Anisotropic Anomalous Diffusion assessed in the human brain by scalar invariant indices

A new method to investigate anomalous diffusion in human brain is proposed. The method has been inspired by both the stretched-exponential model proposed by Hall and Barrick (HB) and DTI. Quantities extracted using HB method were able to discriminate different cerebral tissues on the basis of their complexity, expressed by the stretching exponent gamma and of the anisotropy of gamma across different directions. Nevertheless, these quantities were not defined as scalar invariants like mean diffusivity and fractional anisotropy, which are eigenvalues of the diffusion tensor. We hypotesize instead that the signal may be espressed as a simple stretched-exponential only along the principal axes of diffusion, while in a generic direction the signal is modeled as a combination of three different stretched-exponentials. In this way, we derived indices to quantify both the tissue anomalous diffusion and its anisotropy, independently of the reference frame of the experiment. We tested and compare our new method with DTI and HB approaches applying them to 10 healty subjects brain at 3T. Our experimental results show that our parameters are highly correlated to intrinsic local geometry when compared to HB indices. Moreover, they offer a different kind of contrast when compared to DTI outputs. Specifically, our indices show a higher capability to discriminate among different areas of the corpus callosum, which are known to be associated to different axonal densities.Comment: 21 pages, 6 figures, 2 table

Focus on diffusion MR investigations of musculoskeletal tissue to improve osteoporosis diagnosis: A brief practical review

Nowadays, a huge number of papers have documented the ability of diffusion magnetic resonance imaging (D-MRI) to highlight normal and pathological conditions in a variety of cerebral, abdominal, and cardiovascular applications. To date, however, the role of D-MRI to investigate musculoskeletal tissue, specifically the cancellous bone, has not been extensively explored. In order to determine potentially useful applications of diffusion techniques in musculoskeletal investigation, D-MRI applications to detect osteoporosis disease were reviewed and further explained

Spatio-temporal anomalous diffusion in heterogeneous media by NMR

For the first time, the diffusion phase diagram in highly confined colloidal systems, predicted by Continuous Time Random Walk (CTRW), is experimentally obtained. Temporal and spatial fractional exponents, $\alpha$ and $\mu$, introduced within the framework of CTRW, are simultaneously measured by Pulse Field Gradient Nuclear Magnetic Resonance technique in samples of micro-beads dispersed in water. We find that $\alpha$ depends on the disorder degree of the system. Conversely, $\mu$ depends on both bead sizes and magnetic susceptibility differences within samples. Our findings fully match the CTRW predictions.Comment: 5 pages, 4 figures, submitted to Phys. Rev. Let

About the crazed sequence

In this article we report a detailed and understandable analysis of the evolution of various coherence orders in a Correlated 2D spectroscopy Revamped by Asymmetric Z-gradient Echo Detection (CRAZED) like pulse sequence, used to select a signal from intermolecular Multi Quantum Coherences (iMQCs). Because the signal to-noise-ratio of iMQC is much lower than the signal from conventional single quantum coherence (SQC), an optimization of experimental parameters is a necessity when measurements are made with iMQC. For this purpose a phase cycle is shown that not only allows a simpler selection of a particular quantum coherence order, but also removes receiver artifacts

Revised NODDI model for diffusion MRI data with multiple b-tensor encodings

This work proposes a revision of the NODDI model to relate brain tissue microstructure to the new generation of diffusion MRI data with multiple b-tensor encodings. NODDI was developed originally for conventional multi-shell diffusion data acquired with linear tensor encoding (LTE). While adequate for LTE data, it has been shown to be incompatible with data using spherical tensor encoding (STE). We embed a different set of assumptions in NODDI, while retaining the tortuosity constraint, to accommodate both LTE and STE data. Experiments with human data with multiple b-tensor encodings confirm the efficacy of the revision

Diffusion tensor imaging and magnetic resonance spectroscopy assessment of cancellous bone quality in femoral neck of healthy, osteopenic and osteoporotic subjects at 3T: Preliminary experience.

