3 results about "Heterotaxy" patented technology

The invention relates to a device for distributing and receiving a population of pancreatic islets heterogeneous in size, the device comprising a matrix having a first face opposite a second face, characterized in that the matrix comprises concentric channels centered on a center O, the channels have an opening for receiving the pancreatic cells, the opening leading out onto the first face, the opening extending over the entire length (L) of the channel, the opening having a width (I) taken along the section Si, the device being configured such that the widths of the opening of two adjacent channels have an equal or increasing value moving away from the center O and such that the widths of the opening of a channel closest to the center O and of a channel furthest from the center O have an increasing value moving away from the center O. The invention relates to the field of implantable devices, in particular artificial pancreas devices.

A beam angle optimization method for particle therapy comprises: receiving, by an analysis apparatus, distance information from a patient's body surface to a tumor, internal heterogeneity information, internal transmission information of a particle beam, and internal motion information according to the patient's respiration; inputting, by the analysis apparatus, the distance information from the patient's body surface to the tumor, the internal heterogeneity information, the internal transmission information of the particle beam, and the internal motion information according to the patient's respiration into a deep learning model; and calculating, by the analysis apparatus, a particle therapy beam angle based on an output value of the deep learning model.

This invention relates to a method and medium for quantifying biomechanical heterogeneity and predicting prognosis in hepatocellular carcinoma (HCC) based on a multi-scale mechanical interaction network. The method includes: retrieving the shear modulus and loss angle parameter maps of the tumor based on multi-frequency magnetic resonance elastography data; dividing the tumor into multiple biomechanical regions using mechanical gradient-driven adaptive clustering; constructing an intratumoral mechanical interaction network and extracting its topological features; constructing a multi-organ mechanical coupling model of the tumor, liver, and spleen, and calculating the cross-organ stress transfer efficiency as a coupling feature; fusing intratumoral network features and cross-organ coupling features to form a multi-scale biomechanical phenotypic vector, and inputting it into a machine learning model in conjunction with clinical features to achieve individualized and accurate prediction of postoperative recurrence risk in HCC patients. Compared with existing technologies, this invention provides a novel systemic biomechanical perspective for prognostic assessment by quantifying the intratumoral mechanical heterogeneity and its mechanical interaction with host organs.