77 research outputs found

    Towards non-parametric fiber-specific T1T_1 relaxometry in the human brain

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    Purpose: To estimate fiber-specific T1T_1 values, i.e. proxies for myelin content, in heterogeneous brain tissue. Methods: A diffusion-T1T_1 correlation experiment was carried out on an in vivo human brain using tensor-valued diffusion encoding and multiple repetition times. The acquired data was inverted using a Monte-Carlo inversion algorithm that retrieves non-parametric distributions P(D,R1)\mathcal{P}(\mathbf{D},R_1) of diffusion tensors and longitudinal relaxation rates R1=1/T1R_1 = 1/T_1. Orientation distribution functions (ODFs) of the highly anisotropic components of P(D,R1)\mathcal{P}(\mathbf{D},R_1) were defined to visualize orientation-specific diffusion-relaxation properties. Finally, Monte-Carlo density-peak clustering (MC-DPC) was performed to quantify fiber-specific features and investigate microstructural differences between white-matter fiber bundles. Results: Parameter maps corresponding to P(D,R1)\mathcal{P}(\mathbf{D},R_1)'s statistical descriptors were obtained, exhibiting the expected R1R_1 contrast between brain-tissue types. Our ODFs recovered local orientations consistent with the known anatomy and indicated possible differences in T1T_1 relaxation between major fiber bundles. These differences, confirmed by MC-DPC, were in qualitative agreement with previous model-based works but seem biased by the limitations of our current experimental setup. Conclusions: Our Monte-Carlo framework enables the non-parametric estimation of fiber-specific diffusion-T1T_1 features, thereby showing potential for characterizing developmental or pathological changes in T1T_1 within a given fiber bundle, and for investigating inter-bundle T1T_1 differences.Comment: 11 pages, 6 figures, submitted to Magnetic Resonance in Medicine (MRM) on the 14th of June 202

    Towards 1H-MRSI of the human brain at 7T with slice-selective adiabatic refocusing pulses

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    Contains fulltext : 70576.pdf (publisher's version ) (Closed access)OBJECTIVE: To explore the possibilities of proton spectroscopic imaging (1H-MRSI) of the human brain at 7 Tesla with adiabatic refocusing pulses. MATERIALS AND METHODS: A combination of conventional slice selective excitation and two pairs of slice selective adiabatic refocusing pulses (semi-LASER) results in the formation of an echo from a localized volume. Depending on the used radio frequency (rf) coil efficiency and available rf power, the duration of the adiabatic full passage pulses (AFPs) is adapted to enable echo times down to 50 ms (head coil) or 30 ms (local surface coil). RESULTS: An AFP duration of 5 ms with a corresponding bandwidth of 5.1 kHz resulted in a chemical shift displacement error of 23% over 3.8 ppm at 7T. Using a local surface coil and an echo time down to 30 ms, we detected not only the three main metabolites (NAA, Cr and Cho), but also coupled signals from myo-inositol and glutamate/glutamine in spectra from 0.14 cc voxels with linewidths down to 10 Hz in 10 min measurement time. CONCLUSIONS: The semi-LASER pulse sequence enables 1H-MRSI of the human brain at 7T for larger parts of the brain as well as small localized areas with both a high spectral and spatial resolution

    Bias in MRI Measurements of Apparent Diffusion Coefficient and Kurtosis: Implications for Choice of Maximum Diffusion Encoding

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    Tissue water diffusion is non-Gaussian and the expressions used to calculate diffusion parameters are approximations which introduce systematic errors dependent on the maximum diffusion encoding, diffusion time, etc. This study aimed at characterizing biases in estimates of both apparent diffusion coefficient and kurtosis, and determines their dependence on these parameters. Similar to the approach of several previous studies, Taylor expansion of the diffusion signal was used to calculate biases. Predicted errors were compared with data from one volunteer. Predicted errors agreed well with the measured errors and also the published diffusion tensor imaging measurements. The equations derived predict biases in measured diffusion parameters and explain much of the discrepancy between measurements obtained with different acquisition protocols. The equations may also be used to choose appropriate diffusion encoding for diffusion weighted, tensor, and kurtosis imaging

    Correlations between Diffusion Tensor Imaging (DTI) and Magnetic Resonance Spectroscopy (1H MRS) in schizophrenic patients and normal controls

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    <p>Abstract</p> <p>Background</p> <p>Evidence suggests that white matter integrity may play an underlying pathophysiological role in schizophrenia. N-acetylaspartate (NAA), as measured by Magnetic Resonance Spectroscopy (MRS), is a neuronal marker and is decreased in white matter lesions and regions of axonal loss. It has also been found to be reduced in the prefrontal and temporal regions in patients with schizophrenia. Diffusion Tensor Imaging (DTI) allows one to measure the orientations of axonal tracts as well as the coherence of axonal bundles. DTI is thus sensitive to demyelination and other structural abnormalities. DTI has also shown abnormalities in these regions.</p> <p>Methods</p> <p>MRS and DTI were obtained on 42 healthy subjects and 40 subjects with schizophrenia. The data was analyzed using regions of interests in the Dorso-Lateral Prefrontal white matter, Medial Temporal white matter and Occipital white matter using both imaging modalities.</p> <p>Results</p> <p>NAA was significantly reduced in the patient population in the Medial Temporal regions. DTI anisotropy indices were also reduced in the same Medial Temporal regions. NAA and DTI-anisotropy indices were also correlated in the left medial temporal region.</p> <p>Conclusion</p> <p>Our results implicate defects in the medial temporal white matter in patients with schizophrenia. Moreover, MRS and DTI are complementary modalities for the study of white matter disruptions in patients with schizophrenia.</p

    The role of tissue microstructure and water exchange in biophysical modelling of diffusion in white matter

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    A neuroradiologist’s guide to arterial spin labeling MRI in clinical practice

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