Using reinforcement learning in radiation treatment planning optimization to locate dose-volume objectives
US-2021379404-A1 · Dec 9, 2021 · US
US12533528B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12533528-B2 |
| Application number | US-202318315974-A |
| Country | US |
| Kind code | B2 |
| Filing date | May 11, 2023 |
| Priority date | May 11, 2023 |
| Publication date | Jan 27, 2026 |
| Grant date | Jan 27, 2026 |
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A computer-implemented method for radiation treatment planning, the method comprising: receiving a reference dose value, wherein the reference dose value is a defined maximum radiation dose within a first region for radiation treatment in a patient; applying an optimization procedure to a treatment plan for radiation treatment of the patient, wherein the optimization procedure seeks to minimize a cost function which is representative of a dose excess value above the reference dose value; and responsive to determining that the dose excess value is below a threshold value: decreasing the reference dose value; and reapplying the optimization procedure to the treatment plan, wherein the optimization procedure seeks to minimize the cost function based on the decreased reference dose value.
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What is claimed is: 1 . A computer-implemented method for radiation treatment planning, the method comprising: receiving a reference dose value, wherein the reference dose value is a defined maximum radiation dose within a first region for radiation treatment in a patient; applying an optimization procedure to a treatment plan for radiation treatment of the patient, wherein the optimization procedure reduces a cost function which is representative of a dose excess value above the reference dose value; and responsive to determining that the dose excess value is below a threshold value: decreasing the reference dose value; reapplying the optimization procedure to the treatment plan, wherein the optimization procedure further reduces the cost function based on the decreased reference dose value; and iterating the steps of decreasing the reference dose value and reapplying the optimization procedure until a stopping criterion is reached, wherein the stopping criterion comprises the optimization procedure failing to reduce the cost function such that the dose excess value is below the threshold value after a defined number of optimization iterations or a defined amount of time. 2 . The method of claim 1 , further comprising: responsive to a determination that the stopping criterion has been reached, outputting a set of optimized parameters for the treatment plan. 3 . The method of claim 2 , wherein the set of optimized parameters define a fluence map for the treatment plan. 4 . The method of claim 2 , further comprising: determining a configuration of a radiotherapy system for the treatment plan based on the set of optimized parameters. 5 . The method of claim 1 , wherein the optimization procedure iteratively adapts the treatment plan to minimize the cost function. 6 . The method of claim 1 , wherein the reference dose value is decreased by a fixed value. 7 . The method of claim 6 , wherein the fixed value is between 0.3 and 0.7 Gy. 8 . The method of claim 1 , wherein the reference dose value is decreased by an amount based on one or more of: the reference dose value, the threshold value, and a difference between the reference dose value and the threshold value. 9 . The method of claim 1 , wherein the dose excess value comprises a root mean square dose excess value. 10 . The method of claim 1 , wherein the cost function is a quadratic overdose cost function. 11 . The method of claim 1 , wherein the cost function is proportional to: ∑ i ∈ V ❘ "\[LeftBracketingBar]" V i ❘ "\[RightBracketingBar]" [ D i - Δ ] + 2 representing a summation over i voxels in a volume V of the first region, wherein V i is a volume of the ith voxel, D i is a dose delivered to the ith voxel, Δ is the reference dose value, and the operator [D i −Δ] + represents the maximum of [D i −Δ] and zero. 12 . The method of claim 1 , wherein the method further comprises: prior to applying the optimization procedure, receiving a maximum dose excess value, wherein the threshold value is equal to or less than the maximum dose excess value. 13 . The method of claim 12 , wherein a reference objective for the optimization procedure comprises the reference dose value and the maximum dose excess value. 14 . The method of claim 1 , wherein the optimization procedure further reduces the cost function subject to one or more constraints. 15 . The method of claim 1 , wherein the optimization procedure further reduces the cost function with respect to one or more optimizable parameters. 16 . The method of claim 15 , wherein the one or more optimizable parameters comprise one or more of: the dose excess value, one or more beamlets weights, one or more beam angles, a dose-histogram-volume information, a number of radiation beams, and a dose per beam. 17 . The method of claim 1 , wherein the first region comprises a target region for the radiation treatment and/or an organ at risk, OAR. 18 . A data processing apparatus comprising: a memory storing computer-executable instructions; and a processor configured to execute the instructions to: receive a reference dose value, wherein the reference dose value is a defined maximum radiation dose within a first region for radiation treatment in a patient; apply an optimization procedure to a treatment plan for radiation treatment of the patient, wherein the optimization procedure reduces a cost function which is representative of a dose excess value above the reference dose value; and responsive to determining that the dose excess value is below a threshold value: decrease the reference dose value; reapply the optimization procedure to the treatment plan, wherein the optimization procedure further reduces the cost function based on the decreased reference dose value; and iterate the steps of decreasing the reference dose value and reapplying the optimization procedure until a stopping criterion is reached, wherein the stopping criterion comprises the optimization procedure failing to reduce the cost function such that the dose excess value is below the threshold value after a defined number of optimization iterations or a defined amount of time. 19 . A non-transitory computer-readable storage medium comprising instructions which, when executed by a computer, cause the computer to: receive a reference dose value, wherein the reference dose value is a defined maximum radiation dose within a first region for radiation treatment in a patient; apply an optimization procedure to a treatment plan for radiation treatment of the patient, wherein the optimization procedure reduces a cost function which is representative of a dose excess value above the reference dose value; and responsive to determining that the dose excess value is below a threshold value: decrease the reference dose value; reapply the optimization procedure to the treatment plan, wherein the optimization procedure further reduces the cost function based on the decreased reference dose value; and iterating the steps of decreasing the reference dose value and reapplying the optimization procedure until a stopping criterion is reached, wherein the stopping criterion comprises the optimization procedure failing to reduce the cost function such that the dose excess value is below the threshold value after a defined number of optimization iterations or a defined amount of time. 20 . A computer-implemented method for radiation treatment planning, the method comprising: receiving a reference dose value, wherein the reference dose value is a defined maximum radiation dose withi
using a specific method of dose optimization · CPC title
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