High-dose-rate brachytherapy with optimal needle placement for prostate cancer
A method for needle position optimization for prostate brachytherapy for use with a radiation delivery device configured to use a plurality of needles inserted into a prostate of a patient includes obtaining imagery of the prostate of the patient, generating a needle pool for prostate brachytherapy treatment of the patient based on the imagery of the prostate of the patient, and determining at a computing device an optimum prostate brachytherapy treatment plan for the patient by iteratively removing needles from the needle pool by forming and computationally solving a convex optimization problem wherein the convex optimization problem uses a quadratic dosimetric penalty function, dwell time regularization by total variation, and block sparsity regularization term.
1 . A method for needle position optimization for prostate brachytherapy for use with a radiation delivery device configured to use a plurality of needles inserted into a prostate of a patient, the method comprising:
obtaining imagery of the prostate of the patient;
generating a needle pool for prostate brachytherapy treatment of the patient based on the imagery of the prostate of the patient;
determining at a computing device an optimum prostate brachytherapy treatment plan for the patient by iteratively removing needles from the needle pool by forming and computationally solving a convex optimization problem wherein the convex optimization problem uses a quadratic dosimetric penalty function, dwell time regularization by total variation, and a block sparsity regularization term; and
performing the prostate brachytherapy according to the optimum prostate brachytherapy treatment plan for the patient.
2 . The method of claim 1 wherein the imagery is magnetic resonance imagery.
3 . The method of claim 1 wherein the obtaining the imagery of the prostate of the patient is performed using a portable magnetic resonance imaging (MRI) scanner.
4 . The method of claim 1 wherein the computationally solving the convex optimization problem is performed using a proximal operator graph solver (POGS).
5 . The method of claim 1 wherein the prostate brachytherapy is prostate rotating shield brachytherapy (RSBT).
6 . The method of claim 1 wherein the prostate brachytherapy is high-dose-rate brachytherapy (HDR-BT).
7 . The method of claim 1 wherein the convex optimization problem includes a dose escalation goal and a urethra sparing goal.
8 . A radiation treatment planning system for prostate brachytherapy for use with a radiation delivery device configured to use a plurality of needles inserted into a prostate of a patient, the radiation treatment planning system comprising:
a processor;
a memory operatively connected to the processor having instructions stored thereon for execution by the processor to:
obtain imagery of the prostate of the patient;
generate a needle pool for prostate brachytherapy treatment of the patient based on the imagery of the prostate of the patient;
determine an optimum prostate brachytherapy treatment plan for the patient by iteratively removing needles from the needle pool by forming and computationally solving a convex optimization problem wherein the convex optimization problem uses a quadratic dosimetric penalty function, dwell time regularization by total variation, and a block sparsity regularization term; and
generate an output for conveying the optimum prostate brachytherapy treatment plan to the radiation delivery device.
9 . The radiation treatment planning system of claim 8 wherein the output is in a human-readable form conveying the optimum prostate brachytherapy treatment plan for the patient.
10 . The radiation treatment planning system of claim 8 wherein the imagery is magnetic resonance imagery.
11 . The radiation treatment planning system of claim 8 wherein the imagery of the prostate of the patient is obtained from a portable magnetic resonance imaging (MRI) scanner.
12 . The radiation treatment planning system of claim 8 wherein the computationally solving the convex optimization problem is performed using a proximal operator graph solver (POGS).
13 . The radiation treatment planning system of claim 8 wherein the prostate brachytherapy is prostate rotating shield brachytherapy (RSBT).
14 . The radiation treatment planning system of claim 8 wherein the prostate brachytherapy is high-dose-rate brachytherapy (HDR-BT).
15 . The radiation treatment planning system of claim 8 wherein the convex optimization problem includes a dose escalation goal and a urethra sparing goal.
16 . A system for prostate brachytherapy comprising:
a plurality of needles;
a radiation delivery device configured to deliver radiation according to an optimum prostate brachytherapy treatment plan to use the plurality of needles when inserted into a prostate of a patient to delivery radiation thereto;
a processor;
a memory operatively connected to the processor having instructions stored thereon for execution by the processor to:
obtain imagery of the prostate of the patient;
generate a needle pool for prostate brachytherapy treatment of the patient based on the imagery of the prostate of the patient; and
determine the optimum prostate brachytherapy treatment plan for the patient by iteratively removing needles from the needle pool by forming and computationally solving a convex optimization problem wherein the convex optimization problem uses a quadratic dosimetric penalty function, dwell time regularization by total variation, and a block sparsity regularization term;
generate an output conveying the optimum prostrate brachytherapy treatment plan to the radiation delivery device to deliver radiation according to the optimum prostate brachytherapy treatment plan.
17 . The system of claim 16 further comprising an imaging device for acquiring the imagery of the prostate.
18 . The system of claim 17 wherein the imaging device is a magnetic resonance imaging (MRI) scanner.