Magnetic Resonance Spectroscopy (MRS) and Spectroscopic Imaging (MRSI) play an emerging role in clinical assessment, providing in vivo estimation of disease markers while being non-invasive and applicable to a large range of tissues. However, static magnetic field inhomogeneity, as well as eddy currents in the acquisition hardware, cause important distortions in the lineshape of acquired NMR spectra, possibly inducing significant bias in the estimation of metabolite concentrations. In the post-acquisition stage, this is classically handled through the use of pre-processing methods to correct the dataset lineshape, or through the introduction of more complex analytical model functions. This thesis concentrates on handling arbitrary lineshape distortions in the case of quantitation methods that use a metabolite basis-set as prior knowledge. Current approaches are assessed, and a novel approach is proposed, based on adapting the basis-set lineshape to the measured signal.Assuming a common lineshape to all spectral components, a new method is derived and implemented, featuring time domain local regression (LOWESS) filtering. Validation is performed on synthetic signals as well as on in vitro phantom data. Finally, a completely new approach to MRS quantitation is proposed, centred on the use of the compact spectral support of the estimated common lineshape. The new metabolite estimators are tested alone, as well as coupled with the more common residual-sum-of-squares MLE estimator, significantly reducing quantitation bias for high signal-to-noise ratio data.
| Identifer | oai:union.ndltd.org:CCSD/oai:tel.archives-ouvertes.fr:tel-00716176 |
| Date | 15 July 2010 |
| Creators | Popa, Emil Horia |
| Publisher | Université Claude Bernard - Lyon I |
| Source Sets | CCSD theses-EN-ligne, France |
| Language | English |
| Detected Language | English |
| Type | PhD thesis |
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