Physician Directed Radiation Treatment Planning Engine
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The current radiation treatment planning process is time-consuming and often lacks sufficient physician involvement due to overwhelming degrees of freedom and constraints, leading to suboptimal treatment plans and prolonged time from diagnosis to treatment.
Innovation Solution
A treatment planning engine that empowers physicians to efficiently identify effective radiation treatment outcomes by storing and analyzing previous treatment data, allowing real-time evaluation and iteration of treatment plans, enabling informed decisions during the contouring stage, and facilitating the selection of optimal radiation doses for tumors and nearby anatomical structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If multiple iterations of treatment outcomes are created by dosimetrist and physician over many days, then the radiation treatment plan can be optimized, but the time from diagnosis to treatment increases
Solution Approach 1:
The system performs preliminary actions by pre-calculating and storing treatment outcomes for various contour configurations in a database before they are needed. When a physician contours a tumor, the system immediately retrieves pre-computed treatment outcomes rather than calculating them in real-time, enabling instant evaluation of multiple treatment scenarios without extending the planning timeline
Solution Approach 2:
The system creates copies of treatment outcomes by storing results from previous treatment plans in a database. These stored treatment outcomes can be retrieved and evaluated for new patients with similar anatomical characteristics, allowing physicians to assess multiple treatment scenarios quickly without performing full dosimetric calculations for each case
2Manufacturing precision
If physicians are heavily involved in treatment planning to guide dosimetrist, then treatment quality improves, but physicians become overwhelmed with other demands on their time
Solution Approach 1:
The system enables self-service by allowing physicians to independently contour tumor volumes and automatically retrieve evaluated treatment outcomes without requiring extensive dosimetrist assistance. The automated retrieval and presentation of pre-calculated treatment options empower physicians to perform treatment planning tasks themselves efficiently
Solution Approach 2:
The system acts as an intermediary between the physician's contouring input and the complex dosimetric calculations. It automatically retrieves pre-computed treatment outcomes from the database based on the physician's contours and presents them for evaluation, eliminating the need for physicians to manually perform or closely supervise complex dose calculations
3Manufacturing precision
If dosimetrist creates treatment outcome with overwhelming degrees of freedom and constraint priorities, then optimal plan can be achieved, but the process becomes time-consuming
Solution Approach 1:
The system performs preliminary dosimetric calculations and stores treatment outcomes for various contour configurations before they are needed. This pre-computation handles the complex optimization of degrees of freedom and constraint priorities in advance, so that when a physician needs treatment options, they are immediately available without time-consuming real-time calculations
Solution Approach 2:
The system creates and stores copies of optimized treatment outcomes from previous cases in a database. These pre-optimized treatment plans can be retrieved and adapted for new patients, eliminating the need to re-solve complex optimization problems from scratch and significantly reducing planning time while maintaining optimality
Data Source
AI summary
The treatment planning engine empowers radiation treatment decision makers, such as a physician, to efficiently identify effective radiation treatment outcomes for a given patient during the contouring stage. Specifically, using the treatment planning engine, the physician may iteratively and in real-time evaluate different treatment outcomes for a patient before selecting an optimal outcome that will guide the delivery of radiation treatment to the patient. By providing real-time information as to potential toxicity and treatment efficacy during the contouring stage, the physician is empowered to make informed decisions at the preliminary contouring stage.