Multicenter reproducibility of quantitative susceptibility mapping in a gadolinium phantom using MEDI+0 automatic zero referencing

2019 
Purpose: To determine the reproducibility of quantitative susceptibility mapping at multiple sites on clinical and preclinical scanners (1.5 T, 3 T, 7 T, and 9.4 T) from different vendors (Siemens, GE, Philips, and Bruker) for standardization of multicenter studies. Methods: Seven phantoms distributed from the core site, each containing 5 compartments with gadolinium solutions with fixed concentrations between 0.625 mM and 10 mM. Multi-echo gradient echo scans were performed at 1.5 T, 3 T, 7 T, and 9.4 T on 12 clinical and 3 preclinical scanners. DICOM images from the scans were processed into quantitative susceptibility maps using the Laplacian boundary value (LBV) and MEDI+0 automatic uniform reference algorithm. Region of interest (ROI) analyses were performed by a physicist to determine agreement between results from all sites. Measurement reproducibility was assessed using regression, Bland-Altman plots, and the intra-class correlation coefficient (ICC). Results: Quantitative susceptibility mapping (QSM) from all scanners had similar, artifact-free visual appearance. Regression analysis showed a linear relationship between gadolinium concentrations and average QSM measurements for all phantoms (y = 350x – 0.0346, r2>0.99). The SD of measurements increased almost linearly from 32 ppb to 230 ppb as the measured susceptibility increased from 0.26 ppm to 3.56 ppm. A Bland-Altman plot showed the bias, upper, and lower limits of agreement for all comparisons were −10, −210, and 200 ppb, respectively. The ICC was 0.991 with a 95% CI (0.973, 0.99). Conclusions: QSM shows excellent multicenter reproducibility for a large range of susceptibility values encountered in cranial and extra-cranial applications on a diverse set of scanner platforms. (Less)
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    30
    References
    19
    Citations
    NaN
    KQI
    []