Non local spatial and angular matching : enabling higher spatial resolution diffusion MRI datasets through adaptive denoising

Diffusion magnetic resonance imaging (MRI) datasets suffer from low Signal-to-Noise Ratio (SNR), especially at high b-values. Acquiring data at high b-values contains relevant information and is now of great interest for microstructural and connectomics studies. High noise levels bias the measurements due to the non-Gaussian nature of the noise, which in turn can lead to a false and biased estimation of the diffusion parameters. Additionally, the usage of in-plane acceleration techniques during the acquisition leads to a spatially varying noise distribution, which depends on the parallel acceleration method implemented on the scanner. This paper proposes a novel diffusion MRI denoising technique that can be used on all existing data, without adding to the scanning time. We first apply a statistical framework to convert both stationary and non stationary Rician and non central Chi distributed noise to Gaussian distributed noise, effectively removing the bias. We then introduce a spatially and angular adaptive denoising technique, the Non Local Spatial and Angular Matching (NLSAM) algorithm. Each volume is first decomposed in small 4D overlapping patches, thus capturing the spatial and angular structure of the diffusion data, and a dictionary of atoms is learned on those patches. A local sparse decomposition is then found by bounding the reconstruction error with the local noise variance. We compare against three other state-of-the-art denoising methods and show quantitative local and connectivity results on a synthetic phantom and on an in-vivo high resolution dataset. Overall, our method restores perceptual information, removes the noise bias in common diffusion metrics, restores the extracted peaks coherence and improves reproducibility of tractography on the synthetic dataset. On the 1.2 mm high resolution in-vivo dataset, our denoising improves the visual quality of the data and reduces the number of spurious tracts when compared to the noisy acquisition. Our work paves the way for higher spatial resolution acquisition of diffusion MRI datasets, which could in turn reveal new anatomical details that are not discernible at the spatial resolution currently used by the diffusion MRI community

Association between genetic variants in the Coenzyme Q10 metabolism and Coenzyme Q10 status in humans

<p>Abstract</p> <p>Background</p> <p>Coenzyme Q₁₀(CoQ₁₀) is essential for mitochondrial energy production and serves as an antioxidants in extra mitochondrial membranes. The genetics of primary CoQ₁₀deficiency has been described in several studies, whereas the influence of common genetic variants on CoQ₁₀status is largely unknown. Here we tested for non-synonymous single-nucleotidepolymorphisms (SNP) in genes involved in the biosynthesis (CoQ3^G272S, CoQ6^M406V, CoQ7^M103T), reduction (NQO1^P187S, NQO2^L47F) and metabolism (apoE3/4) of CoQ₁₀and their association with CoQ₁₀status. For this purpose, CoQ₁₀serum levels of 54 healthy male volunteers were determined before (T₀) and after a 14 days supplementation (T₁₄) with 150 mg/d of the reduced form of CoQ₁₀.</p> <p>Findings</p> <p>At T₀, the CoQ₁₀level of heterozygous NQO1^P187Scarriers were significantly lower than homozygous S/S carriers (0.93 ± 0.25 μM versus 1.34 ± 0.42 μM, p = 0.044). For this polymorphism a structure homology-based method (PolyPhen) revealed a possibly damaging effect on NQO1 protein activity. Furthermore, CoQ₁₀plasma levels were significantly increased in apoE4/E4 genotype after supplementation in comparison to apoE2/E3 genotype (5.93 ± 0.151 μM versus 4.38 ± 0.792 μM, p = 0.034). Likewise heterozygous CoQ3^G272Scarriers had higher CoQ₁₀plasma levels at T₁₄compared to G/G carriers but this difference did not reach significance (5.30 ± 0.96 μM versus 4.42 ± 1.67 μM, p = 0.082).</p> <p>Conclusions</p> <p>In conclusion, our pilot study provides evidence that NQO1^P187Sand apoE polymorphisms influence CoQ₁₀status in humans.</p

In-plane “superresolution” MRI with phaseless sub-pixel encoding

PURPOSE: Acquisition of high-resolution imaging data using multiple excitations without the sensitivity to fluctuations of the transverse magnetization phase, which is a major problem of multi-shot MRI. THEORY AND METHODS: The concept of superresolution MRI based on microscopic tagging is analyzed using an analogy with the optical method of structured illumination. Sinusoidal tagging is shown to provide subpixel resolution by mixing of neighboring spatial frequency (k-space) bands. It represents a phaseless modulation added on top of the standard Fourier encoding, which allows the phase fluctuations to be discarded at an intermediate reconstruction step. Improvements are proposed to correct for tag distortions due to magnetic field inhomogeneity and to avoid the propagation of Gibbs ringing from intermediate low-resolution images to the final image. The method was applied to diffusion-weighted EPI. RESULTS: Artifact-free superresolution images can be obtained despite a finite duration of the tagging sequence and related pattern distortions by a field map based phase correction of band-wise reconstructed images. The ringing effect present in the intermediate images can be suppressed by partial overlapping of the mixed k-space bands in combination with an adapted filter. High-resolution diffusion-weighted images of the human head were obtained with a three-shot EPI sequence despite motion-related phase fluctuations between the shots. CONCLUSION: Due to its phaseless character, tagging-based sub-pixel encoding is an alternative to k-space segmenting in the presence of unknown phase fluctuations, in particular those due to motion under strong diffusion gradients. Proposed improvements render the method practicable in realistic conditions