Image-Based Dynamic Modeling of Thermal Therapies Using Proper Orthogonal Decomposition of Magnetic Resonance Thermometry Images

摘要

Planning and model-based control of noninvasive thermal therapies require thermal response and power deposition models of the target, which are site- and patient-specific. In this paper, we propose an image-based approach to the identification of low-dimensional model of noninvasive thermal treatments using MRI temperature imaging. The models of thermal response and specific absorption rate (SAR) of noninvasively transduced energy by the target and the surrounding normal tissue are identified in the reduced basis of proper orthogonal decomposition of thermal images. The developed methods are less sensitive to temporal and spatial noises in image data, slow image acquisition rate, and are suitable for adaptive model re-identification by recursively utilizing newly acquired images. The proposed concepts and developed methods are tested using the results of MR thermal imaging experiments with tissue phantom noninvasively heated by focused ultrasound.