Multi-site Radiotherapy Beam Scoring Algorithm
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Solution Overview
Problem
Current radiotherapy systems are inefficient in treating multiple tumors simultaneously while minimizing damage to critical organs, requiring extensive human effort and time, limiting the treatment of multiple metastases to only a few due to the complexity of planning and calculating precise radiation doses.
Innovation Solution
A system and method that utilize a computing system to generate a set of beams that maximize dosage to tumors while minimizing dosage to Organs at Risk (OAR) by scoring and ranking candidate beams based on their ability to cover tumors and impact on normal organs, automatically selecting the best beams for treatment, and transmitting them to a radiation therapy beam generator for generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual planning methods are used to determine radiation beam angles and shapes for multiple tumors, then treatment precision can be achieved, but the planning time and human effort required become excessively long
Solution Approach 1:
The patent replaces manual mechanical planning processes with an automated computer-based system that uses algorithms to calculate optimal beam angles and shapes. The system automatically processes three-dimensional medical images, identifies tumor locations, computes radiation dosages, and generates treatment plans without manual intervention, thereby maintaining precision while dramatically reducing planning time from hours to minutes.
Solution Approach 2:
The system enables self-service planning where the computer automatically performs all planning tasks including image processing, tumor identification, beam parameter optimization, and dosage calculation based on pre-programmed algorithms and clinical guidelines, eliminating the need for continuous human oversight while maintaining high accuracy standards.
2Productivity
If multiple tumors are treated simultaneously, then treatment efficiency increases, but the complexity of avoiding critical Organs at Risk increases significantly
Solution Approach 1:
The patent segments the complex multi-tumor treatment planning into distinct automated computational steps: three-dimensional image reconstruction, individual tumor identification and localization, critical organ mapping, beam path calculation for each tumor, dosage optimization considering all tumors and organs simultaneously, and treatment sequence determination. This segmentation allows the system to handle multiple tumors efficiently while managing complexity through systematic processing.
Solution Approach 2:
The system transitions from two-dimensional treatment planning to three-dimensional spatial modeling, using volumetric medical images to accurately represent tumor and organ positions in space. This dimensional enhancement enables the system to calculate optimal beam angles and paths that account for the spatial relationships between multiple tumors and critical organs, simplifying the complexity of multi-target planning.
3Reliability
If extensive manual optimization is performed to avoid Organs at Risk, then safety of treatment improves, but the number of tumors that can be treated is limited to 1-2
Solution Approach 1:
The patent replaces manual safety optimization processes with automated computational algorithms that can simultaneously evaluate and optimize beam paths for multiple tumors while respecting constraints for all critical organs. The system processes numerous potential beam configurations and selects optimal solutions that maximize tumor coverage while minimizing organ exposure, enabling treatment of 3-4 or more tumors with maintained safety standards.
Solution Approach 2:
The system creates virtual models and simulations of radiation beam interactions with patient anatomy, allowing extensive optimization of treatment plans in the digital domain before actual treatment delivery. Multiple beam configurations can be tested and compared virtually, ensuring safety requirements are met while maximizing the number of treatable tumors without increasing actual treatment time or risk.
Data Source
AI summary
A method of radiating a plurality of masses in a patient is provided, including receiving a three-dimensional model of the patient, the model including respective locations of a plurality of OARs, receiving a set of locations in the model corresponding to the masses, respective prescribed radiation dosages for the masses, and respective radiation limits for the OARs. The method includes computing a candidate set of beams having respective beam paths that travel through at least one of the masses. The method includes scoring the candidate set of beams based on respective dosages provided to the masses, respective dosages provided to the OARs, and beams in a set of selected beams for treatment, adding a best-scoring beam among the candidate set of beams to the set of selected beams, and radiating the masses using the set of selected beams.