TY - GEN
T1 - Physics-Based Simulation to Enable Ultrasound Monitoring of HIFU Ablation
T2 - 21st International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2018
AU - Audigier, Chloé
AU - Kim, Younsu
AU - Ellens, Nicholas
AU - Boctor, Emad M.
N1 - Publisher Copyright:
© 2018, Springer Nature Switzerland AG.
PY - 2018
Y1 - 2018
N2 - High intensity focused ultrasound (HIFU) is used to ablate pathological tissue non-invasively, but reliable and real-time thermal monitoring is crucial to ensure a safe and effective procedure. It can be provided by MRI, which is an expensive and cumbersome modality. We propose a monitoring method that enables real-time assessment of temperature distribution by combining intra-operative ultrasound (US) with physics-based simulation. During the ablation, changes in acoustic properties due to rising temperature are monitored using an external US sensor. A physics-based HIFU simulation model is then used to generate 3D temperature maps at high temporal and spatial resolutions. Our method leverages current HIFU systems with external low-cost and MR-compatible US sensors, thus allowing its validation against MR thermometry, the gold-standard clinical temperature monitoring method. We demonstrated in silico the method feasibility, performed sensitivity analysis and showed experimentally its applicability on phantom data using a clinical HIFU system. Promising results were obtained: a mean temperature error smaller than 1.5°C was found in four experiments.
AB - High intensity focused ultrasound (HIFU) is used to ablate pathological tissue non-invasively, but reliable and real-time thermal monitoring is crucial to ensure a safe and effective procedure. It can be provided by MRI, which is an expensive and cumbersome modality. We propose a monitoring method that enables real-time assessment of temperature distribution by combining intra-operative ultrasound (US) with physics-based simulation. During the ablation, changes in acoustic properties due to rising temperature are monitored using an external US sensor. A physics-based HIFU simulation model is then used to generate 3D temperature maps at high temporal and spatial resolutions. Our method leverages current HIFU systems with external low-cost and MR-compatible US sensors, thus allowing its validation against MR thermometry, the gold-standard clinical temperature monitoring method. We demonstrated in silico the method feasibility, performed sensitivity analysis and showed experimentally its applicability on phantom data using a clinical HIFU system. Promising results were obtained: a mean temperature error smaller than 1.5°C was found in four experiments.
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U2 - 10.1007/978-3-030-00937-3_11
DO - 10.1007/978-3-030-00937-3_11
M3 - Conference contribution
AN - SCOPUS:85053821162
SN - 9783030009366
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 89
EP - 97
BT - Medical Image Computing and Computer Assisted Intervention – MICCAI 2018 - 21st International Conference, 2018, Proceedings
A2 - Frangi, Alejandro F.
A2 - Fichtinger, Gabor
A2 - Schnabel, Julia A.
A2 - Alberola-López, Carlos
A2 - Davatzikos, Christos
PB - Springer Verlag
Y2 - 16 September 2018 through 20 September 2018
ER -