pydesigner-v10-pythonic-implementation-designer-pipeline-for

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) ...

Medical University of South Carolina

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.

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

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). The three tissue models are all constructed with the diffusion and kurtosis tensors, and they are hence compatible with diffusional kurtosis imaging. Nevertheless, the models differ significantly in their details and predictions. For voxels with fractional anisotropies (FAs) exceeding 0.5, all three are reasonably consistent with FBI. However, for lower FA values, one of these, called the white matter tract integrity (WMTI) model, is found to be in much better accord with FBI than the other two, suggesting that the WMTI model has a broader range of applicability.

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

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. We found that in vivo structural and diffusion MRI reliably reported the acute microinfarct core, based on spatial co-registrations with post-mortem stains of neuronal viability. Consistent with our hypothesis, c-Fos assays for neuronal activity and in vivo imaging of single vessel hemodynamics both reported functional deficits in viable peri-lesional tissues beyond the microinfarct core. We estimated that the volume of tissue with functional deficit in cortex was at least 12-fold greater than the volume of the microinfarct core. Impaired hemodynamic responses in peri-lesional tissues persisted at least 14 days, and were attributed to lasting deficits in neuronal circuitry or neurovascular coupling. These data show how individually miniscule microinfarcts could contribute to broader brain dysfunction during vascular cognitive impairment and dementia.

Functional deficits induced by cortical microinfarcts.

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). Therapy-related reduction in the number of semantic but not phonemic errors was associated with strengthening (renormalization) of ILF MK (r = -0.90, p < 0.05 corrected), suggesting that speech recovery is related to structural plasticity of language-specific components of the residual language network. Ann Neurol 2017;82:147-151.

Structural plasticity of the ventral stream and aphasia recovery.

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.

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

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. Both the AWF and the intra-axonal diffusivity obtained with FBWM are found to be significantly larger than for WMTI, with the FBWM values for the intra-axonal diffusivity being more consistent with recent results obtained using isotropic diffusion weighting. An important practical advantage of FBWM is that the only nonlinear fitting required is the minimization of a cost function with just a single free parameter, which facilitates the implementation of efficient and robust numerical routines.

Modeling white matter microstructure with fiber ball imaging.

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. Based on the dual stream model of language processing, we tested the hypothesis that semantic errors would be associated with ventral stream damage, whereas phonemic errors would be associated with dorsal stream damage, but not vice-versa. Multi-shell diffusion MRI was used to obtain kurtosis-based white matter tractography from 32 chronic stroke survivors. Using diffusion microstructural tissue modeling, we estimated axonal loss along the length of the inferior and superior longitudinal fasciculi (ILF and SLF), representing the main pathways in the ventral and dorsal streams, respectively. The frequency of semantic paraphasias was strongly associated with ILF axonal loss, whereas phonemic paraphasias were strongly associated with SLF axonal loss, but not vice versa. This dissociation between semantic and phonological processing is in agreement with the dual stream model of language processing and corroborates the concept that, during speech production, knowledge association (semantics) depends on the integrity of ventral, whereas form encoding (phonological encoding) is more localized to dorsal pathways. These findings also demonstrate the importance of the residual integrity of specific white matter pathways beyond regional gray matter damage for speech production.

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

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

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

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 4.5 to 18 months of age, and the diffusion parameters were investigated in four white matter regions (fimbria, external capsule, internal capsule and corpus callosum). Significant changes were observed in several diffusion parameters, particularly in the fimbria and in the external capsule, with a statistically significant decrease in diffusivity and a statistically significant increase in kurtosis. Our preliminary results demonstrate that dMRI can detect microstructural changes in white matter for the 3xTg-AD mouse model due to aging and/or progression of pathology, depending strongly on the diffusion parameter and anatomical region.

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

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. To inform the design of optimal scan protocols for its implementation, FBI predictions are investigated here with in vivo data from healthy adult volunteers acquired at 3 T for b-values spanning 1000 to 10,000 s/mm, for diffusion-encoding directions varying in number from 30 to 256 and for TE ranging from 90 to 120 ms. Our results suggest b-values above 4000 s/mm with at least 64 diffusion-encoding directions are adequate to achieve reasonable accuracy with FBI for calculating axon-specific diffusion measures and for performing WM fiber tractography (WMFT).

Optimization of data acquisition and analysis for fiber ball imaging.

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).

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

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. Thus, the goal of this study was to investigate the sensitivity of dMRI to capture brain microstructural alterations in 2-month-old 3×Tg-AD mice. In the fimbria, the fractional anisotropy (FA), kurtosis fractional anisotropy (KFA), and radial kurtosis (K ) were found to be significantly lower in 3×Tg-AD mice than in controls, while the mean diffusivity (MD) and radial diffusivity (D ) were found to be elevated. In the fornix, K was lower for 3×Tg-AD mice; in the dorsal hippocampus MD and D were elevated, as were FA, MD, and D in the ventral hippocampus. These results indicate, for the first time, dMRI changes associated with myelin abnormalities in young 3×Tg-AD mice, before they develop AD pathology. Morphological quantification of myelin basic protein immunoreactivity in the fimbria was significantly lower in the 3×Tg-AD mice compared with the age-matched controls. Our results demonstrate that dMRI is able to detect widespread, significant early brain morphological abnormalities in 2-month-old 3×Tg-AD mice.

