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Abstract #4015

Detecting the presence of fat using PLANET-based parameter mapping

Yulia Shcherbakova1, Cornelis A.T. van den Berg2, Soraya Gavazzi2, Chrit T.W. Moonen1, and Lambertus W. Bartels1

1Center for Image Sciences, Imaging Division, UMC Utrecht, Utrecht, Netherlands, 2Department of Radiotherapy, Imaging Devision, UMC Utrecht, Utrecht, Netherlands

The PLANET method was introduced to simultaneously map T1, T2, banding free magnitude, local off-resonance, and RF phase using phase-cycled bSSFP data. All these parameters are estimated from a linear least squares fitting of an ellipse to complex data.

The PLANET method is based on a Lorentzian single-component relaxation model, which results in symmetric bSSFP magnitude profile and elliptical behavior of the complex transverse magnetization. However, when a second or more components with different frequency distributions are present within a voxel, the complex signal might not lie on an ellipse anymore. Hence, PLANET post-processing would return erroneous quantitative parameters.

In this study we show that the sensitivity of PLANET to the presence of multiple components can be exploited to map the spatial distribution of voxels in which multiple spectral peaks are present. We demonstrate that this feature of PLANET can be used to create fat-only map.

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