We propose a multicomponent fitting algorithm for multiecho T(2) data which allows for correction of T(2) distributions in the presence of stimulated echoes. Tracking the population of spins in many coherence pathways via the iterated method of the Extended Phase Graph algorithm allows for accurate quantification of echo magnitudes. The resulting decay curves allow for correction of errors due to nonideal refocusing pulses as a result of inhomogeneities in the B(1) transmit field. Non-Negative Least Squares fitting is used to quantify the magnitude of T(2) components at various T(2) values. This method, allowing calculation of the T(2) distribution with simultaneous extraction of the refocusing pulse flip angle, requires no change to image acquisition procedures and no extra data input. Validation by means of both simulations and in vivo data shows excellent interscan reproducibility while vastly improving the accuracy of extracted T(2) parameters in voxels where poor B(1) homogeneity leads to refocusing pulse flip angles significantly less than 180°. Most notably, myelin water fraction values in these regions are found to have increased consistency and accuracy.

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ObjectiveWe investigate how known differences in myelin architecture between regions along the cortico-spinal tract and frontal white matter (WM) in 19 healthy adolescents are reflected in several quantitative MRI parameters that have been proposed to non-invasively probe WM microstructure. In a clinically feasible scan time, both conventional imaging sequences as well as microstructural MRI parameters were assessed in order to quantitatively characterise WM regions that are known to differ in the thickness of their myelin sheaths, and in the presence of crossing or parallel fibre organisation.ResultsWe found that diffusion imaging, MR spectroscopy (MRS), myelin water fraction (MWF), Magnetization Transfer Imaging, and Quantitative Susceptibility Mapping were myelin-sensitive in different ways, giving complementary information for characterising WM microstructure with different underlying fibre architecture. From the diffusion parameters, neurite density (NODDI) was found to be more sensitive than fractional anisotropy (FA), underlining the limitation of FA in WM crossing fibre regions. In terms of sensitivity to different myelin content, we found that MWF, the mean diffusivity and chemical-shift imaging based MRS yielded the best discrimination between areas.ConclusionMultimodal assessment of WM microstructure was possible within clinically feasible scan times using a broad combination of quantitative microstructural MRI sequences. By assessing new microstructural WM parameters we were able to provide normative data and discuss their interpretation in regions with different myelin architecture, as well as their possible application as biomarker for WM disorders.

The proposed hybrid multicore approach represents a more efficient alternative to MATLAB, especially for large-scale batch processing.

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