Abstract: Lumen-apposing shunt devices for transporting body fluid from a first compartment (e.g., peritoneal cavity) to a second compartment (e.g., bladder) comprise a longitudinal tube communicating between the two compartments and retention systems that separate apart and maintain each end of the tube within the respective compartment. The retention systems include double self-expandable wheels and double inflatable balloons enveloping the tube transversely, with one wheel or balloon in the first compartment and the other wheel or balloon in the second compartment. The self-expanded wheels or inflated balloons support and retain the shunt device between the compartments as fluid (e.g., ascites) from the first compartment flows into the second compartment in response to pressure gradients between the compartments. The shunt device contains a one-way valve mechanism to provide unidirectional flow of fluid from the first to the second compartment and to prevent reflux from the second to the first compartment.

Abstract: A method for treatment or prevention of diseases accompanying abnormal growth of a body organ or mass. Specifically, a method of manufacturing a capsule device to encase a body organ such as kidney, liver and ovary is provided. Abnormal growth of a body organ is slowed or halted by covering the body organ such as kidney, liver and ovary. The diseases associated with abnormal growth include, for example, polycystic kidney disease and polycystic liver disease.

Abstract: A method for the detection of target structures shown in digital medical images, the method of comprising: (1) generating a three dimensional (3D) volumetric data set of a patient region within which the target structure resides from a plurality of segmented medical image slices; (2) grouping contiguous structures that are depicted in the 3D volumetric data set to create corresponding grouped structure data sets; (3) assigning each grouped structure data set to one of a plurality of detection algorithms, each detection algorithm being configured to detect a different type of target structure; and (4) processing each grouped structure data set according to its assigned detection algorithm to thereby detect whether any target structures are present in the medical images. Preferably, the target structures are pulmonary nodules, and a specialized detection algorithm is applied to image data classified as a candidate for depicting perivascular nodules.