Automatic generation of patient-specific radiation therapy planning parameters
First Claim
1. A method comprising:
- receiving by a data-processing system;
(a) first data based on a geometric characterization of one or more organs at risk proximate to a target volume of a patient P, wherein the geometric characterization associates each of a plurality of distances from the target volume with a respective percentage of the volume of the one or more organs at risk;
(b) second data comprising a size of the target volume and the respective sizes and shapes of the one or more organs at risk; and
generating, by said data-processing system using a predictive model, one or more radiation treatment planning parameters for said patient P based on the first data and the second data.
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Abstract
An apparatus and method for automatically generating radiation treatment planning parameters are disclosed. In accordance with the illustrative embodiment, a database is constructed that stores: (i) patient data and past treatment plans by expert human planners for these patients, and (ii) optimal treatment plans that are generated using multi-objective optimization and Pareto front search and that represent the best tradeoff opportunities of the patient case, and a predictive model (e.g., a neural network, a decision tree, a support vector machine [SVM], etc.) is then trained via a learning algorithm on a plurality of input/output mappings derived from the contents of the database. During training, the predictive model is trained to identify and infer patterns in the treatment plan data through a process of generalization. Once trained, the predictive model can then be used to automatically generate radiation treatment planning parameters for new patients.
17 Citations
18 Claims
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1. A method comprising:
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receiving by a data-processing system; (a) first data based on a geometric characterization of one or more organs at risk proximate to a target volume of a patient P, wherein the geometric characterization associates each of a plurality of distances from the target volume with a respective percentage of the volume of the one or more organs at risk; (b) second data comprising a size of the target volume and the respective sizes and shapes of the one or more organs at risk; and generating, by said data-processing system using a predictive model, one or more radiation treatment planning parameters for said patient P based on the first data and the second data. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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- 8. A method comprising training by a data-processing system a predictive model on a plurality of input-output mappings, wherein the output of each input-output mapping is based on a dose distribution and a dose volume histogram for a respective patient, and wherein the input of each input-output mapping comprises one or more data that are based on a geometric characterization of one or more organs at risk proximate to a target volume of the respective patient, wherein said geometric characterization associates each of a plurality of distances from said target volume with a respective percentage of the volume of said one or more organs at risk.
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15. A method comprising storing in a database, by a data-processing system:
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(a) one or more planning parameters of a first radiation treatment plan, wherein said first radiation treatment plan is for a first patient and is generated by one of; (i) an expert human planner, and (ii) a data-processing system using one or both of multi-objective optimization and pareto front search; (b) a first geometric characterization of a first non-empty set of organs at risk proximate to a first target volume of said first patient, wherein the first geometric characterization is a function of volume for the organs at risk; (c) one or more planning parameters of a second radiation treatment plan, wherein said second radiation treatment plan is for a second patient and is generated by one of; (i) an expert human planner, and (ii) a data-processing system using one or both of multi-objective optimization and pareto front search; and (d) a second geometric characterization of a second non-empty set of organs at risk proximate to a second target volume of said second patient, wherein the second geometric characterization is a function of volume for the organs at risk. - View Dependent Claims (16)
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17. A method comprising:
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receiving by a data-processing system one or more data, wherein at least one of the data is based on a geometric characterization of one or more organs at risk proximate to a target volume of a patient P, and wherein the geometric characterization associates each of a plurality of distances from said target volume with a respective percentage of the volume of said one or more organs at risk; and generating by the data-processing system one or more radiation treatment planning parameters for the patient P based on the one or more data.
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18. A method comprising:
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receiving first data and second data at a data-processing system, wherein; (a) the first data is based on a geometric characterization of one or more organs at risk proximate to a target volume of a patient P; and (b) the second data is based on the size of the target volume and the respective sizes and shapes of the one or more organs at risk; and generating by the data-processing system one or more radiation treatment planning parameters for the patient P based on the first data and the second data.
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Specification