Document Detail

Effects of respiratory liver motion on heating for gated and model-based motion-compensated high-intensity focused ultrasound ablation.
MedLine Citation:
PMID:  22003668     Owner:  NLM     Status:  In-Process    
PURPOSE: To quantify the effects of respiratory motion on high-intensity focused ultrasound heating of liver tissue by comparing the simulated ablation using a conventional respiratory gating versus a MR-model-based motion compensation approach.
METHODS: To measure liver motion, dynamic free-breathing abdominal MR scans were acquired for five volunteers. Deformable registration was used to calculate continuous motion models, and tissue heating at a moving single focus was computed in 3-D by solving the bioheat equation. Ablated volume ratios with respect to the static case, V(ab), were determined for a range of exposure times t(exp) and heating rates r.
RESULTS: To achieve V(ab) > 90% required t(exp) < 0.5s and r > 120 degrees C/s when gating, whereas t(exp) < 1s and r > 60 degrees C/s for motion-compensation.
CONCLUSIONS: Accurate compensation for respiratory motion is important for efficient tissue ablation. Model-based motion compensation allows substantially lower heating rates than gating, reducing the risk of skin burns and focal boiling.
Erik-Jan Rijkhorst; Ian Rivens; Gail ter Haar; David Hawkes; Dean Barratt
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention     Volume:  14     ISSN:  -     ISO Abbreviation:  Med Image Comput Comput Assist Interv     Publication Date:  2011  
Date Detail:
Created Date:  2011-10-18     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101249582     Medline TA:  Med Image Comput Comput Assist Interv     Country:  Germany    
Other Details:
Languages:  eng     Pagination:  605-12     Citation Subset:  IM    
Centre for Medical Image Computing, University College London, London, UK.
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