Extended Kalman filtering for MR-thermometry guided high intensity focused ultrasound using the bio heat transfer equation

Roujol, Sébastien; Hey, S.; Moonen, C.; Ries, Mario

doi:10.1109/icip.2011.6116094

Cited by 2 publications

(1 citation statement)

References 18 publications

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“…Johnson and Saidel 5 began research in the field of interventional and adaptive simulation in 2002 by analyzing 3D simulation for thermal processes and conducting one of the first theoretical studies. Based on this work, they and other researchers 6,7 came to the same two conclusions. First, a continuous simulation of the heat distribution is able to increase the spatial resolution of a volumetric ablation monitoring.…”

Section: Related Worksupporting

confidence: 69%

Adaptive simulation of 3D thermometry maps for interventional MR-guided tumor ablation using Pennes’ bioheat equation and isotherms

Alpers

Rötzer

Gutberlet

et al. 2022

Sci Rep

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Minimally-invasive thermal ablation procedures have become clinically accepted treatment options for tumors and metastases. Continuous and reliable monitoring of volumetric heat distribution promises to be an important condition for successful outcomes. In this work, an adaptive bioheat transfer simulation of 3D thermometry maps is presented. Pennes’ equation model is updated according to temperature maps generated by uniformly distributed 2D MR phase images rotated around the main axis of the applicator. The volumetric heat diffusion and the resulting shape of the ablation zone can be modelled accurately without introducing a specific heat source term. Filtering the temperature maps by extracting isotherms reduces artefacts and noise, compresses information of the measured data and adds physical a priori knowledge. The inverse heat transfer for estimating values of the simulated tissue and heating parameters is done by reducing the sum squared error between these isotherms and the 3D simulation. The approach is evaluated on data sets consisting of 13 ex vivo bio protein phantoms, including six perfusion phantoms with simulated heat sink effects. Results show an overall average Dice score of 0.89 ± 0.04 (SEM < 0.01). The optimization of the parameters takes 1.05 ± 0.26 s for each acquired image. Future steps should consider the local optimization of the simulation parameters instead of a global one to better detect heat sinks without a priori knowledge. In addition, the use of a proper Kalman filter might increase robustness and accuracy if combined with our method.

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Section: Related Worksupporting

confidence: 69%

Adaptive simulation of 3D thermometry maps for interventional MR-guided tumor ablation using Pennes’ bioheat equation and isotherms

Alpers

Rötzer

Gutberlet

et al. 2022

Sci Rep

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Robust Adaptive Extended Kalman Filtering for Real Time MR-Thermometry Guided HIFU Interventions

Roujol

Senneville

Hey

et al. 2012

IEEE Trans. Med. Imaging

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Abstract-Real time magnetic resonance (MR) thermometry is gaining clinical importance for monitoring and guiding high intensity focused ultrasound (HIFU) ablations of tumorous tissue. The temperature information can be employed to adjust the position and the power of the HIFU system in real time and to determine the therapy endpoint.The requirement to resove both physiological motion on mobile organs and the rapid temperature variations induced by state-ofthe art high-power HIFU systems requires fast MRI-acquisition schemes, which are generally hampered by low signal to noise ratios (SNR). This directly limits the precision of real time MR-thermometry and thus in many cases the feasability of sophisticated control algorithms. To overcome these limitations, temporal filtering of the temperature has been suggested in the past, which has generally an adverse impact on the accuracy and latency of the filtered data.Here, we propose a novel model based digital filter combining an extended Kalman filter (EKF) with a predictive model of the temperature based on the bio heat transfer equation. This filter aims to improve the precision of MR-thermometry while monitoring and adapting its impact on the accuracy using the formalism of adaptive extended Kalman filtering. An additional outlier rejection addresses the problem of sparse artifacted temperature points. The filter was evaluated and compared to a matched FIR filter using simulated data, HIFU experiments on phantoms and in vivo data obtained during HIFU ablations on porcine kidneys. The filter provides improved artefact and noise reduction, while having a minimal impact on accuracy and latency.

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Extended Kalman filtering for MR-thermometry guided high intensity focused ultrasound using the bio heat transfer equation

Cited by 2 publications

References 18 publications

Adaptive simulation of 3D thermometry maps for interventional MR-guided tumor ablation using Pennes’ bioheat equation and isotherms

Adaptive simulation of 3D thermometry maps for interventional MR-guided tumor ablation using Pennes’ bioheat equation and isotherms

Robust Adaptive Extended Kalman Filtering for Real Time MR-Thermometry Guided HIFU Interventions

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