We assessed the potential of diffusion tensor imaging (DTI) in combination with proton magnetic resonance spectroscopy ((1)H-MRS), in cancellous bone quality evaluation of the femoral neck in postmenopausal women. INTRODUCTION: DTI allows for non-invasive microarchitectural characterization of heterogeneous tissue. In this work we hypothesized that DTI parameters mean diffusivity (MD) and fractional anisotropy (FA) of bone marrow water, can provide information about microstructural changes that occur with the development of osteoporosis disease. Because osteoporosis is associated with increased bone marrow fat content, which in principal can alter DTI parameters, the goal of this study was to examine the potential of MD and FA, in combination with bone marrow fat fraction (FF), to discriminate between healthy, osteopenic and osteoporotic subjects, classified according to DXA criteria. MATERIALS AND METHODS: Forty postmenopausal women (mean age, 68.7years; range 52-81years), underwent a Dual-energy X-ray absorptiometry (DXA) examination in femoral neck, to be classified as healthy (n=12), osteopenic (n=14) and osteoporotic (n=14) subjects. (1)H-MRS and DTI (with b value=2500s/mm(2)) of femoral neck were obtained in each subject at 3T. The study protocol was approved by local Ethics Committee. MD, FA, FF and MD/FF, FA/FF were obtained and compared among the three bone-density groups. One-way ANOVA with multiple comparisons Bonferroni test and Pearson correlation analysis were applied. Receiver operating characteristic (ROC) curve analysis was also performed. RESULTS: Reproducibility of DTI measures was satisfactory. CV was approximately 2%-3% for MD and 4%-5% for FA measurements. Moreover, no significant difference was found in both MD and FA measurements between two separate sessions (median 34days apart) comprised of six healthy volunteers. FF was able to discriminate between healthy and osteoporotic subjects only. Conversely MD and FA were able to discriminate healthy from osteopenic and healthy from osteoporotic subjects, but they were not able to discriminate between osteopenic and osteoporotic patients. A significant correlation between MD and FF was observed in healthy group only. A moderate correlation was found between MD and T-score when all groups together are considered. No significant correlation was found between MD and T-score within groups. A significant positive correlation between FA and FF was found in both osteopenic and osteoporotic groups. Vice-versa no correlation between FA and FF was observed in healthy group. A high significant positive correlation was found between FA and T-score in all groups together, in healthy and in osteoporotic groups. MD/FF and FA/FF are characterized by a higher sensitivity and specificity compared to MD and FA in the discrimination between healthy, and osteoporotic subjects. MD/FF vs FA/FF graph extracted from femoral neck, identify all healthy individuals according to DXA results. CONCLUSION: DTI-(1)H-MRS protocol performed in femoral neck seems to be highly sensitive and specific in identifying healthy subjects. A MR exam is more expensive when compared to a DXA investigation. However, even though DXA BMD evaluation has been the accepted standard for osteoporosis diagnosis, DXA result has a low predictive value on patients' risk for future fractures. Thus, new approaches for examining patients at risk for developing osteoporosis would be desirable. Preliminary results showed here suggest that future studies on a larger population based on DTI assessment in the femoral neck, in combination with (1)H-MRS investigations, might allow screening of high-risk populations and the establishment of cut-off values of normality, with potential application of the method to single subjects

Apparent Diffusion Coefficient Assessment of Brain Development in Normal Fetuses and Ventriculomegaly

