Temperature estimation for MR-guided microwave hyperthermia using block-based compressed sensing.

Mild hyperthermia has been clinically employed as an adjuvant for radiation/chemotherapy and is under investigation for precise thermally-mediated delivery of cancer therapeutic agents. Magnetic Resonance Imaging (MRI) facilitates non-invasive, real-time spatial thermometry for monitoring and guiding hyperthermia procedures. Long image acquisition time during MR-guided hyperthermia may fail to capture rapid changes in temperature. This may lead to unwanted heating of healthy tissue and/or temperature rise above hyperthermic range. We have developed a block-based compressed sensing approach to reconstruct volumetric MR-derived microwave hyperthermia temperature profiles using a subset of measured data. This algorithm exploits the sparsity of MR images due to the presence of inter- and intra-slice correlation of hyperthermic MR-derived temperature profiles. We have evaluated the performance of our developed algorithm on a phantom and in vivo in mice using previously implemented microwave applicators. This algorithm reconstructs 3D temperature profiles with PSNR of 33 dB - 49 dB in comparison to the original profiles. In summary, this study suggests that microwave hyperthermia induced temperature profiles can be reconstructed using subsamples to reduce MR image acquisition time.