PyDesigner v1.0: A Pythonic Implementation of the DESIGNER Pipeline for Diffusion Magnetic Resonance Imaging.

PyDesigner is a Python-based software package based on the original Diffusion parameter EStImation with Gibbs and NoisE Removal (DESIGNER) pipeline (Dv1) for dMRI preprocessing and tensor estimation. This software is openly provided for non-commercial research and may not be used for clinical care. PyDesigner combines tools from FSL and MRtrix3 to perform denoising, Gibbs ringing correction, eddy current motion correction, brain masking, image smoothing, and Rician bias correction to optimize the estimation of multiple diffusion measures.

Fiber Ball White Matter Modeling Reveals Microstructural Alterations in Healthy Brain Aging.

Age-related white matter degeneration is characterized by myelin breakdown and neuronal fiber loss that preferentially occur in regions that myelinate later in development. Conventional diffusion MRI (dMRI) has demonstrated age-related increases in diffusivity but provide limited information regarding the tissue-specific changes driving these effects. A recently developed dMRI biophysical modeling technique, Fiber Ball White Matter (FBWM) modeling, offers enhanced biological interpretability by estimating microstructural properties specific to the intra-axonal and extra-axonal spaces.

Cortical microstructural changes associated with treated aphasia recovery.

Objectives: To investigate the hypothesis that language recovery in post-stroke aphasia is associated with structural brain changes.

Methods: We evaluated whether treatment-induced improvement in naming is associated with reorganization of tissue microstructure within residual cortical regions. To this end, we performed a retrospective longitudinal treatment study using comprehensive language-linguistic assessments and diffusion MRI sequences optimized for the assessment of complex microstructure (diffusional kurtosis imaging) to evaluate the relationship between language treatment response and cortical changes in 26 individuals with chronic stroke-induced aphasia.

Fiber ball white matter modeling in focal epilepsy.

Multicompartment diffusion magnetic resonance imaging (MRI) approaches are increasingly being applied to estimate intra-axonal and extra-axonal diffusion characteristics in the human brain. Fiber ball imaging (FBI) and its extension fiber ball white matter modeling (FBWM) are such recently described multicompartment approaches. However, these particular approaches have yet to be applied in clinical cohorts.

Diffusion MRI detects early brain microstructure abnormalities in 2-month-old 3×Tg-AD mice.

The 3×Tg-AD mouse is one of the most studied animal models of Alzheimer's disease (AD), and develops both amyloid beta deposits and neurofibrillary tangles in a temporal and spatial pattern that is similar to human AD pathology. Additionally, abnormal myelination patterns with changes in oligodendrocyte and myelin marker expression are reported to be an early pathological feature in this model. Only few diffusion MRI (dMRI) studies have investigated white matter abnormalities in 3×Tg-AD mice, with inconsistent results.

Triple diffusion encoding MRI predicts intra-axonal and extra-axonal diffusion tensors in white matter.

Purpose: To demonstrate how triple diffusion encoding (TDE) MRI can be applied to separately estimate the intra-axonal and extra-axonal diffusion tensors in white matter (WM).

Methods: Using a TDE pulse sequence with an axially symmetric b-matrix, diffusion MRI data were acquired at 3T for 3 healthy adults with an axial b-value of 4000 s/mm , a radial b-value of 307 s/mm , and 64 diffusion encoding directions. This acquisition was then repeated with the radial b-value set to 0.

Optimization of data acquisition and analysis for fiber ball imaging.

The inverse Funk transform of high angular resolution diffusion imaging (HARDI) data provides an estimate for the fiber orientation density function (fODF) in white matter (WM). Since the inverse Funk transform is a straightforward linear transformation, this technique, referred to as fiber ball imaging (FBI), offers a practical means of calculating the fODF that avoids the need for a response function or nonlinear numerical fitting. Nevertheless, the accuracy of FBI depends on both the choice of b-value and the number of diffusion-encoding directions used to acquire the HARDI data.

Diffusion MRI detects longitudinal white matter changes in the 3xTg-AD mouse model of Alzheimer's disease.

The sensitivity of multiple diffusion MRI (dMRI) parameters to longitudinal changes in white matter microstructure was investigated for the 3xTg-AD transgenic mouse model of Alzheimer's disease, which manifests both amyloid beta plaques and neurofibrillary tangles. By employing a specific dMRI method known as diffusional kurtosis imaging, eight different diffusion parameters were quantified to characterize distinct aspects of water diffusion. Four female 3xTg-AD mice were imaged at five time points, ranging from 4.

