Improved diffusion imaging through SNR-enhancing joint reconstruction.

Quantitative diffusion imaging is a powerful technique for the characterization of complex tissue microarchitecture. However, long acquisition times and limited signal-to-noise ratio represent significant hurdles for many in vivo applications. This article presents a new approach to reduce noise while largely maintaining resolution in diffusion weighted images, using a statistical reconstruction method that takes advantage of the high level of structural correlation observed in typical datasets. Compared to existing denoising methods, the proposed method performs reconstruction directly from the measured complex k-space data, allowing for gaussian noise modeling and theoretical characterizations of the resolution and signal-to-noise ratio of the reconstructed images. In addition, the proposed method is compatible with many different models of the diffusion signal (e.g., diffusion tensor modeling and q-space modeling). The joint reconstruction method can provide significant improvements in signal-to-noise ratio relative to conventional reconstruction techniques, with a relatively minor corresponding loss in image resolution. Results are shown in the context of diffusion spectrum imaging tractography and diffusion tensor imaging, illustrating the potential of this signal-to-noise ratio-enhancing joint reconstruction approach for a range of different diffusion imaging experiments.

Regional alterations of brain microstructure in Parkinson's disease using diffusion tensor imaging.

This study tested the hypothesis that diffusion tensor imaging can detect alteration in microscopic integrity of white matter and basal ganglia regions known to be involved in Parkinson's disease (PD) pathology. It was also hypothesized that there is an association between diffusion abnormality and PD severity and subtype. Diffusion tensor imaging at 4 Tesla was obtained in 12 PD and 20 control subjects, and measures of fractional anisotropy and mean diffusivity were evaluated using both region-of-interest and voxel-based methods. Movement deficits and subtypes in PD subjects were assessed using the Motor Subscale (Part III) of the Unified Parkinson's Disease Rating Scale. Reduced fractional anisotropy (P < .05, corrected) was found in PD subjects in regions related to the precentral gyrus, substantia nigra, putamen, posterior striatum, frontal lobe, and the supplementary motor areas. Reduced fractional anisotropy in the substantia nigra correlated (P < .05, corrected) with the increased rating scale motor scores. Significant spatial correlations between fractional anisotropy alterations in the putamen and other PD-affected regions were also found in the context of PD subtypes index analysis. Our data suggest that microstructural alterations detected with diffusion tensor might serve as a potential biomarker for PD.

Diffusion time dependence of magnetic resonance diffusion signal decays: an investigation of water exchange in human brain in vivo.

OBJECT: To understand the behavior of diffusion signal decays of water in white matter of human brain in vivo and to estimate tissue microstructure parameters such as exchange time of diffusing water molecules in human brain. MATERIALS AND METHODS: Diffusion decays were measured over an extended range of diffusion weightings (b-values) up to a maximum of 12,500 s/mm(2) and diffusion times between 19.9 and 53.8 ms in eight healthy human subjects using MRI scans. The diffusion signal decays were all Rician noise corrected and then analyzed using multi-component non-negative least squares (NNLS) data analysis. RESULTS: Three diffusion coefficients including one at (0.930 ± 0.003) × 10(-3) (80 ± 1%) mm(2)/s, another at (0.067 ± 0.002) × 10(-3) (19 ± 1%) mm(2)/s and a small contribution at (1.20 ± 0.02) × 10(-2) (1.00 ± 0.01%) mm(2)/s were observed in the diffusion decay using the highest b-value. The diffusion decays show diffusion time dependence for the slow diffusion coefficient which has not previously been reported. CONCLUSION: This study presents the accurate diffusion parameters by the use of very large b-values along with Rician noise correction and multi-component data analysis. The experimental results are consistent with the theoretical predictions used to estimate the exchange time of diffusing water molecules for a model of human brain tissue.

Improved pseudo-continuous arterial spin labeling for mapping brain perfusion.

PURPOSE: To investigate arterial spin labeling (ASL) methods for improved brain perfusion mapping. Previously, pseudo-continuous ASL (pCASL) was developed to overcome limitations inherent with conventional continuous ASL (CASL), but the control scan (null pulse) in the original method for pCASL perturbs the equilibrium magnetization, diminishing the ASL signal. Here, a new modification of pCASL, termed mpCASL is reported, in which the perturbation caused by the null pulse is reduced and perfusion mapping improved. MATERIALS AND METHODS: improvements with mpCASL are demonstrated using numerical simulations and experiments. ASL signal intensity as well as contrast and reproducibility of in vivo brain perfusion images were measured in four volunteers who had MRI scans at 4 Tesla and the data compared across the labeling methods. RESULTS: Perfusion maps with mpCASL showed, on average, higher ASL signal intensity and higher image contrast than those from CASL or pCASL. Furthermore, mpCASL yielded better reproducibility in repeat scans than the other methods. CONCLUSION: The experimental results are consistent with the hypothesis that the new null pulse of mpCASL leads to improved brain perfusion images.

Joint assessment of structural, perfusion, and diffusion MRI in Alzheimer's disease and frontotemporal dementia.

Most MRI studies of Alzheimer's disease (AD) and frontotemporal dementia (FTD) have assessed structural, perfusion and diffusion abnormalities separately while ignoring the relationships across imaging modalities. This paper aimed to assess brain gray (GM) and white matter (WM) abnormalities jointly to elucidate differences in abnormal MRI patterns between the diseases. Twenty AD, 20 FTD patients, and 21 healthy control subjects were imaged using a 4 Tesla MRI. GM loss and GM hypoperfusion were measured using high-resolution T1 and arterial spin labeling MRI (ASL-MRI). WM degradation was measured with diffusion tensor imaging (DTI). Using a new analytical approach, the study found greater WM degenerations in FTD than AD at mild abnormality levels. Furthermore, the GM loss and WM degeneration exceeded the reduced perfusion in FTD whereas, in AD, structural and functional damages were similar. Joint assessments of multimodal MRI have potential value to provide new imaging markers for improved differential diagnoses between FTD and AD.

In-vivo investigation of the human cingulum bundle using the optimization of MR diffusion spectrum imaging.

Diffusion spectrum imaging (DSI) is a generalization of diffusion tensor imaging to map fibrous structure of white matter and potentially very sensitive to alterations of the cingulum bundles in dementia. In this in-vivo 4T study, DSI parameters especially spatial resolution and diffusion encoding bandwidth were optimized on humans to segment the cingulum bundles for tract level measurements of diffusion. The careful tailoring of the DSI acquisitions in conjunction with fiber tracking provided an optimal DSI setting for a reliable quantification of the cingulum bundle tracts. The optimization of tracking the cingulum bundle was verified using fiber tract quantifications, including coefficients of variability of DSI measurements along the fibers between and within healthy subjects in back-to-back studies and variogram analysis of spatial correlations between diffusion orientation distribution functions (ODF) along the cingulum bundle tracts. The results demonstrate that the identification of the cingulum bundle in human brain is reproducible using an optimized DSI parameter for maximum b-value and high spatial resolution of the DSI acquisition with a feasible acquisition time of whole brain in clinical practice. This optimized DSI setting should be useful for detecting alterations along the cingulum bundle in Alzheimer disease and related neurodegenerative disorders.