Abstract:
In a continuous arc radiation therapy planning method for planning a radiation therapy session parameterized by a set of parameters for control points (CPs) along at least one radiation source arc, a geometric optimization (40) is performed that does not include calculating radiation absorption profiles to generate optimized values for a sub-set of the parameters. After the geometric optimization, a main optimization (42) is performed that includes calculating radiation absorption profiles. The main optimization is performed with the sub-set of parameters initialized to the optimized values from the geometric optimization. The sub-set of parameters optimized by the geometric optimization may include collimator angle parameters for a multileaf collimator (MLC) (58). The geometric optimization may optimize a cost function comprising a sum over the CPs of a per-CP cost function dependent on a target-only region (62) defined as a planning target volume excluding any portion overlapping an organ at risk.
Abstract:
The invention relates to a method of selecting a set of beam geometries for use in radiation therapy. The method (10) comprises providing (12) a plurality of candidate beam geometries; optimizing (1) a radiation treatment plan with all candidate beam geometries; and computing (14) a cost function value based on all candidate beam geometries. A first beam geometry from the plurality of candidate beam geometries is removed (15) and a first modified cost function value based on the candidate beam geometries without the removed first beam geometry computed (16). The first beam geometry is restored (17). The steps of removing a beam geometry, computing of a modified cost function value and restoring of the removed beam geometry are repeated (R) for all other candidate beam geometries. One or more beam geometries from the plurality of candidate beam geometries based on the modified cost function values are chosen (19).
Abstract:
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.
Abstract:
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.
Abstract:
A method and system for normalizing an IMPT plan are provided as well as an arrangement for planning IMPT and a computer program product comprising instructions to perform the method. The method comprises the steps of: receiving an IMPT plan for a subject to be treated, receiving anatomical image data of the subject comprising at least one ROI, and receiving at least one clinical goal associated with the ROI. The method further comprises identifying one or more deficiency areas of the IMPT plan within the ROI where the clinical goal is not met, and identifying the particle spots of the IMPT plan that are associated with the identified deficiency areas as critical particle spots. When the critical spots have been identified, the method comprises normalizing at least one of the deficiency areas by adjusting the intensity of the critical particle spots.
Abstract:
A radiation therapy system (100) includes a radiation therapy (RT) optimizer unit (102) and an interactive planning interface unit (120). The RT optimizer unit (102) receives at least one target structure and at least one organ-at-risk (OAR) structure segmented from a volumetric image (108), and generates an optimized RT plan (140) based on dose objectives (200-204, 210-222, 320), at least one dose objective of the dose objectives corresponding to each of the at least one target structure (210-222) and the at least one OAR structure (200-204). 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 (120) interactively controls each of the dose objectives through controls (300) displayed on a single display (126) of a display device (124), operates the RT optimizer unit to iteratively compute the planned radiation dose according to the controls, and provide visual feedback (310, 134) on the single display according to progress of the RT optimizer unit after each trial.
Abstract:
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.
Abstract:
The present invention relates to image fusion of lower resolution images (32) and higher resolution reference images (50) of an object (30). Specific image scanning geometries used for acquiring the lower resolution images (32) are determined based on a machine learning algorithm that uses at least one feature in at least one region of interest in the respective lower resolution images (32) as input. Image scanning geometry matching oblique higher resolution images (54) are generated based on the higher resolution reference images (50) and the determined specific image scanning geometries used for acquiring the respective lower resolution images (32). The oblique higher resolution images (54) are registered with the lower resolution images (32) in order to generate registered higher resolution images. Current feature information is extracted from the lower resolution images and mapped on corresponding feature information in the registered higher resolution images in order to generate fusion images.
Abstract:
A radiation therapy delivery device console (50) controls a radiation therapy delivery device (36) and an imaging device (40, 42), and further performs adaptive radiotherapy (ART) recommendation as follows. The imaging device is controlled to acquire a current image (44) of a patient. At least one perturbation of the current image is determined compared with a radiation therapy planning image (1) from which a radiation therapy plan (22) for the patient has been generated. An ART recommendation score is computed, indicating whether ART should be performed, based on the determined at least one perturbation. A recommendation is displayed as to whether ART should be performed based on the computed ART recommendation score, or an alarm is displayed conditional upon the computed ART recommendation score satisfying an ART recommendation criterion.
Abstract:
A robustness optimization is disclosed for a broad beam proton therapy plan. A nominal dose distribution (62) is computed, to be delivered to a volume by performing proton therapy on the volume according to a proton therapy plan (50) having parameters (52) 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 (62) and a perturbed dose distribution calculated to be delivered to the volume modified by an error scenario (64) 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 (44) to produce a proton therapy plan that is robust for any of these error scenarios.