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Estimating tissue volume fractions and proton density in multi-component MRF
Martijn A. Nagtegaal1, Laura Nunez Gonzalez2, Dirk H.J. Poot2, Matthias J.P. van Osch3, Jeroen H.J.M. de Bresser4, Juan A. Hernandez Tamames1,2, and Frans M. Vos1,2
1Department of Imaging Physics, Delft University of Technology, Delft, Netherlands, 2Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands, 3C.J. Gorter Center for high field MRI, Department of Radiology, Leiden University Medical Center, Leiden, Netherlands, 4Department of Radiology, Leiden University Medical Center, Leiden, Netherlands
Obtaining tissue volume fractions from multi-component MRF data requires accurate estimation of proton density values. An effective method to estimate these PD values is proposed and tested in simulations and in-vivo.  
Figure 4 Estimated volume fraction maps and RF fields for one subject scanned 7 times. The subject was repositioned after every scan, possibly resulting in slightly different slice locations, volume estimations and $$$B_1^-$$$ field estimations, although visual differences are minimal this hindered quantitative comparison on a voxel basis. Low rank reconstruction(rank 6) was used, in subsequent SPIJN processing $$$\mu=0.2$$$ was applied. Tissues were identified based on relaxation times. The acquitisition scheme from [4] was used.
Figure 3 Boxplots of estimated $$$T_1$$$, $$$T_2$$$ and relative proton densities over 7 scans per subject. $$$T_1$$$ and $$$T_2$$$ values show descrete estimations due to the used dictionary grid (5% relative step size). Proton densities were calculated relative to gray matter. Literature values for WM relative to GM are between 84% and 90%, for CSF 116% and 128%. Relaxation times for WM are consistent with literature[15], GM shows slightly lower times than expected, potentially caused by partial volume effects in GM areas.