Tumor Heterogeneity Visualization With Therapy Response Graphs
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Solution Overview
Problem
Current methods for visualizing tumor heterogeneity and survival statistics are inefficient and fail to incorporate therapy effectiveness, while existing survival plots like Kaplan-Meier plots are limited in representing comprehensive patient data.
Innovation Solution
A system and method that generates visual representations of tumor heterogeneity by differentiating subclones based on genetic variations and therapy effectiveness, and provides survival statistics through enhanced graphs such as survival function, median survival, mortality risk, and survival probability graphs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If current methods for visualizing tumor heterogeneity are used, then the visualization can be generated, but the visualization is not efficient and easy to understand
Solution Approach 1:
The patent segments tumor heterogeneity visualization into distinct graphical representations: a tumor heterogeneity graph showing subclone distributions, a therapy effectiveness graph displaying treatment responses, and a survival function graph presenting survival statistics. This segmentation allows complex tumor data to be broken down into manageable, easily interpretable visual components that address the technical contradiction by improving ease of understanding while maintaining comprehensive information presentation.
2Adaptability or versatility
If current methods for visualizing tumor heterogeneity are used, then the visualization can be generated, but therapy effectiveness is not incorporated
Solution Approach 1:
The patent merges multiple types of information into an integrated visualization system that combines tumor heterogeneity data, therapy effectiveness data, and survival statistics into a unified presentation. The system generates a tumor heterogeneity graph, therapy effectiveness graph, and survival function graph that work together to provide comprehensive information about patient outcomes and treatment responses, thereby incorporating therapy effectiveness without losing any critical information.
Solution Approach 2:
The visualization system is designed with multi-functionality to handle various types of medical data including tumor heterogeneity, therapy responses, and survival outcomes. The system can process different data formats and presentation requirements, making it universally applicable to various clinical scenarios while maintaining the ability to incorporate therapy effectiveness information that was previously excluded from standard visualizations.
3Adaptability or versatility
If Kaplan-Meier plot is used for survival visualization, then survival data can be displayed, but the plot is limited and does not encompass full array of information from EMR
Solution Approach 1:
The patent extends the traditional one-dimensional Kaplan-Meier survival curve into multiple dimensions by adding tumor heterogeneity graphs that display subclone-specific data, therapy effectiveness graphs that show treatment responses, and additional survival statistics graphs that provide comprehensive survival information. This dimensional expansion allows the visualization to encompass the full array of information available from electronic medical records while maintaining clarity through structured, multi-dimensional presentation.
Data Source
AI summary
A method (100) for visualizing heterogeneity of a patient's tumor, comprising: (i) receiving (120) information about a patient, comprising demographic and clinical information about the patient, an identification of the patient's tumor type, and a heterogeneity assessment of the patient's tumor; (ii) obtaining (130), based on the identification of the patient's tumor type and the heterogeneity assessment of the patient's tumor, therapy effectiveness information for each of the two or more subclones of the tumor: (iii) generating (140) a visual representation of the heterogeneity assessment of the patient's tumor and the obtained therapy effectiveness information for each of the two or more subclones of the tumor; and (iv) providing (150), via a user interface of the system, the generated visual representation, wherein the visual representation comprises a tumor heterogeneity graph and a therapy effectiveness graph.