Dr. MyungHo In Profile

Dr. MyungHo In

at Mayo Clinic

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Publications (1)

Proceedings Article | 1 April 2024 Presentation + Paper

Thermometry mapping during CT-guided thermal ablations: sensitivity and clinical feasibility using spectral CT

Kuan Zhang, Andrea Ferrero, MyungHo In, Christopher Favazza

Proceedings Volume 12925, 129251R (2024) https://doi.org/10.1117/12.3008671

KEYWORDS: Temperature metrology, Ablation, Thermometry, Computed tomography, Reconstruction algorithms, X-ray computed tomography, Medical image reconstruction, Data modeling, Temperature sensors, X-rays

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In this work, we aimed to investigate the sensitivity of spectral CT to changes in temperatures. Moreover, we assessed the accuracy and precision of spectral CT to provide temperature mapping within the treatment volume in CT-guided hypo- and hyper-thermal tumor ablations. Leveraging optical temperature sensors and a 3D printed phantom holder designed to precisely position metallic thermal ablation applicators and reduce the associated image artifacts, we collected spectral CT data spanning a wide range of temperatures (-100 to +90°C) and used a robust theoretical model to fit these distributions for both conventional and spectral CT data. From these expressions, look-up tables that map temperature to CT were generated within the temperature range of interest for cryoablation and hyperthermal ablations, respectively. Consistent with expectations from theoretical models for a water-based gel material, we demonstrated similar sensitivity for conventional and spectral results, with a 3-fold increase in sensitivity in the heating temperature range compared to frozen material. Next, we used repeated scans of a multi-energy phantom to determine the imaging protocol that yield the highest precision (standard deviation of average signal through repeated measurements) in CT signal at the radiation dose levels used in our practice for treatment monitoring during thermal ablation. Our data revealed the complex interplay among radiation dose, image noise, and material decomposition accuracy for spectral data. With a 5mGy CTDIvol limit, we obtained a standard deviation of the average value within a 3³ mm³ VOI value of 0.85HU-equivalent for electron density images, corresponding to a precision of 7°C and 2°C for frozen and heated gel, respectively. Conventional image data, including with the application of an in-house CNN denoising algorithm, was unable to reduce the standard deviation of ROI measurements below 1HU. This information was used to develop a clinical-ready CT thermometry protocol that was subsequently independently tested on hyper-thermal measurements, demonstrating an accuracy (root mean square error) in temperature estimates of <8°C for heated gel.

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