclosing respective polyps and at least one of an indication of size and a type of the respective polyp indicating likelihood of developing maligiancy, obtaining a bounding box for a polyp and at least one of an indication of size and type of the polyp, and generating instructions for presenting within the GUI, an overlay of the bounding box over the polyp and the at least one of the indication of size and type of the polyp.

A colon cleanliness indicating device including a forward toilet-secured receiving section configured with a recessed receptacle for receiving colonic effluent and a rearward indicating section for indicating a degree of colon cleanliness. The indicating section is formed with one or more channels in fluid communication with the receptacle through which the received colonic effluent is flowable and by which the received colonic effluent can be visualized in order to assess a degree of colon cleanliness.

A force estimation system for calculating force information regarding forces applied to one or more positions of a flexible tubular portion having flexibility through an arithmetic operation, the force estimation system comprising: a processor configured to input the deformation state and the mechanical property at a plurality of longitudinal positions of the flexible tubular portion, and calculates the force information of the force applied to the individual positions of the flexible tubular portion based on the deformed state and the mechanical property.