Patent ID: 11894141
Assignee: PROGENICS PHARMACEUTICALS, INC.
Field: Measurement (Instruments)
Classification: CPC G | IPC G

Claim 34:
35. A method comprising performing, by a processor of a server computing device, (i) to (iv) as follows:
(i) receiving and storing, by the processor of a server computing device, a plurality of medical images in a database, each medical image associated with a particular corresponding patient;
(ii) accessing, by the processor, one or more of the medical images associated with a particular patient from the database;
(iii) automatically analyzing, by the processor, the one or more medical images using a machine learning algorithm; and
(iv) generating, by the processor, a radiologist report for the particular patient according to the one or more medical images for the patient,
wherein the one or more medical images comprise a composite image of the particular patient, the composite image comprising a CT scan overlaid with a nuclear medicine image acquired at a substantially same time as the CT scan and following administration to the patient of an imaging agent comprising a Prostate Specific Membrane Antigen (PSMA) binding agent comprising a radionuclide, wherein the method comprises automatically analyzing the composite image by:
(a) using the composite image to geographically identify a 3D boundary for each of one or more regions of imaged tissue within the nuclear medicine image; and
(b) computing, using the nuclear medicine image with the identified 3D boundary(ies) of the one or more region(s), a value of each of one or more risk indices, each risk index value indicative of cancer state or progression in the patient, and
wherein, for at least one particular risk index of the one or more risk indices, the method comprises computing, by the processor, the value of the particular risk index by:
determining, for each of the one or more regions, a corresponding cancerous tissue level within the region based on intensity values of the nuclear medicine image within the 3D boundary of the region; and
computing the value of the risk index based on the determined cancerous tissue levels within the one or more regions.