Koninklijke Philips Corporation N.v.

Gipson Joe Anto

Vaitheeswaran Ranganathan

Prashant Kumar

Sivaramakrishnan Krishnaiyer Raman

Deepak Pitambar Mahajan

Bojarajan Perumal

Murali Balasubramanian

Reshmi Bhattacharjee

Ajesh Kumar

A method includes generating a nominal dose distribution based on an image and clinical goals. The method further includes generating a setup error dose distribution based on range and setup uncertainties. The method further includes generating a dose distribution for a parameter of an internal organ. The method further includes optimizing a planned dose distribution of an intensity modulated proton therapy plan by minimizing a total objective value including the nominal dose distribution, the setup error dose distribution dose distribution, and the dose distribution for the internal organ. The method further includes generating a final dose distribution for the intensity modulated proton therapy plan based on beam parameters of the optimized planned dose distribution. The method further includes controlling a proton therapy apparatus configured to deliver proton therapy based on the intensity modulated proton therapy plan with the optimized planned dose distribution.

Intensity modulated proton therapy (IMPT) plan optimization based at least on internal organ anticipated movement and/or expected deformation

A radiation therapy system () includes a radiation therapy (RT) optimizer unit () and an interactive planning interface unit (). The RT optimizer unit () receives at least one target structure and at least one organ-at-risk (OAR) structure segmented from a volumetric image (), and generates an optimized RT plan () based on dose objectives (--), at least one dose objective of the dose objectives corresponding to each of the at least one target structure (-) and the at least one OAR structure (-). The optimized RT plan includes a planned radiation dose for each voxel of the volumetric image using external beam radiation therapy, wherein the RT optimizer unit operates iteratively. The interactive planning interface unit () interactively controls each of the dose objectives through controls () displayed on a single display () of a display device (), operates the RT optimizer unit to iteratively compute the planned radiation dose according to the controls, and provide visual feedback () on the single display according to progress of the RT optimizer unit after each trial.

Radiation therapy interactive planning

A robustness optimization is disclosed for a broad beam proton therapy plan. A nominal dose distribution () is computed, to be delivered to a volume by performing proton therapy on the volume according to a proton therapy plan () having parameters () defining a range compensator shape and a range band. The parameters of the proton therapy plan are adjusted to reduce a difference between the nominal dose distribution () and a perturbed dose distribution calculated to be delivered to the volume modified by an error scenario () by performing proton therapy on the volume modified by the error scenario in accordance with the proton therapy plan with the parameters adjusted by the adjusting operation. The adjusting may be repeated serially for each error scenario of a set of error scenarios () to produce a proton therapy plan that is robust for any of these error scenarios.

Robust broad beam optimization for proton therapy

A method and related system to adjust an existing treatment plan. A second optimization is run based on a dual objective function system that includes a first objective function used for the optimization in respect of the existing plan and a second, extended objective function that includes the said first objective function as a functional component.

Method to reduce local hot/cold spots in DMPO-based IMRT planning

A method for dose-gradient based optimization of an intensity modulated radiation therapy plan. First, an optimizer () performs a first optimization () of the plan to generate dose distributions corresponding to the plan. Next, the optimizer () generates a beam specific dose gradient map () for each beam of the plan. Then, new dose gradients are specified () for the plan. Last, the optimizer () performs a final optimization () using the new dose gradients. The final optimization is given the new dose gradients as soft constraints into an objective function. The optimizer () 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.

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Gipson Joe Anto