IMRT Dose Gradient Optimization for Delivery Complexity

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Solution Overview

Problem

Current radiation therapy planning, particularly in intensity modulated radiation therapy (IMRT), faces challenges in efficiently optimizing beam placement and dose delivery due to high complexity and sensitivity to geometric uncertainties, leading to increased monitor units and prolonged delivery times, with existing smoothing algorithms often degrading plan quality by failing to distinguish between desirable and undesirable modulation.

Innovation Solution

A dose gradient-based optimization technique that involves optimizing initial plan settings, generating dose gradient maps, allowing user input for specifying new gradients in beam's eye view, and performing a second optimization using these gradients as constraints to control IMRT delivery complexity and improve plan quality.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If smoothing algorithms are applied to reduce beam complexity, then deliverability is improved, but plan quality degrades because the algorithm cannot distinguish between desirable and undesirable modulation

Engineering Contradiction:
ImprovedeliverabilityVSAvoidplan quality
Core Design Contradiction:
Ease of operationVSManufacturing precision

Solution Approach 1:

The patent applies different smoothing strategies to different regions of the beam based on local characteristics. Desirable modulation (sharp gradients at target boundaries) is preserved while undesirable modulation (high frequency fluctuations within uniform regions) is smoothed, achieving both quality preservation and deliverability improvement

Inventive Principle:
Principle #3Local quality

2Manufacturing precision

If intensity patterns become more complex to achieve optimization objectives, then dose distribution quality is improved, but delivery complexity increases with more monitor units and longer delivery times

Engineering Contradiction:
Improvedose distribution qualityVSAvoiddelivery complexity
Core Design Contradiction:
Manufacturing precisionVSDevice complexity

Solution Approach 1:

The patent extracts and removes high frequency spatial fluctuations and sharp intensity peaks from the optimized fluence pattern while preserving the essential low frequency dose distribution characteristics, thereby reducing delivery complexity without significantly compromising dose quality

Inventive Principle:
Principle #2Taking out (Extraction)

Solution Approach 2:

Instead of directly optimizing for simple deliverable patterns, the patent first optimizes for ideal dose distribution and then applies post-processing smoothing to achieve deliverability, inverting the traditional optimization sequence

Inventive Principle:
Principle #13The other way round (Inversion)

3Measurement precision

If excessive monitor units are used to achieve precise dose distribution, then dose precision is improved, but additional dose is delivered to patient from transmission and leakage

Engineering Contradiction:
Improvedose precisionVSAvoidadditional dose from transmission and leakage
Core Design Contradiction:
Measurement precisionVSObject-generated harmful factors

Solution Approach 1:

The patent modifies the intensity parameters of the beam by applying smoothing constraints during optimization or post-processing, reducing the magnitude of intensity variations and resulting monitor units while maintaining acceptable dose distribution precision

Inventive Principle:
Principle #35Parameter changes

Data Source

PatentEP2994195B1Interactive dose gradient based optimization technique to control IMRT delivery complexity
Publication Date: 2022.02.23 KONINKLIJKE PHILIPS NV
  • EP2994195B1 patent drawingFigure 1
  • EP2994195B1 patent drawingFigure 2
  • EP2994195B1 patent drawingFigure 3

AI summary

A method for dose-gradient based optimization of an intensity modulated radiation therapy plan.First, an optimizer (6) performs a first optimization (40) of the plan to generate dose distributions corresponding to the plan. Next, theoptimizer (6) generates a beam specific dose gradient map (42) for each beam of the plan. Then, new dose gradients are specified (44) for the plan.Last, the optimizer (6) performs a final optimization(46) using the new dose gradients.The final optimization is given the new dose gradients as soft constraints into an objective function. The optimizer (3) applies a limiting factor to the objective function such that a first dose gradient is limited by the optimizer only if the first dose gradient exceeds the new dose gradient for a specific beamlet.