PURPOSE: To describe, assess, and implement a simple precision estimation framework for optimization of spin-lock time (TSL) sampling schedules for quantitative T1ρ mapping using a mono-exponential signal model. MATERIALS AND METHODS: A method is described for estimating T1ρ precision, and a cost function based on the precision estimates is evaluated to determine efficient TSL sampling schedules. The validity of the framework was tested by imaging a phantom with various sampling schedules and comparing theoretical and experimental precision values. The method utility was demonstrated with in vivo T1ρ mapping of brain tissue using a similar procedure as the phantom experiment. To assist investigators, optimal sampling schedules are tabulated for various tissue types and an online calculator is implemented. RESULTS: Theoretical and experimental precision values followed similar trends for both the phantom and in vivo experiments. The mean absolute percentage error (MAPE) of theoretical estimates of T1ρ map signal-to-noise ratio (SNR) was typically 5% in the phantom experiment and 33% in the in vivo demonstration. In both experiments, optimal TSL schedules yielded greater T1ρ map SNR efficiency than typical schedules. CONCLUSION: The framework can be used to improve the imaging efficiency of T1ρ mapping protocols and to guide selection of imaging parameters.
PURPOSE: To describe, assess, and implement a simple precision estimation framework for optimization of spin-lock time (TSL) sampling schedules for quantitative T1ρ mapping using a mono-exponential signal model. MATERIALS AND METHODS: A method is described for estimating T1ρ precision, and a cost function based on the precision estimates is evaluated to determine efficient TSL sampling schedules. The validity of the framework was tested by imaging a phantom with various sampling schedules and comparing theoretical and experimental precision values. The method utility was demonstrated with in vivo T1ρ mapping of brain tissue using a similar procedure as the phantom experiment. To assist investigators, optimal sampling schedules are tabulated for various tissue types and an online calculator is implemented. RESULTS: Theoretical and experimental precision values followed similar trends for both the phantom and in vivo experiments. The mean absolute percentage error (MAPE) of theoretical estimates of T1ρ map signal-to-noise ratio (SNR) was typically 5% in the phantom experiment and 33% in the in vivo demonstration. In both experiments, optimal TSL schedules yielded greater T1ρ map SNR efficiency than typical schedules. CONCLUSION: The framework can be used to improve the imaging efficiency of T1ρ mapping protocols and to guide selection of imaging parameters.
Authors: Casey P Johnson; Gary E Christensen; Jess G Fiedorowicz; Merry Mani; Joseph J Shaffer; Vincent A Magnotta; John A Wemmie Journal: Bipolar Disord Date: 2018-01-07 Impact factor: 6.744
Authors: Shafik N Wassef; John Wemmie; Casey P Johnson; Hans Johnson; Jane S Paulsen; Jeffrey D Long; Vincent A Magnotta Journal: Mov Disord Date: 2015-03-29 Impact factor: 10.338
Authors: Casey P Johnson; Hye-Young Heo; Daniel R Thedens; John A Wemmie; Vincent A Magnotta Journal: Magn Reson Imaging Date: 2014-08-02 Impact factor: 2.546
Authors: Nana Owusu; Casey P Johnson; William Kearney; Dan Thedens; John Wemmie; Vincent A Magnotta Journal: NMR Biomed Date: 2019-11-19 Impact factor: 4.044