  Over the past decades, thermal ablation procedures such as high intensity
focused ultrasound (HIFU) have been developed vaporize cancerous tissues in a
focal area. Thermal ablation has the potential to non-invasively eliminate
tumors and treat other medical conditions with high efficacy and better patient
outcomes. However, it is necessary for treatment to be coupled with real time
temperature monitoring in order to deliver sufficient thermal dosage to the
target while sparing surrounding, healthy tissues. To this end, computed
tomography (CT) has been explored to offer fine spatial resolution at a rapid
speed. However, current CT thermometry techniques are sensitive to
heterogeneous tissue properties, imaging noise, and artifacts. To address this
challenge, this paper utilizes the emerging photon-counting CT technology,
performs tomographic thermometry based on material decomposition, and obtains
excellent results in realistic numerical simulation. Specifically, three
algorithms were designed to decouple material composition and thermal expansion
from spectral CT reconstruction and compared in a comparative study. The best
algorithm, referred to as the one-step algorithm, uniquely finds both material
decomposition and the associated temperature at the same time in a closed form
solution, which is robust to changes in tissue composition and generates
temperature predictions with centigrade accuracy under realistic CT image noise
levels.
