Cloud-Based Medical Image Analysis With 3D Risk Maps
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Solution Overview
Problem
The existing process for medical imaging in cancer diagnosis and treatment decision-making relies heavily on radiologist reports, which may be difficult for physicians to interpret and communicate effectively to patients, leading to misinformed decisions and increased patient trauma.
Innovation Solution
A cloud-based platform with a graphical user interface (GUI) that supports automated analysis of PET/SPECT images, generates radiologist reports, and allows for machine learning-enhanced decision-making, providing patients with interactive 3D risk maps for clearer understanding of their condition and treatment options.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If radiologist reports are used for medical image analysis, then professional medical assessment is provided, but the reports are difficult for physicians and patients to interpret and understand
Solution Approach 1:
The patent creates simplified visual copies of complex medical imaging data. Instead of presenting raw radiologist reports or complex imaging data, the system generates simplified visual representations such as color-coded risk maps, 3D anatomical models with highlighted regions, and graphical summaries that replicate the essential diagnostic information in an easily interpretable format for physicians and patients
Solution Approach 2:
The patent employs color coding to represent different levels of disease risk, tissue characteristics, and diagnostic findings. By mapping complex radiological data to intuitive color scales (e.g., red for high risk, green for low risk), the system transforms difficult-to-interpret medical images into visually accessible information while preserving diagnostic precision
2Loss of information
If detailed radiologist reports are generated, then comprehensive medical assessment is provided, but effective communication to patients is hindered
Solution Approach 1:
The patent segments comprehensive radiologist reports into multiple hierarchical levels of detail. The system divides complex medical assessments into core diagnostic findings, supporting evidence, and detailed technical data, allowing users to access different levels of information complexity. This enables effective patient communication by presenting only essential information in simple terms while preserving access to complete medical assessment when needed
Solution Approach 2:
The patent introduces an intermediary visualization layer between the radiologist's detailed report and patient understanding. This intermediary system translates complex medical terminology and imaging data into patient-friendly visual representations, acting as a mediator that preserves the completeness of the original assessment while improving communication effectiveness
3Device complexity
If traditional image analysis methods are used, then existing workflows are maintained, but patient understanding and informed decision-making are reduced
Solution Approach 1:
The patent adds a new visual dimension to traditional medical imaging workflows. By generating 3D visualizations, color-coded risk maps, and graphical representations alongside conventional 2D images, the system enhances patient comprehension without disrupting existing workflow simplicity. The additional dimensional information provides intuitive spatial and risk context that helps patients understand their condition better
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances patient comprehension of medical imaging results and treatment options, reducing reliance on physician interpretation and providing a visual tool for informed decision-making.
Implementation Method 1
the small molecule diagnostic 1404 targets the extracellular domain of prostate specific membrane antigen (PSMA), a protein amplified on the surface of >95% of prostate cancer cells
Implementation Method 2
1404 is labeled with technetium-99m, a gamma-emitter isotope that is widely available, relatively inexpensive, facilitates efficient preparation, and has spectrum characteristics attractive for nuclear medicine imaging applications
Implementation Method 3
The radioactive portion of the molecule serves as a beacon so that an image may be obtained depicting the disease location and concentration using commonly available nuclear medicine cameras, known as single-photon emission computerized tomography (SPECT) or positron emission tomography (PET) cameras
Data Source
AI summary
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.