Optimization of thermoradiotherapy treatment
A combined set of treatment plans including radiation treatment and hyperthermia treatment may be optimized either by co-optimizing both plans together or by optimizing one of the plans and then optimizing the other taking into account the predicted effect of the first optimized plan.
1 . A computer-based method for generating a set of treatment plans including a radiation treatment plan and a hyperthermia treatment plan, for thermoradiotherapy treatment for a treatment volume of a patient, the method comprising:
a. obtaining an optimization problem including at least one objective function related to the multimodality treatment including hyperthermia and radiation, wherein the objective function models a combined biological effect of temperature and dose for each of a plurality of voxels of the treatment volume using a biophysical model with temperature-dependent parameters and is subject to constraints of at least one radiotherapy delivery device and at least one hyperthermia applicator;
b. generating at least one of the radiation treatment plan and the hyperthermia treatment plan by optimizing the objective function value evaluated for the predicted combined effect over the set of treatment plans wherein the optimization simultaneously adjusts hyperthermia power deposition parameters and radiation dose-distribution variables within a single coupled optimization problem, such that the temperature field and radiation dose at the voxels evolve interdependently during the optimization; and
c. delivering thermoradiotherapy treatment to the patient in accordance with the set of treatment plans.
2 . The method of claim 1 , wherein the radiation treatment plan is an external beam radiation treatment plan.
3 . The method of claim 1 , wherein the step of generating the at least one of the radiation treatment plan and the hyperthermia treatment plan comprises co-optimization of the hyperthermia plan and the radiotherapy plan, the optimization problem including information on a predicted combined effect of temperature and dose for each voxel.
4 . The method of claim 1 , wherein a pre-existing hyperthermia plan has been obtained before the step of obtaining the optimization problem, and wherein the step of generating the at least one of the radiation treatment plan and the hyperthermia treatment plan comprises optimizing the radiotherapy plan accounting for the predicted effect of at least one pre-existing hyperthermia plan, wherein the optimization problem includes temperature dependence information for the biological parameters for each voxel.
5 . The method of claim 1 , wherein a pre-existing radiation treatment plan has been obtained and wherein the step of generating the at least one of the radiation treatment plan and the hyperthermia treatment plan comprises optimizing the hyperthermia plan accounting for the predicted effect of at least one pre-existing radiotherapy plan, wherein the optimization problem includes the effect of the radiation dose for each voxel.
6 . The method of claim 1 , wherein the model includes one or more of the following: the equivalent radiation dose, equivalent uniform distribution, biological effective dose, thermal enhancement ratio, tumor control probability, normal tissue complication probability, complication free cure probability, secondary cancer, and/or overall survival.
7 . The method of claim 1 , wherein the optimization problem comprises constraints which define parameters that are maintained during optimization.
8 . The method of claim 1 , wherein the optimization problem comprises a biological or a physical objective.
9 . The method of claim 1 , wherein the optimization problem is defined to optimize machine parameters of at least one of the heat delivery systems and the radiation delivery system as variables.
10 . The method of claim 1 , wherein the optimization problem includes at least one constraint related to machine limitations of at least one delivery machine that will be used to deliver hyperthermia treatment and/or radiation treatment as constraints or objectives.
11 . The method of claim 1 , wherein the optimization problem includes a simplified machine model for either the heating system or the radiation treatment system for which the parameters are optimized.
12 . The method of claim 1 , further comprising the step, performed before the steps of claim 1 , of defining the set of treatment plans including the hyperthermia plan and the radiotherapy plan and at least one other type of plan.
13 . The method of claim 1 , wherein the set of treatment plans comprises at least a first and a second radiotherapy plan, where the first radiotherapy plan is optimized for delivery on the same day as the at least one hyperthermia plan and the second radiotherapy plan is optimized for delivery on the days where no hyperthermia plan is delivered.
14 . The method of claim 1 , wherein the set of treatment plans comprises at least one additional therapy plan along with the at least one hyperthermia plan and at least one radiotherapy plan, said at least one additional therapy plan related to a systemic treatment.
15 . A computer program product comprising a non-transitory computer readable storage medium containing instructions which when run in a processor will cause the processor to perform the method according to claim 1 .
16 . A computer comprising a processor and a program memory, wherein the program memory holds a computer program product according to claim 15 , for being executed in the processor.