Adaptive Radiotherapy NTCP Model Using Biomarkers
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Solution Overview
Problem
Current radiotherapy protocols face challenges in accurately predicting normal tissue complication probabilities (NTCP) due to their reliance on population mean statistics, ignoring individual patient risk profiles, which can lead to suboptimal tumor control or severe side effects.
Innovation Solution
An adaptive radiotherapy system that utilizes a planning processor to calculate individualized NTCP and tumor control probability (TCP) models based on patient-specific biomarkers, modifying the equivalent uniform dose (EUD) function with dose-modifying factors to optimize radiation therapy protocols dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If population mean statistics are used for NTCP modeling, then the model is simple and based on general data, but it fails to account for individual patient risk profiles leading to inaccurate predictions
Solution Approach 1:
The patent applies local quality by transitioning from population-level average parameters to patient-specific localized parameters. Individual patient risk profiles, biomarker values, and treatment response characteristics are used to customize NTCP model parameters for each patient, thereby improving prediction accuracy without requiring overly complex model structures. The model adapts local patient characteristics into the general NTCP framework.
Solution Approach 2:
The patent implements parameter changes by dynamically adjusting NTCP model parameters based on individual patient data. Key parameters such as dose-response relationships, volume effects, and sensitivity factors are modified according to patient-specific biomarkers, genetic profiles, and treatment history. This allows the model to maintain mathematical simplicity while incorporating personalized information through parameter adaptation rather than structural complexity.
2Reliability
If individual patient risk profiles are incorporated into NTCP models, then prediction accuracy improves, but the complexity of the model increases
Solution Approach 1:
The patent applies preliminary action by collecting and analyzing patient-specific risk profile data, biomarkers, and treatment response indicators before finalizing the NTCP model parameters. This preparatory step allows the model to be pre-configured with individual patient characteristics, ensuring reliable tumor control probability predictions without requiring complex real-time adjustments during treatment planning. The personalized parameters are established in advance based on patient-specific data.
3Adaptability or versatility
If dose-modifying factors are applied to EUD functions, then treatment plans can be optimized for individual patients, but the calculation complexity increases
Solution Approach 1:
The patent applies asymmetry by implementing asymmetric dose-modifying factors that are specifically tailored to individual patient characteristics rather than applying uniform adjustments. The modifying factors are derived from patient-specific biomarkers, genetic profiles, and treatment response patterns, creating asymmetric adjustments that reflect the unique biology of each patient. This approach enables customized treatment optimization without requiring symmetric or standardized modification schemes that would be simpler but less effective.
Data Source
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AI summary
A therapy system includes a diagnostic image scanner (12) that acquires a diagnostic image of a target region to be treated. A planning processor (70) is configured to generate a patient specific adaptive radiation therapy plan based on patient specific biomarkers before and during therapy. A first set of patient specific biomarkers is determined then used for the determination of a first normal tissue complication probability (NTCP) model and a first tumor control probability (TCP) model. A radiation therapy device (40) administers a first dose of radiation to the target region with a protocol based on the first NTCP model and the first TCP model. A second set of patient specific biomarkers is determined. A relationship between the first set and second set of patient specific biomarkers is used to determine a second NTCP model and a second TCP model. The radiation therapy device (40) administers a second dose of radiation to the target region with a protocol based on the second NTCP model and second TCP model.