Motion Detection in Image-Guided Thermal Therapy Using Trained Machine-Learning Model

A method for controlling a delivery of thermal therapy, comprising:

• inserting a thermal therapy applicator into a mammal;
• capturing first magnetic resonance (MR) images, with an MR imaging system, of the mammal at a first time, the first MR images representing first cross-sectional images of the mammal including an inserted thermal therapy applicator, the first cross-sectional images at respective spatial locations in the mammal;
• segmenting the first MR images with a trained machine-learning (ML) model running on the computer, the trained ML model having been trained with reference segmented MR images that include a reference thermal therapy applicator;
• determining, with the computer, a respective first shape and/or a respective first position of the inserted thermal therapy applicator at each spatial location;
• applying thermal therapy, with the inserted thermal therapy applicator, to a target volume in the mammal;
• and
• while applying the thermal therapy:
• a. capturing second MR images, with the MR imaging system, of the mammal at a second time, the second MR images representing second cross-sectional images of the mammal and the inserted thermal therapy applicator, the second cross-sectional images at the respective spatial locations;
• b. segmenting the second MR images with the trained ML model;
• c. determining, with the computer, a respective second shape and/or a respective second position of the inserted thermal therapy applicator at each spatial location;
• d. calculating, with the computer, a displacement of the inserted thermal therapy applicator at each spatial location by comparing the respective first and second shapes and/or the respective first and second positions of the inserted thermal therapy applicator at each spatial location;
• and
• e. producing a notification, with the computer, when the displacement of the inserted thermal therapy applicator is greater than a predetermined threshold value.

A system for controlling a delivery of thermal therapy, comprising:

• a magnetic resonance (MR) imaging system;
• a computer in communication with the MR imaging system, the computer including:
• one or more processors;
• and
• non-volatile computer-readable memory operably coupled to the one or more processors, the non-volatile computer-readable memory storing computer-readable instructions that, when executed by the one or more processors, cause the one or more processors to:
• receive first MR images of a mammal at a first time, the first MR images representing first cross-sectional images of the mammal including an inserted thermal therapy applicator, the first cross-sectional images at respective spatial locations in the mammal;
• segment the first MR images with a trained machine-learning (ML) model running on the computer, the trained ML model having been trained with reference segmented MR images that include a reference thermal therapy applicator;
• determine a respective first shape and/or a respective first position of the inserted thermal therapy applicator at each spatial location;
• while the thermal therapy is applied with the inserted thermal therapy applicator:
• a. receive second MR images of the mammal at a second time, the second MR images representing second cross-sectional images of the mammal and the inserted thermal therapy applicator, the second cross-sectional images at the respective spatial locations;
• b. segment the second MR images with the trained ML model;
• c. determine a respective second shape and/or a respective second position of the inserted thermal therapy applicator at each spatial location;
• d. calculate a displacement of the inserted thermal therapy applicator at each spatial location by comparing the respective first and second shapes and/or the respective first and second positions of the inserted thermal therapy applicator at each spatial location;
• and
• e. produce a notification when the displacement of the inserted thermal therapy applicator is greater than a predetermined threshold value.