Dynamic Radiotherapy Strategy Adjustment via Real-Time Risk Modeling
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Solution Overview
Problem
Current radiotherapy-based treatments face challenges in accurately quantifying and managing the risk of adverse events, which affects the balance between treatment efficacy and patient safety, particularly in combination therapies like radiotherapy and immunotherapy.
Innovation Solution
A computer-implemented method that generates a radiotherapy-based treatment strategy by obtaining and modifying a risk value based on identified side-effects, using temporal and severity characteristics to adjust the treatment plan and minimize risk while maximizing efficacy, employing a risk model to classify subjects and update treatment strategies iteratively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If radiation dose is increased to improve treatment efficacy, then tumor size reduction is improved, but risk of adverse events increases
Solution Approach 1:
The patent dynamically adjusts treatment parameters (radiation dose, fractionation scheme) based on real-time monitoring of adverse events and tumor response. The risk value model allows continuous modification of treatment parameters to optimize the balance between efficacy and safety throughout the treatment course.
Solution Approach 2:
The system implements continuous feedback loops where adverse events are monitored, risk values are updated, and treatment plans are adjusted accordingly. This closed-loop control enables real-time optimization of radiation dosing based on actual patient response and tolerance.
2Object-affected harmful factors
If treatment characteristics are adjusted to reduce risk, then adverse events are reduced, but treatment efficacy decreases
Solution Approach 1:
The treatment plan transitions from static to dynamic, with continuous adjustment of radiation dose and scheduling based on real-time patient response. The system adapts treatment characteristics dynamically to maintain optimal efficacy while minimizing risk throughout the treatment course.
Solution Approach 2:
Treatment parameters such as radiation dose, fractionation, and scheduling are continuously modified based on updated risk values. This allows the system to reduce risk while preserving efficacy by optimizing parameters rather than simply lowering overall dose.
3Ease of operation
If a fixed treatment plan is used, then treatment simplicity is maintained, but ability to respond to adverse events is reduced
Solution Approach 1:
The system pre-establishes risk models, monitoring protocols, and adjustment algorithms before treatment begins. This preliminary preparation enables rapid, automated responses to adverse events without requiring complex real-time decision-making, maintaining operational simplicity while enhancing adaptability.
Solution Approach 2:
The treatment planning system automatically adjusts treatment parameters based on monitored adverse events and updated risk values, reducing the need for manual intervention. The system serves itself by continuously optimizing treatment based on real-time data without requiring constant clinician input.
Data Source
AI summary
A method of generating a strategy for performing a radiotherapy-based treatment and a system for performing the method. During a radiotherapy-based treatment, characteristics of side-effects are monitored and a risk model of the subject modified based on the characteristics. A new treatment strategy for the radiotherapy-based treatment is obtained based on the modified risk model.