Reduced NAA-Levels in the NAWM of Patients with MS Is a Feature of Progression. A Study with Quantitative Magnetic Resonance Spectroscopy at 3 Tesla

Reduced N-acetyl-aspartate (NAA) levels in magnetic resonance spectroscopy (MRS) may visualize axonal damage even in the normal appearing white matter (NAWM). Demyelination and axonal degeneration are a hallmark in multiple sclerosis (MS).To define the extent of axonal degeneration in the NAWM in the remote from focal lesions in patients with relapsing-remitting (RRMS) and secondary progressive MS (SPMS).H-MR-chemical shift imaging (TR = 1500ms, TE = 135ms, nominal resolution 1ccm) operating at 3Tesla to assess the metabolic pattern in the fronto–parietal NAWM. Ratios of NAA to creatine (Cr) and choline (Cho) and absolute concentrations of the metabolites in the NAWM were measured in each voxel matching exclusively white matter on the anatomical T2 weighted MR images.No significant difference of absolute concentrations for NAA, Cr and Cho or metabolite ratios were found between RRMS and controls. In SPMS, the NAA/Cr ratio and absolute concentrations for NAA and Cr were significantly reduced compared to RRMS and to controls.In our study SPMS patients, but not RRMS patients were characterized by low NAA levels. Reduced NAA-levels in the NAWM of patients with MS is a feature of progression

Measuring macroscopic brain connections in vivo

Decades of detailed anatomical tracer studies in non-human animals point to a rich and complex organization of long-range white matter connections in the brain. State-of-the art in vivo imaging techniques are striving to achieve a similar level of detail in humans, but multiple technical factors can limit their sensitivity and fidelity. In this review, we mostly focus on magnetic resonance imaging of the brain. We highlight some of the key challenges in analyzing and interpreting in vivo connectomics data, particularly in relation to what is known from classical neuroanatomy in laboratory animals. We further illustrate that, despite the challenges, in vivo imaging methods can be very powerful and provide information on connections that is not available by any other means

Multi-Compartment T2 Relaxometry Using a Spatially Constrained Multi-Gaussian Model

The brain's myelin content can be mapped by T2-relaxometry, which resolves multiple differentially relaxing T2 pools from multi-echo MRI. Unfortunately, the conventional fitting procedure is a hard and numerically ill-posed problem. Consequently, the T2 distributions and myelin maps become very sensitive to noise and are frequently difficult to interpret diagnostically. Although regularization can improve stability, it is generally not adequate, particularly at relatively low signal to noise ratio (SNR) of around 100-200. The purpose of this study was to obtain a fitting algorithm which is able to overcome these difficulties and generate usable myelin maps from noisy acquisitions in a realistic scan time. To this end, we restrict the T2 distribution to only 3 distinct resolvable tissue compartments, modeled as Gaussians: myelin water, intra/extra-cellular water and a slow relaxing cerebrospinal fluid compartment. We also impose spatial smoothness expectation that volume fractions and T2 relaxation times of tissue compartments change smoothly within coherent brain regions. The method greatly improves robustness to noise, reduces spatial variations, improves definition of white matter fibers, and enhances detection of demyelinating lesions. Due to efficient design, the additional spatial aspect does not cause an increase in processing time. The proposed method was applied to fast spiral acquisitions on which conventional fitting gives uninterpretable results. While these fast acquisitions suffer from noise and inhomogeneity artifacts, our preliminary results indicate the potential of spatially constrained 3-pool T2 relaxometry