Network for medical image analysis, decision support system, and related graphical user interface (GUI) applications
Inventors
Assignees
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Publication Number
US-10665346-B2
Publication Date
2020-05-26
Expiration Date
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.
Core Innovation
The invention is a network-based system for generating a disease risk map as decision-making support for evaluating risk of cancer or risk of recurrence of cancer. The system includes a processor and a memory with instructions for accessing one or more medical images associated with a particular patient from a database and analyzing the medical images using a machine learning algorithm to generate the risk map.
The risk map comprises a visual representation of tissue overlaid with graphical denotations marking one or more regions of risk of cancer or risk of recurrence of cancer. The analysis comprises creation of a 3D image of the one or more regions of risk overlaid on the one or more medical images, and the 3D image comprises geographic identification of one or more specific tissue region(s).
The disclosed subject matter further describes radiolabeled PSMA/MDP/MIP imaging agents that include a metal radioisotope substitution, including technetium-99m and alternative metal radioisotopes. The disclosed subject matter also describes computation of a whole-body bone scan index (BSI) and analysis of composite PET/CT and SPECT/CT images, including overlaying the composite images, segmenting the images into anatomical and skeletal regions, and analyzing detected hotspots to derive cancer risk indices.
The disclosed subject matter also describes a cloud-based decision support system for generating reports and tracking risk indices across repeated patient visits. The system is described as using a microservice-based architecture with a graphical user interface (GUI) and reporting for BSI and risk indices, supporting a radiologist report.
Claims Coverage
The partial claims content provided includes one independent claim. The independent claim contains three main inventive contributions: network-based access to patient medical images and machine learning analysis to generate a cancer risk map, a specific risk-map visualization with tissue and graphical denotations of risk regions, and construction of a 3D overlay with geographic identification of specific tissue regions, followed by GUI display for user presentation or review.
Network-based system for generating a disease risk map for decision-making support
A network-based system comprising a processor and memory that access one or more medical images associated with a particular patient from a database and perform analysis of the medical images using a machine learning algorithm to generate a risk map for use as decision-making support for evaluating risk of cancer or risk of recurrence of cancer.
3D tissue overlay with graphical denotations of risk regions
The risk map comprises a visual representation of tissue overlaid with graphical denotations marking one or more regions of risk of cancer or risk of recurrence of cancer, and the analysis comprises creation of a 3D image of the one or more regions overlaid on the one or more medical images.
Geographic identification and GUI display of the risk map
The 3D image comprises geographic identification of one or more specific tissue region(s) overlaid on the one or more medical images, and the system causes display of the risk map via a graphical user interface (GUI) for presentation or review of the risk map by a user.
Across the independent claim, the core inventive coverage centers on generating a cancer risk map via machine learning applied to patient medical images accessed from a database, producing a tissue-based visualization with graphical denotations, creating a 3D overlay with geographic identification of specific tissue regions, and presenting the resulting risk map through a GUI.
Stated Advantages
Decision support for cancer treatment decision-making and disease tracking.
Automated analysis of targeted nuclear medicine images, including PET/SPECT and composite CT overlays.
Generates risk indices and maps, including 3D tissue overlays with graphical risk denotations.
Produces radiologist reports.
Documented Applications
Evaluating risk of cancer or risk of recurrence of cancer.
Cancer treatment decision-making.
Disease tracking.
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