Automated magnetic resonance image segmentation for ultrasound thermal therapy control

1. A method for controlling delivery of thermal therapy, comprising:

acquiring magnetic resonance (MR) images, with an MR imaging system, of tissue proximal to a target treatment region in a patient, the tissue including a non-spatially uniform subcutaneous fat layer;

in a computer comprising a hardware-based processor, automatically determining an actual thickness of the subcutaneous fat layer using a trained neural network, the neural network trained using manually-segmented MR images from previous patients;

in the computer, automatically adjusting a set of treatment parameters based on the actual thickness of the subcutaneous fat layer; and

delivering thermal therapy to the target treatment region with a high-intensity focused ultrasound (HIFU) system based on the adjusted set of treatment parameters.

2. The method of claim 1 , wherein the set of treatment parameters comprises an input to a safety control algorithm.

3. The method of claim 2 , wherein the safety control algorithm ensures a predetermined maximum temperature and/or a predetermined maximum thermal dose of tissue between the target treatment region and a therapeutic applicator of the HIFU system.

4. The method of claim 2 , wherein the safety control algorithm increases a cooldown time between thermal therapy sonications when the actual thickness of the subcutaneous fat layer is higher than a predetermined thickness, the predetermined thickness corresponding to an average subcutaneous fat layer thickness for the gender of the patient.

5. The method of claim 2 , wherein the safety control algorithm decreases a cooldown time between thermal therapy sonications when the actual thickness of the subcutaneous fat layer is lower than the predetermined thickness.

6. The method of claim 1 , wherein the set of treatment parameters comprises a frequency of ultrasound energy generated by the HIFU system.

7. The method of claim 1 , wherein the set of treatment parameters comprises a power of ultrasound energy generated by the HIFU system.

8. The method of claim 7 , wherein the power of the ultrasound energy increases when the actual thickness of the subcutaneous fat layer is higher than a predetermined thickness, the predetermined thickness corresponding to an average subcutaneous fat layer thickness for the gender of the patient.

9. The method of claim 8 , wherein the power of the ultrasound energy decreases when the actual thickness of the subcutaneous fat layer is lower than the predetermined thickness.

10. The method of claim 1 , wherein the set of treatment parameters comprises a relative phase of ultrasound energy generated by each ultrasound transducer element in an array of ultrasound transducer elements.

11. A system for delivering ultrasound thermal therapy comprising:

a magnetic resonance (MR) imaging system;

a high-intensity focused ultrasound (HIFU) system comprising an array of ultrasound transducer elements;

a computer comprising a hardware-based processor, the computer operatively coupled to the MR imaging system and to the HIFU system; and

a non-transitory storage medium comprising computer-readable instructions that, when executed by the processor, cause the processor to:

send a first output signal to the MR system to acquire MR images of tissue proximal to a target treatment region in a patient, the tissue including a non-spatially uniform subcutaneous fat layer,

automatically determine an actual thickness of the subcutaneous fat layer using a trained neural network, the neural network trained using manually-segmented MR images from previous patients,

adjust a set of treatment parameters based on the actual thickness of the subcutaneous fat layer, and

send a second output signal to the HIFU system to deliver thermal therapy to the target treatment region based on the adjusted set of treatment parameters.

12. The system of claim 11 , wherein the set of treatment parameters comprises an input to a safety control algorithm.

13. The system of claim 12 , wherein the safety control algorithm ensures a predetermined maximum temperature and/or a predetermined maximum thermal dose of tissue between the target treatment region and a therapeutic applicator of the HIFU system.

14. The system of claim 12 , wherein the safety control algorithm increases a cooldown time between thermal therapy sonications when the actual thickness of the subcutaneous fat layer is higher than a predetermined thickness, the predetermined thickness corresponding to an average subcutaneous fat layer thickness for the gender of the patient.

15. The system of claim 14 , wherein the safety control algorithm decreases a cooldown time between thermal therapy sonications when the actual thickness of the subcutaneous fat layer is lower than the predetermined thickness.

16. The system of claim 11 , wherein the set of treatment parameters comprises a frequency of ultrasound energy generated by the HIFU system.

17. The system of claim 11 , wherein the set of treatment parameters comprises a power of ultrasound energy generated by the HIFU system.

18. The system of claim 17 , wherein the power of the ultrasound energy increases when the thickness of the subcutaneous fat layer is higher than a predetermined thickness, the predetermined thickness corresponding to an average subcutaneous fat layer thickness for the gender of the patient.

19. The system of claim 18 , wherein the power of the ultrasound energy decreases when the thickness of the subcutaneous fat layer is lower than the predetermined thickness.

20. The system of claim 11 , wherein the set of treatment parameters comprises a relative phase of ultrasound energy generated by each ultrasound transducer element in the array of ultrasound transducer elements.