Calvin B Shaw1,2, Jens H Jensen1,2, Rachael L Deardorff1,2, Maria Vittoria Spampinato2, Joseph A Helpern1,2,3,4. 1. Center for Biomedical Imaging, Medical University of South Carolina, Charleston, South Carolina, USA. 2. Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, South Carolina, USA. 3. Department of Neurosciences, Medical University of South Carolina, Charleston, South Carolina, USA. 4. Department of Neurology, Medical University of South Carolina, Charleston, South Carolina, USA.
Abstract
PURPOSE: To quantitatively compare diffusion metrics for human brain estimated with diffusional kurtosis imaging (DKI) at applied field strengths of 1.5 and 3T. MATERIALS AND METHODS: DKI data for brain were acquired at both 1.5 and 3T from each of six healthy volunteers using a twice-refocused diffusion-weighted imaging sequence. From these data, parametric maps of mean diffusivity (MD), axial diffusivity (D‖ ), radial diffusivity (D⊥ ), fractional anisotropy (FA), mean diffusional kurtosis (MK), axial kurtosis (K‖ ), radial kurtosis (K⊥ ), and kurtosis fractional anisotropy (KFA) were estimated. Comparisons of the results from the two field strengths were made for each metric using both Bland-Altman plots and linear regression to calculate coefficients of determination (R2 ) and best fit lines. RESULTS: Diffusion metrics measured at 1.5 and 3T were observed to be similar. Linear regression of the full datasets had coefficients of determination varying from a low of R2 = 0.86 for KFA to a high of R2 = 0.97 for FA. The slopes of the 3T vs. 1.5T best linear fits varied from 0.881 ± 0.009 for KFA to 1.038 ± 0.010 for D‖ . From a Bland-Altman analysis of selected regions of interest, the mean differences of the metrics for the two field strengths were all found to be less than 6%, except for KFA, which showed the largest relative discrepancy of 10%. CONCLUSION: Diffusion metrics measured with DKI at 1.5 and 3T are strongly correlated and typically differ by only a few percent. The somewhat higher discrepancy for the KFA is argued to mainly reflect the effects of signal noise. This supports the robustness DKI results with respect to field strength. LEVEL OF EVIDENCE: 3 J. Magn. Reson. Imaging 2017;45:673-680.
PURPOSE: To quantitatively compare diffusion metrics for human brain estimated with diffusional kurtosis imaging (DKI) at applied field strengths of 1.5 and 3T. MATERIALS AND METHODS: DKI data for brain were acquired at both 1.5 and 3T from each of six healthy volunteers using a twice-refocused diffusion-weighted imaging sequence. From these data, parametric maps of mean diffusivity (MD), axial diffusivity (D‖ ), radial diffusivity (D⊥ ), fractional anisotropy (FA), mean diffusional kurtosis (MK), axial kurtosis (K‖ ), radial kurtosis (K⊥ ), and kurtosis fractional anisotropy (KFA) were estimated. Comparisons of the results from the two field strengths were made for each metric using both Bland-Altman plots and linear regression to calculate coefficients of determination (R2 ) and best fit lines. RESULTS: Diffusion metrics measured at 1.5 and 3T were observed to be similar. Linear regression of the full datasets had coefficients of determination varying from a low of R2 = 0.86 for KFA to a high of R2 = 0.97 for FA. The slopes of the 3T vs. 1.5T best linear fits varied from 0.881 ± 0.009 for KFA to 1.038 ± 0.010 for D‖ . From a Bland-Altman analysis of selected regions of interest, the mean differences of the metrics for the two field strengths were all found to be less than 6%, except for KFA, which showed the largest relative discrepancy of 10%. CONCLUSION: Diffusion metrics measured with DKI at 1.5 and 3T are strongly correlated and typically differ by only a few percent. The somewhat higher discrepancy for the KFA is argued to mainly reflect the effects of signal noise. This supports the robustness DKI results with respect to field strength. LEVEL OF EVIDENCE: 3 J. Magn. Reson. Imaging 2017;45:673-680.
Authors: Ipsita Goswami; Daphne Kamino; Elysa Widjaja; Melissa Paniccia; Nicholas Mitsakakis; Aideen Moore; Emily W Y Tam Journal: Pediatr Res Date: 2022-03-15 Impact factor: 3.953