MR thermometry for focused ultrasound monitoring utilizing model predictive filtering and ultrasound beam modeling

Comparison study of reconstruction algorithms for volumetric necrosis maps from 2D multi-slice GRE thermometry images

Cancer is a disease which requires a significant amount of careful medical attention. For minimally-invasive thermal ablation procedures, the monitoring of heat distribution is one of the biggest challenges. In this work, three approaches for volumetric heat map reconstruction (Delauney triangulation, minimum volume enclosing ellipsoids (MVEE) and splines) are presented based on uniformly distributed 2D MRI phase images rotated around the applicator’s main axis. We compare them with our previous temperature interpolation method with respect to accuracy, robustness and adaptability. All approaches are evaluated during MWA treatment on the same data sets consisting of 13 ex vivo bio protein phantoms, including six phantoms with simulated heat sink effects. Regarding accuracy, the DSC similarity results show a strong trend towards the MVEE (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0.80\pm 0.03$$\end{document}0.80±0.03) and the splines (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0.77\pm 0.04$$\end{document}0.77±0.04) method compared to the Delauney triangulation (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0.75\pm 0.02$$\end{document}0.75±0.02) or the temperature interpolation (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0.73\pm 0.07$$\end{document}0.73±0.07). Robustness is increased for all three approaches and the adaptability shows a significant trend towards the initial interpolation method and the splines. To overcome local inhomogeneities in the acquired data, the use of adaptive simulations should be considered in the future. In addition, the transfer to in vivo animal experiments should be considered to test for clinical applicability.

Thermal Memory Based Photoacoustic Imaging of Temperature

Temperature mapping is essential in many biomedical studies and interventions to precisely control the tissue's thermal conditions for optimal treatment efficiency and minimal side effects. Based on the Grüneisen parameter's temperature dependence, photoacoustic (PA) imaging can provide relative temperature measurement, but it has been traditionally challenging to measure absolute temperatures without knowing the baseline temperature, especially in deep tissues with unknown optical and acoustic properties. Here, we report a new thermal-energy-memory-based photoacoustic thermometry (TEMPT). By illuminating the tissue with a burst of nanosecond laser pulses, TEMPT exploits the temperature dependence of the thermal energy lingering, which is probed by the corresponding PA signals acquired within the thermal confinement. A self-normalized ratiometric measurement cancels out temperature-irrelevant quantities and estimates the Grüneisen parameter. The temperature can then be evaluated, given the tissue's temperature-dependent Grüneisen parameter, mass density, and specific heat capacity. Unlike the conventional PA thermometry, TEMPT does not require the knowledge of tissue's baseline temperature, nor the optical properties. We have developed a mathematical model to describe the temperature dependence in TEMPT. We have demonstrated the feasibility of the temperature evaluation on tissue phantoms at 1.5 cm depth within a clinically relevant temperature range. Finally, as proof-of-concept, we applied TEMPT for temperature mapping during focused ultrasound treatment in mice in vivo at 2 mm depth. As a generic temperature mapping method, TEMPT is expected to find applications in thermotherapy of cancers on small animal models.