Diffusion neuro-MRI has benefited significantly from sophisticated pre-processing procedures aimed at improving image quality and diagnostic. In this work, diffusion-weighted imaging (DWI) was used with artifact correction and the apparent diffusion coefficient (ADC) was quantified to investigate fetal brain development. The DWI protocol was designed in order to limit the acquisition time and to estimate ADC without perfusion bias. The ADC in normal fetal brains was compared to cases with isolated ventriculomegaly (VM), a common fetal disease whose DWI studies are still scarce. DWI was performed in 58 singleton fetuses (Gestational age (GA) range: 19–38w) at 1.5T. In 31 cases, VM was diagnosed on ultrasound. DW-Spin Echo EPI with b-values = 50, 200, 700 s/mm2 along three orthogonal axes was used. All images were corrected for noise, Gibbs-ringing, and motion artifacts. The signal-to-noise ratio (SNR) was calculated and the ADC was measured with a linear least-squared algorithm. A multi-way ANOVA was used to evaluate differences in ADC between normal and VM cases and between second and third trimester in different brain regions. Correlation between ADC and GA was assessed with linear and quadratic regression analysis. Noise and artifact correction considerably increased SNR and the goodness-of-fit. ADC measurements were significantly different between second and third trimester in centrum semiovale, frontal white matter, thalamus, cerebellum and pons of both normal and VM brains (p ≤ 0.03). ADC values were significantly different between normal and VM in centrum semiovale and frontal white matter (p ≤ 0.02). ADC values in centrum semiovale, thalamus, cerebellum and pons linearly decreased with GA both in normal and VM brains, while a quadratic relation with GA was found in basal ganglia and occipital white matter of normal brains and in frontal white matter of VM (p ≤ 0.02). ADC values in all fetal brain regions were lower than those reported in literature where DWI with b = 0 was performed. Conversely, they were in agreement with the results of other authors who measured perfusion and diffusion contributions separately. By optimizing our DWI protocol we achieved an unbiased quantification of brain ADC in reasonable scan time. Our findings suggested that ADC can be a useful biomarker of brain abnormalities associated with VM

Apparent diffusion coefficient assessment of brain development in normal fetuses and ventriculomegaly

Diffusion neuro-MRI has benefited significantly from sophisticated pre-processing procedures aimed at improving image quality and diagnostic. In this work, diffusion-weighted imaging (DWI) was used with artifact correction and the apparent diffusion coefficient (ADC) was quantified to investigate fetal brain development. The DWI protocol was designed in order to limit the acquisition time and to estimate ADC without perfusion bias. The ADC in normal fetal brains was compared to cases with isolated ventriculomegaly (VM), a common fetal disease whose DWI studies are still scarce. DWI was performed in 58 singleton fetuses (Gestational age (GA) range: 19–38w) at 1.5T. In 31 cases, VM was diagnosed on ultrasound. DW-Spin Echo EPI with b-values = 50, 200, 700 s/mm2 along three orthogonal axes was used. All images were corrected for noise, Gibbs-ringing, and motion artifacts. The signal-to-noise ratio (SNR) was calculated and the ADC was measured with a linear least-squared algorithm. A multi-way ANOVA was used to evaluate differences in ADC between normal and VM cases and between second and third trimester in different brain regions. Correlation between ADC and GA was assessed with linear and quadratic regression analysis. Noise and artifact correction considerably increased SNR and the goodness-of-fit. ADC measurements were significantly different between second and third trimester in centrum semiovale, frontal white matter, thalamus, cerebellum and pons of both normal and VM brains (p ≤ 0.03). ADC values were significantly different between normal and VM in centrum semiovale and frontal white matter (p ≤ 0.02). ADC values in centrum semiovale, thalamus, cerebellum and pons linearly decreased with GA both in normal and VM brains, while a quadratic relation with GA was found in basal ganglia and occipital white matter of normal brains and in frontal white matter of VM (p ≤ 0.02). ADC values in all fetal brain regions were lower than those reported in literature where DWI with b = 0 was performed. Conversely, they were in agreement with the results of other authors who measured perfusion and diffusion contributions separately. By optimizing our DWI protocol we achieved an unbiased quantification of brain ADC in reasonable scan time. Our findings suggested that ADC can be a useful biomarker of brain abnormalities associated with VM

Structural disorder and anomalous diffusion in random packing of spheres

Nowadays Nuclear Magnetic Resonance diffusion (dNMR) measurements of water molecules in heterogeneous systems have broad applications in material science, biophysics and medicine. Up to now, microstructural rearrangement in media has been experimentally investigated by studying the diffusion coefficient (D(t)) behavior in the tortuosity limit. However, this method is not able to describe structural disorder and transitions in complex systems. Here we show that, according to the continuous time random walk framework, the dNMR measurable parameter α, quantifying the anomalous regime of D(t), provides a quantitative characterization of structural disorder and structural transition in heterogeneous systems. To demonstrate this, we compare α measurements obtained in random packed monodisperse micro-spheres with Molecular Dynamics simulations of disordered porous media and 3D Monte Carlo simulation of particles diffusion in these kind of systems. Experimental results agree well with simulations that correlate the most used parameters and functions characterizing the disorder in porous media