Keywords: Spectroscopy, Brain, Data Analysis, High-Field MRSI, Signal Modeling, Quantitative Imaging
Motivation: Proton MR Spectroscopy Imaging requires specialized quantification software. Several packages are available; however, they can give significantly different outputs, which can cause errors in decision making.
Goal(s): We theorize that quantification algorithms can be improved by introducing spatial-based constraints to the model alongside the traditional spectral constraints.
Approach: We developed an alternative modality to our quantification software which incorporates the spatial relationship for confounding fitting parameters as a constraint for four human datasets. Improved fit performance is quantified using CRLB error measurements.
Results: Reduced error estimates were observed for all metabolites. Metabolite distribution stayed consistent between fitting strategies and expected tissue distribution.
Impact: The results of this study are promising for improving the interpretability of MRSI data. Our approach managed to improve the reproducibility of our quantification results and is translatable to a wide range of spectral fitting strategies.
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