Diffusion-weighted (DW-) MRS investigates non-invasively microstructural properties of tissue by probing metabolite diffusion in vivo. Despite the growing interest in DW-MRS for clinical applications, little has been published on the reproducibility of this technique. In this study, we explored the optimization of a single-voxel DW-semi-LASER sequence for clinical applications at 3 T, and evaluated the reproducibility of the method under different experimental conditions. DW-MRS measurements were carried out in 10 healthy participants and repeated across three sessions. Metabolite apparent diffusion coefficients (ADCs) were calculated from mono-exponential fits (ADCexp) up to b = 3300 s/mm2, and from the diffusional kurtosis approach (ADCK) up to b = 7300 s/mm2. The inter-subject variabilities of ADCs of N-acetylaspartate + N-acetylaspartylglutamate (tNAA), creatine + phosphocreatine, choline containing compounds, and myo-inositol were calculated in the posterior cingulate cortex (PCC) and in the corona radiata (CR). We explored the effect of physiological motion on the DW-MRS signal and the importance of cardiac gating and peak thresholding to account for signal amplitude fluctuations. Additionally, we investigated the dependence of the intra-subject variability on the acquisition scheme using a bootstrapping resampling method. Coefficients of variation were lower in PCC than CR, likely due to the different sensitivities to motion artifacts of the two regions. Finally, we computed coefficients of repeatability for ADCexp and performed power calculations needed for designing clinical studies. The power calculation for ADCexp of tNAA showed that in the PCC seven subjects per group are sufficient to detect a difference of 5% between two groups with an acquisition time of 4 min, suggesting that ADCexp of tNAA is a suitable marker for disease-related intracellular alteration even in small case–control studies. In the CR, further work is needed to evaluate the voxel size and location that minimize the motion artifacts and variability of the ADC measurements.
Bibliographical noteFunding Information:
This work was supported by the programs ‘Institut des neurosciences translationnelle’ (ANR‐10‐IAIHU‐06) and ‘Infrastructure d'avenir en Biologie Santé’ (ANR‐11‐INBS‐0006). Małgorzata Marjańska and Edward J. Auerbach acknowledge the support of NIH grants (BTRC P41 EB015894 and P30 NS076408).
This work was supported by the programs ?Institut des neurosciences translationnelle? (ANR-10-IAIHU-06) and ?Infrastructure d'avenir en Biologie Sant?? (ANR-11-INBS-0006). Ma?gorzata Marja?ska and Edward J. Auerbach acknowledge the support of NIH grants (BTRC P41 EB015894 and P30 NS076408).
© 2020 John Wiley & Sons, Ltd.
- power calculation