Artificial intelligence modeling for radiation therapy dose distribution analysis

Patent metadata

Field	Value
Publication number	US-12121747-B2
Application number	US-202117208781-A
Country	US
Kind code	B2
Filing date	Mar 22, 2021
Priority date	Mar 22, 2021
Publication date	Oct 22, 2024
Grant date	Oct 22, 2024

Abstract

Disclosed herein are methods and systems to optimize a radiation therapy treatment plan using dose distribution values predicted via a trained artificial intelligence model. A server trains the AI model using a training dataset comprising data associated with a plurality of previously implemented radiation therapy treatments on a plurality of previous patients and dose distributions associated with one or more organs of each previous patient. The server then executes the trained AI model to predict dose distribution for a patient. The server then displays a heat map illustrating the predicted values, transmits the predicted values to a plan optimizer to generate an optimized treatment plan for the patient, and/or transmits an alert when a treatment plan generated by a plan optimizer deviates from rules and thresholds indicated within the patient's plan objectives.

First claim

What we claim is:

1. A method comprising:
retrieving, by a processor, a radiation therapy treatment plan for a patient comprising a plan dose distribution value associated with the patient;
executing, by the processor using the radiation therapy treatment plan, an artificial intelligence model to predict a predicted dose distribution value for an anatomical region of the patient based at least in part on the plan dose distribution value, the artificial intelligence model trained using a training dataset comprising data associated with a plurality of previously implemented radiation therapy treatments on a plurality of previous patients and dose distributions associated with one or more organs of each previous patient; and
transmitting, by the processor, a notification when the predicted dose distribution value exceeds a threshold corresponding to a criterion to identify a first region indicating a hot spot or a second region indicating a cold spot.

2. The method of claim 1 , wherein the threshold is retrieved from a plan objective associated with the patient.

3. The method of claim 1 , wherein the threshold corresponds to at least one dose distribution value within an existing treatment plan generated by a plan optimizer software solution.

4. The method of claim 1 , wherein the radiation therapy treatment plan is generated by a plan optimizer application and further comprising:
transmitting, by the processor, data associated with the at least one dose distribution value predicted by the artificial intelligence model to the plan optimizer application.

5. The method of claim 1 , wherein the artificial intelligence model is trained using dose-volume histograms of previous patients and their corresponding first and second thresholds.

6. The method of claim 1 , wherein the artificial intelligence model is trained using a set of medical images associated with previous patients.

7. The method of claim 6 , wherein the processor revises at least one medical image from the set of medical images that includes a particular object.

8. The method of claim 1 , wherein the notification comprises a heat map having a set of segments where each segment corresponds to a first coordinate and a second coordinate of the anatomical region of the patient, wherein a visual attribute of each segment corresponds to a calculated dose distribution value.

9. A computer system comprising:
a server comprising a processor and a non-transitory computer-readable medium containing instructions that when executed by the processor causes the processor to perform operations comprising:
retrieve a radiation therapy treatment plan for a patient comprising a plan dose distribution value associated with the patient;
execute, using the radiation therapy treatment plan, an artificial intelligence model to predict a predicted dose distribution value for an anatomical region of the patient based at least in part on the plan dose distribution value, the artificial intelligence model trained using a training dataset comprising data associated with a plurality of previously implemented radiation therapy treatments on a plurality of previous patients and dose distributions associated with one or more organs of each previous patient; and
transmit a notification when the predicted dose distribution value exceeds a threshold corresponding to a criterion to identify a first region indicating a hot spot or a second region indicating a cold spot.

10. The computer system of claim 9 , wherein the threshold is retrieved from a plan objective associated with the patient.

11. The computer system of claim 9 , wherein the threshold corresponds to at least one dose distribution value within an existing treatment plan generated by a plan optimizer software solution.

12. The computer system of claim 9 , wherein the radiation therapy treatment plan is generated by a plan optimizer application and the instructions further cause the processor to:
transmit the at least one dose distribution value predicted by the artificial intelligence model to the plan optimizer application.

13. The computer system of claim 9 , wherein the artificial intelligence model is trained using dose-volume histograms of previous patients and their corresponding first and second thresholds.

14. The computer system of claim 9 , wherein the artificial intelligence model is trained using a set of medical images associated with previous patients.

15. The computer system of claim 14 , wherein the instructions are configured to further cause the processor to revise at least one medical image from the set of medical images that includes a particular object.

16. The computer system of claim 9 , wherein the notification comprises a heat map having a set of segments where each segment corresponds to a first coordinate and a second coordinate of the anatomical region of the patient, wherein a visual attribute of each segment corresponds to a calculated dose distribution value.

17. A computer system comprising:
a processor in communication with an artificial intelligence model and an electronic device, the processor configured to:
retrieve a radiation therapy treatment plan for a patient comprising a plan dose distribution value associated with the patient;
execute, using the radiation therapy treatment plan, the artificial intelligence model to predict a predicted dose distribution value for an anatomical region of the patient based at least in part on the plan dose distribution value, the artificial intelligence model trained using a training dataset comprising data associated with a plurality of previously implemented radiation therapy treatments on a plurality of previous patients and dose distributions associated with one or more organs of each previous patient; and
transmit a notification, to the electronic device, when the predicted dose distribution value exceeds a threshold corresponding to a criterion to identify a first region indicating a hot spot or a second region indicating a cold spot.

18. The computer system of claim 17 , wherein the threshold is retrieved from a plan objective associated with the patient.

Assignees

• Siemens Healthineers Int Ag

Inventors

• Peltola Jarkko
• Rusanen Marko
• Pietila Ville

Classifications

• A61N5/1038

  taking into account previously administered plans applied to the same patient, i.e. adaptive radiotherapy · CPC title

• G06N20/00

  Machine learning · CPC title

• G16H30/40

  for processing medical images, e.g. editing · CPC title

• G16H20/40

  relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture · CPC title

• A61N2005/1041

  using a library of previously administered radiation treatment applied to other patients · CPC title