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US 11,894,141 B2Granted
Network for medical image analysis, decision support system, and related graphical user interface (GUI) applications
AssigneeProgenics Pharmaceuticals, Inc.
InventorMark R. Baker
Life of this patent
Estimating the term…
Abstract
Described herein is a platform and supported graphical user interface (GUI) decision-making tools for use by medical practitioners and/or their patients, e.g., to aide in the process of making decisions about a course of cancer treatment and/or to track treatment and/or the progress of a disease.
Claims35
A network-based decision support system comprising:
- a processor;
- and
- a memory having instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to:
- (i) receive and store a plurality of medical images in a database, each medical image associated with a corresponding patient;
- (ii) access one or more of the medical images associated with a particular patient from the database;
- (iii) automatically analyze the one or more medical images using a machine learning algorithm;
- and
- (iv) generate 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 obtained 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 instructions cause the processor to automatically analyze 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 the system is a cloud-based system.
9 more elements
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, said processor a processor of a cloud-based system, 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.
6 more elements
A method for tracking prostate cancer progression and treatment efficacy over time, for one or more patient(s), the method comprising:
- (a) repeatedly receiving and storing in a database, over time, by a processor of a computing device, said processor a processor of a cloud-based system, a plurality of medical images for each of the one or more patient(s) to obtain, for each of the one or more patient(s), a series of medical images taken over time;
- (b) for each of the one or more patient(s), automatically analyzing, by the processor, using a machine learning algorithm, the series of medical images for the patient to determine values of one or more risk indices for each medical image of the series, thereby tracking determined values of the one or more risk indices over a course prostate cancer progression and treatment for the patient;
- and
- (c) for each of the one or more patient(s), storing, by the processor, the determined values of the one or more risk indices, each indicative of prostate cancer state or progression, for the patient for further processing and/or causing, by the processor, display of a graphical representation of the determined values of the one or more risk indices for the patient,
- wherein the series of medical images for a particular patient of the one or more patient(s) comprises 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, and wherein step (b) comprises:
- 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
- computing the value of each of the one or more risk indices using the nuclear medicine image with the identified 3D boundary(ies) of the one or more region(s).
5 more elements
A system for tracking prostate cancer progression and treatment efficacy over time, for one or more patient(s), the system comprising:
- a processor;
- and
- a memory having instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to:
- (a) repeatedly receive and store in a database, over time, a plurality of medical images for each of the one or more patient(s) to obtain, for each of the one or more patient(s), a series of medical images taken over time;
- (b) for each of the one or more patient(s), automatically analyze the series of medical images for the patient, using a machine learning algorithm, to determine values of one or more risk indices for each medical image of the series, thereby tracking determined values of the one or more risk indices over a course prostate cancer progression and treatment for the patient;
- and
- (c) for each of the one or more patient(s), store the determined values of the one or more risk indices, each indicative of prostate cancer state or progression, for the patient for further processing and/or cause display of a graphical representation of the determined values of the one or more risk indices for the patient
- wherein the series of medical images for a particular patient of the one or more patient(s) comprises 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, and wherein step (b) comprises:
- 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
- computing the value of each of the one or more risk indices using the nuclear medicine image with the identified 3D boundary(ies) of the one or more region(s), and
- wherein the system is a cloud-based system.
9 more elements
A network-based decision support system comprising:
- a processor;
- and
- a memory having instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to:
- (i) receive and store a plurality of medical images in a database, each medical image associated with a corresponding patient;
- (ii) access one or more of the medical images associated with a particular patient from the database;
- (iii) automatically analyze the one or more medical images using a machine learning algorithm;
- and
- (iv) generate 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 obtained 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 instructions cause the processor to automatically analyze 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 the plurality of medical images in the database comprise a series of medical images of a first patient taken over time, and wherein the instructions cause the processor to determine a value of at least a first risk index for each medical image of the series, thereby tracking determined values of at least the first risk index for the first patient over time.
10 more elements
A network-based decision support system comprising:
- a processor;
- and
- a memory having instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to:
- (i) receive and store a plurality of medical images in a database, each medical image associated with a corresponding patient;
- (ii) access one or more of the medical images associated with a particular patient from the database;
- (iii) automatically analyze the one or more medical images using a machine learning algorithm;
- And
- (iv) generate 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 obtained 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 instructions cause the processor to automatically analyze 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 instructions cause the processor to compute 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 particular risk index based on the determined cancerous tissue levels within the one or more regions.
13 more elements
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 the plurality of medical images in the database comprise a series of medical images of a first patient taken over time, and wherein the instructions cause the processor to determine a value of at least a first risk index for each medical image of the series, thereby tracking determined values of at least the first risk index for the first patient over time.
7 more elements
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.
10 more elements
Dependencies are inferred from the claim text.