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Daisuke Kokuryo

Publications and source records attributed to Daisuke Kokuryo.

2 recordsLinked to original sources

Near-real-time feedback control system for liver thermal ablations based on self-referenced temperature imaging.

Our challenge was to design and implement a dedicated temperature imaging feedback control system to guide and assist in a thermal liver ablation procedure in a double-donut 0.5T open MR scanner. This system has near-real-time feedback capability based on a newly developed "self-referenced" temperature imaging method using "moving-slab" and complex-field-fitting techniques. Two phantom validation studies and one ex vivo experiment were performed to compare the newly developed self-referenced method with the conventional subtraction method and evaluate the ability of the feedback control system in the same MR scanner. The near-real-time feedback system was achieved by integrating the following primary functions: (1) imaging of the moving organ temperature; (2) on-line needle tip tracking; (3) automatic turn-on/off the heating devices; (4) a Windows operating system-based novel user-interfaces. In the first part of the validation studies, microwave heating was applied in an agar phantom using a fast spoiled gradient recalled echo in a steady state sequence. In the second part of the validation and ex vivo study, target visualization, treatment planning and monitoring, and temperature and thermal dose visualization with the graphical user interface of the thermal ablation software were demonstrated. Furthermore, MR imaging with the "self-referenced" temperature imaging method has the ability to localize the hot spot in the heated region and measure temperature elevation during the experiment. In conclusion, we have demonstrated an interactively controllable feedback control system that offers a new method for the guidance of liver thermal ablation procedures, as well as improving the ability to assist ablation procedures in an open MR scanner.

Algorithms↗

Optimization of self-reference thermometry using complex field estimation.

Referenceless, or self-reference, thermometry is a technique for mapping temperature differences in the region of interest (ROI) using the baseline phase estimated by extrapolating the field in the surrounding region for estimation (RFE) and subtracting the estimated baseline from the measured field. In the present work a self-reference technique based on complex field estimation using 2D polynomials comprising complex-valued coefficients was proposed and optimized. Numerical simulations with a Gaussian-profiled phase distribution demonstrated that the ROI radius had to be 2.3-2.5 times the standard deviation (SD) of the Gaussian function in order to keep the error below 8% of the peak phase change. The area ratio between the ROI and the RFE had to be larger than 2.0 to maintain the error level. Based on the simulations, and phantom and volunteer experiments, the complex-based method with independently optimized polynomial orders for the two spatial dimensions was compared with the phase-based method using the similar-order optimization strategy. The complex-based method appeared to be useful when phase unwrapping was not removed. Otherwise, the phase-based method yielded equivalent results with less polynomial orders.

Body Temperature↗