Model-based PRFS thermometry using fat as the internal reference and the extended Prony algorithm for model fitting
Autor: | Cheng Li, Wen Qin, Dehe Weng, Kui Ying, Kuncheng Li, Xinyi Pan |
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Rok vydání: | 2010 |
Předmět: |
Materials science
Proton resonance frequency Field (physics) Monte Carlo method Biomedical Engineering Biophysics Reproducibility of Results Model fitting Magnetic Resonance Imaging Sensitivity and Specificity Signal Imaging phantom Body Temperature Adipose Tissue Liver Reference Values Thermography Geese Image Interpretation Computer-Assisted Animals Radiology Nuclear Medicine and imaging Spectral data Algorithm Algorithms Gradient echo |
Zdroj: | Magnetic Resonance Imaging. 28:418-426 |
ISSN: | 0730-725X |
Popis: | A model-based proton resonance frequency shift (PRFS) thermometry method was developed to significantly reduce the temperature quantification errors encountered in the conventional phase mapping method and the spatiotemporal limitations of the spectroscopic thermometry method. Spectral data acquired using multi-echo gradient echo (GRE) is fit into a two-component signal model containing temperature information and fat is used as the internal reference. The noniterative extended Prony algorithm is used for the signal fitting and frequency estimate. Monte Carlo simulations demonstrate the advantages of the method for optimal water-fat separation and temperature estimation accuracy. Phantom experiments demonstrate that the model-based method effectively reduces the interscan motion effects and frequency disturbances due to the main field drift. The thermometry result of ex vivo goose liver experiment with high intensity focused ultrasound (HIFU) heating was also presented in the paper to indicate the feasibility of the model-based method in real tissue. |
Databáze: | OpenAIRE |
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