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US 10,864,382 B2Granted
System and method for radiation therapy treatment planning
AssigneeRaySearch Laboratories AB
InventorRasmus Bokrantz
Life of this patent
Estimating the term…
Abstract
Radiation therapy treatment planning methods facilitate predicting achievable dose distributions by training a prediction model for clinical DVH curves based on simplified DVH curves obtained using standardized methods. Machine learning applied on pairs of clinical and simplified DVH curves enables predicting actual clinical DVH curves based on simplified DVH curves.
Claims16
A method for use in radiation therapy treatment planning, comprising:
- a. obtaining a protocol plan, which has been created by applying a plan generation protocol to a set of patient data for a current patient, said set of patient data comprising at least one planning image;
- b. calculating at least one protocol dose volume histogram (DVH) curve, each protocol DVH curve relating a dose distribution for the protocol plan to a volume of a structure in a structure set, the dose distribution and the structure set being associated with the at least one planning image;
- c. obtaining estimated clinical DVH curves by sending the at least one protocol DVH curve as a query to a prediction model, the prediction model being arranged to determine estimated clinical DVH curves on the basis of the at least one protocol DVH curve for the current patient based on a relationship between previous protocol DVH curves and previous clinical DVH curves for a collection of previous patients, wherein the estimated clinical DVH curves are determined based on clinical DVH curves from previous patients that have protocol DVH curves having a distance to the at least one protocol DVH curve of the current patient below a specified threshold value;
- and
- d. using at least one of the estimated clinical DVH curves in treatment planning for the current patient.
2 more elements
A method of training a prediction model for use in radiation therapy treatment planning, the training of the prediction model comprising the following steps:
- a. obtaining a set of patient data for a previous patient, the set of patient data comprising at least one planning image;
- b. obtaining a plan generation protocol;
- c. obtaining a protocol plan of the previous patient by applying the plan generation protocol to the set of patient data;
- d. calculating at least one protocol dose volume histogram (DVH) curve for the previous patient, each protocol DVH curve relating a dose distribution for the protocol plan of the previous patient to a volume of a structure in a structure set associated with the at least one planning image;
- e. obtaining a clinical DVH curve associated with each protocol DVH curve, each clinical DVH curve relating a clinical dose distribution for the previous patient to the volume;
- f. performing steps a-e for each of a number of previous patients to obtain a number of pairs including a protocol DVH curve and an associated clinical DVH curve;
- g. selecting a subset of the pairs of DVH curves;
- and
- h. training a machine learning model using the pairs of protocol DVH curve and associated clinical DVH curve of the previous patients, the machine learning model being configured to take protocol DVH curves of a current patient as input and return estimated clinical DVH curves as input, the process of training the machine learning model involving adjusting system parameters of the machine learning model toward minimization of a deviation between estimated clinical DVH curves and true clinical DVH curves for the previous patients.
6 more elements
Dependencies are inferred from the claim text.