Measuring intra-axonal T in white matter with direction-averaged diffusion MRI.

Purpose: To demonstrate how the T relaxation time of intra-axonal water (T ) in white matter can be measured with direction-averaged diffusion MRI.

Methods: For b-values larger than about 4000 s/mm , the direction-averaged diffusion MRI signal from white matter is dominated by the contribution from water within axons, which enables T to be estimated by acquiring data for multiple TE values and fitting a mono-exponential decay curve. If given a value of the intra-axonal diffusivity, an extension of the method allows the extra-axonal relaxation time (T ) to be calculated also.

Types of naming errors in chronic post-stroke aphasia are dissociated by dual stream axonal loss.

The types of errors during speech production can vary across individuals with chronic post-stroke aphasia, possibly due to the location and extent of brain damage. In this study, we evaluated the relationship between semantic vs. phonemic errors during confrontational naming, and their relationship with the degree of damage to ventral and dorsal white matter pathways extending beyond the necrotic stroke lesion.

Modeling white matter microstructure with fiber ball imaging.

Fiber ball imaging (FBI) provides a means of calculating the fiber orientation density function (fODF) in white matter from diffusion MRI (dMRI) data obtained over a spherical shell with a b-value of about 4000 s/mm or higher. By supplementing this FBI-derived fODF with dMRI data acquired for two lower b-value shells, it is shown that several microstructural parameters may be estimated, including the axonal water fraction (AWF) and the intrinsic intra-axonal diffusivity. This fiber ball white matter (FBWM) modeling method is demonstrated for dMRI data acquired from healthy volunteers, and the results are compared with those of the white matter tract integrity (WMTI) method.

Comparison of cumulant expansion and q-space imaging estimates for diffusional kurtosis in brain.

Purpose: To compare estimates for the diffusional kurtosis in brain as obtained from a cumulant expansion (CE) of the diffusion MRI (dMRI) signal and from q-space (QS) imaging.

Theory And Methods: For the CE estimates of the kurtosis, the CE was truncated to quadratic order in the b-value and fit to the dMRI signal for b-values from 0 up to 2000s/mm. For the QS estimates, b-values ranging from 0 up to 10,000s/mm were used to determine the diffusion displacement probability density function (dPDF) via Stejskal's formula.

Structural plasticity of the ventral stream and aphasia recovery.

Restrengthening of the residual language network is likely to be crucial for speech recovery in poststroke aphasia. Eight participants with chronic aphasia received intensive speech therapy for 3 weeks, with standardized naming tests and brain magnetic resonance imaging before and after therapy. Kurtosis-based diffusion tensor tractography was used to measure mean kurtosis (MK) along a segment of the inferior longitudinal fasciculus (ILF).

Functional deficits induced by cortical microinfarcts.

Clinical studies have revealed a strong link between increased burden of cerebral microinfarcts and risk for cognitive impairment. Since the sum of tissue damage incurred by microinfarcts is a miniscule percentage of total brain volume, we hypothesized that microinfarcts disrupt brain function beyond the injury site visible to histological or radiological examination. We tested this idea using a mouse model of microinfarcts, where single penetrating vessels that supply mouse cortex were occluded by targeted photothrombosis.

Evaluating kurtosis-based diffusion MRI tissue models for white matter with fiber ball imaging.

In order to quantify well-defined microstructural properties of brain tissue from diffusion MRI (dMRI) data, tissue models are typically employed that relate biological features, such as cell morphology and cell membrane permeability, to the diffusion dynamics. A variety of such models have been proposed for white matter, and their validation is a topic of active interest. In this paper, three different tissue models are tested by comparing their predictions for a specific microstructural parameter to a value measured independently with a recently proposed dMRI method known as fiber ball imaging (FBI).

Dependence on b-value of the direction-averaged diffusion-weighted imaging signal in brain.

Purpose: The dependence of the direction-averaged diffusion-weighted imaging (DWI) signal in brain was studied as a function of b-value in order to help elucidate the relationship between diffusion weighting and brain microstructure.

Methods: High angular resolution diffusion imaging (HARDI) data were acquired from two human volunteers with 128 diffusion-encoding directions and six b-value shells ranging from 1000 to 6000s/mm in increments of 1000s/mm. The direction-averaged signal was calculated for each shell by averaging over all diffusion-encoding directions, and the signal was plotted as a function of b-value for selected regions of interest.