OBJECT: The aim of this paper is to characterize the noise propagation for MRI temperature change measurement with emphasis on finding the best echo time combinations that yield the lowest temperature noise. MATERIALS AND METHODS: A Cramer-Rao lower-bound (CRLB) calculation was used to estimate the temperature noise for a model of the MR signal in fat-water voxels. The temperature noise CRLB was then used to find a set of echo times that gave the lowest temperature change noise for a range of fat-water frequency differences, temperature changes, fat/water signal ratios, and T2* values. CRLB estimates were verified by Monte Carlo simulation and in phantoms using images acquired in a 1.5 T magnet. RESULTS: Results show that regions exist where the CRLB predicts minimal temperature variation as a function of the other variables. The results also indicate that the CRLB values calculated in this paper provide excellent guidance for predicting the variation of temperature measurements due to changes in the signal parameters. For three echo scans, the best noise characteristics are seen for TE values of 20.71, 23.71, and 26.71 ms. Results for five and seven echo scans are also presented in the text. CONCLUSION: The results present a comprehensive analysis of the effects of different scan parameters on temperature noise, potentially benefiting the selection of scan parameters for clinical MRI thermometry.
OBJECT: The aim of this paper is to characterize the noise propagation for MRI temperature change measurement with emphasis on finding the best echo time combinations that yield the lowest temperature noise. MATERIALS AND METHODS: A Cramer-Rao lower-bound (CRLB) calculation was used to estimate the temperature noise for a model of the MR signal in fat-water voxels. The temperature noise CRLB was then used to find a set of echo times that gave the lowest temperature change noise for a range of fat-water frequency differences, temperature changes, fat/water signal ratios, and T2* values. CRLB estimates were verified by Monte Carlo simulation and in phantoms using images acquired in a 1.5 T magnet. RESULTS: Results show that regions exist where the CRLB predicts minimal temperature variation as a function of the other variables. The results also indicate that the CRLB values calculated in this paper provide excellent guidance for predicting the variation of temperature measurements due to changes in the signal parameters. For three echo scans, the best noise characteristics are seen for TE values of 20.71, 23.71, and 26.71 ms. Results for five and seven echo scans are also presented in the text. CONCLUSION: The results present a comprehensive analysis of the effects of different scan parameters on temperature noise, potentially benefiting the selection of scan parameters for clinical MRI thermometry.
Authors: Ernest L Madsen; Maritza A Hobson; Gary R Frank; Hairong Shi; Jingfeng Jiang; Timothy J Hall; Tomy Varghese; Marvin M Doyley; John B Weaver Journal: Ultrasound Med Biol Date: 2006-06 Impact factor: 2.998
Authors: Huanzhou Yu; Ann Shimakawa; Charles A McKenzie; Ethan Brodsky; Jean H Brittain; Scott B Reeder Journal: Magn Reson Med Date: 2008-11 Impact factor: 4.668
Authors: Richard Kijowski; Michael A Woods; Kenneth S Lee; Kuya Takimi; Huanzhou Yu; Ann Shimakawa; Jean H Brittain; Scott B Reeder Journal: J Magn Reson Imaging Date: 2009-02 Impact factor: 4.813
Authors: Gavin Hamilton; Michael S Middleton; Mark Bydder; Takeshi Yokoo; Jeffrey B Schwimmer; Yuko Kono; Heather M Patton; Joel E Lavine; Claude B Sirlin Journal: J Magn Reson Imaging Date: 2009-07 Impact factor: 4.813
Authors: Philip K Lee; Lauren E Watkins; Timothy I Anderson; Guido Buonincontri; Brian A Hargreaves Journal: Magn Reson Med Date: 2019-05-26 Impact factor: 4.668
Authors: Dimitrios C Karampinos; Huanzhou Yu; Ann Shimakawa; Thomas M Link; Sharmila Majumdar Journal: Magn Reson Med Date: 2012-01-13 Impact factor: 4.668
Authors: Guanshu Liu; Qin Qin; Kannie W Y Chan; Yuguo Li; Jeff W M Bulte; Michael T McMahon; Peter C M van Zijl; Assaf A Gilad Journal: NMR Biomed Date: 2014-03 Impact factor: 4.044