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

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. The modeling of several diffusion parameters with interpretable biological meaning may offer the development of new, noninvasive biomarkers of pharmacoresistance in epilepsy. In the present study, we used FBI and FBWM to evaluate intra-axonal and extra-axonal diffusion properties of white matter tracts in patients with longstanding focal epilepsy. FBI/FBWM diffusion parameters were calculated along the length of 50 white matter tract bundles and statistically compared between patients with refractory epilepsy, nonrefractory epilepsy and controls. We report that patients with chronic epilepsy had a widespread distribution of extra-axonal diffusivity relative to controls, particularly in circumscribed regions along white matter tracts projecting to cerebral cortex from thalamic, striatal, brainstem, and peduncular regions. Patients with refractory epilepsy had significantly greater markers of extra-axonal diffusivity compared to those with nonrefractory epilepsy. The extra-axonal diffusivity alterations in patients with epilepsy observed in the present study could be markers of neuroinflammatory processes or a reflection of reduced axonal density, both of which have been histologically demonstrated in focal epilepsy. FBI is a clinically feasible MRI approach that provides the basis for more interpretive conclusions about the microstructural environment of the brain and may represent a unique biomarker of pharmacoresistance in epilepsy.

Fiber ball white matter modeling in focal epilepsy.

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

Cortical microstructural changes associated with treated aphasia recovery.

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. We used FBWM to illustrate the biological mechanisms underlying changes throughout white matter in healthy aging using data from 63 cognitively unimpaired adults ages 45-85 with no radiological evidence of neurodegeneration or incipient Alzheimer's disease. Conventional dMRI and FBWM metrics were computed for two late-myelinating (genu of the corpus callosum and association tracts) and two early-myelinating regions (splenium of the corpus callosum and projection tracts). We examined the associations between age and these metrics in each region and tested whether age was differentially associated with these metrics in late- vs. early-myelinating regions. We found that conventional metrics replicated patterns of age-related increases in diffusivity in late-myelinating regions. FBWM additionally revealed specific intra- and extra-axonal changes suggestive of myelin breakdown and preferential loss of smaller-diameter axons, yielding  corroboration of findings from histopathological studies of aged brains. These results demonstrate that advanced biophysical modeling approaches, such as FBWM, offer novel information about the microstructure-specific alterations contributing to white matter changes in healthy aging. These tools hold promise as sensitive indicators of early pathological changes related to neurodegenerative disease.

Article	Year
Dependence on b-value of the direction-averaged diffusion-weighted imaging signal in brain. Magnetic resonance imaging\| PubMed ID: 27989904	2017
Evaluating kurtosis-based diffusion MRI tissue models for white matter with fiber ball imaging. NMR in biomedicine\| PubMed ID: 28085211	2017
Functional deficits induced by cortical microinfarcts. Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism\| PubMed ID: 28090802	2017
Structural plasticity of the ventral stream and aphasia recovery. Annals of neurology\| PubMed ID: 28628946	2017
Comparison of cumulant expansion and q-space imaging estimates for diffusional kurtosis in brain. Magnetic resonance imaging\| PubMed ID: 29306048	2018
Modeling white matter microstructure with fiber ball imaging. NeuroImage\| PubMed ID: 29660512	2018
Types of naming errors in chronic post-stroke aphasia are dissociated by dual stream axonal loss. Scientific reports\| PubMed ID: 30254222	2018
Measuring intra-axonal T in white matter with direction-averaged diffusion MRI. Magnetic resonance in medicine\| PubMed ID: 30506959	2019
Diffusion MRI detects longitudinal white matter changes in the 3xTg-AD mouse model of Alzheimer's disease. Magnetic resonance imaging\| PubMed ID: 30543850	2019
Optimization of data acquisition and analysis for fiber ball imaging. NeuroImage\| PubMed ID: 31284026	2019
Triple diffusion encoding MRI predicts intra-axonal and extra-axonal diffusion tensors in white matter. Magnetic resonance in medicine\| PubMed ID: 31763730	2020
Diffusion MRI detects early brain microstructure abnormalities in 2-month-old 3×Tg-AD mice. NMR in biomedicine\| PubMed ID: 32557874	2020
Fiber ball white matter modeling in focal epilepsy. Human brain mapping\| PubMed ID: 33605514	2021
Cortical microstructural changes associated with treated aphasia recovery. Annals of clinical and translational neurology\| PubMed ID: 34406705	2021
Fiber Ball White Matter Modeling Reveals Microstructural Alterations in Healthy Brain Aging. Aging brain\| PubMed ID: 36324695	2022

Emilie T. McKinnon

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