Neurite Orientation Dispersion And Density Imaging Research Articles

C-NODDI: a constrained NODDI model for axonal density and orientation determinations in cerebral white matter.

Neurite orientation dispersion and density imaging (NODDI) provides measures of neurite density and dispersion through computation of the neurite density index (NDI) and the orientation dispersion index (ODI). However, NODDI overestimates the cerebrospinal fluid water fraction in white matter (WM) and provides physiologically unrealistic high NDI values. Furthermore, derived NDI values are echo-time (TE)-dependent. In this work, we propose a modification of NODDI, named constrained NODDI (C-NODDI), for NDI and ODI mapping in WM. Using NODDI and C-NODDI, we investigated age-related alterations in WM in a cohort of 58 cognitively unimpaired adults. Further, NDI values derived using NODDI or C-NODDI were correlated with the neurofilament light chain (NfL) concentration levels, a plasma biomarker of axonal degeneration. Finally, we investigated the TE dependence of NODDI or C-NODDI derived NDI and ODI. ODI derived values using both approaches were virtually identical, exhibiting constant trends with age. Further, our results indicated a quadratic relationship between NDI and age suggesting that axonal maturation continues until middle age followed by a decrease. This quadratic association was notably significant in several WM regions using C-NODDI, while limited to a few regions using NODDI. Further, C-NODDI-NDI values exhibited a stronger correlation with NfL concentration levels as compared to NODDI-NDI, with lower NDI values corresponding to higher levels of NfL. Finally, we confirmed the previous finding that NDI estimation using NODDI was dependent on TE, while NDI derived values using C-NODDI exhibited lower sensitivity to TE in WM. C-NODDI provides a complementary method to NODDI for determination of NDI in white matter.

Comparison of different neurite density metrics with brain asymmetry evaluation

The standard diffusion MRI model with intra- and extra-axonal water pools offers a set of microstructural parameters describing brain white matter architecture. However, non-linearities in the standard model and diffusion data contamination by noise and imaging artefacts make estimation of diffusion metrics challenging. In order to develop reliable diffusion approaches and to avoid computational model degeneracy, additional theoretical assumptions allowing stable numerical implementations are required. Advanced diffusion approaches allow for estimation of intra-axonal water fraction (AWF), describing a key structural characteristic of brain tissue. AWF can be interpreted as an indirect measure or proxy of neurite density and has a potential as useful clinical biomarker. Established diffusion approaches such as white matter tract integrity, neurite orientation dispersion and density imaging (NODDI), and spherical mean technique provide estimates of AWF within their respective theoretical frameworks. In the present study, we estimated AWF metrics using different diffusion approaches and compared measures of brain asymmetry between the different metrics in a sub-sample of 182 subjects from the UK Biobank. Multivariate decomposition by mean of linked independent component analysis revealed that the various AWF proxies derived from the different diffusion approaches reflect partly non-overlapping variance of independent components, with distinct anatomical distributions and sensitivity to age. Further, voxel-wise analysis revealed age-related differences in AWF-based brain asymmetry, indicating less apparent left-right hemisphere difference with higher age. Finally, we demonstrated that NODDI metrics suffer from a quite strong dependence on used numerical algorithms and post-processing pipeline. The analysis based on AWF metrics strongly depends on the used diffusion approach and leads to poorly reproducible results.

White matter microstructural disruption in minimal hepatic encephalopathy: a neurite orientation dispersion and density imaging (NODDI) study.

To evaluate the ability of neurite orientation dispersion and density imaging (NODDI) for detecting white matter (WM) microstructural abnormalities in minimal hepatic encephalopathy (MHE). Diffusion-weighted images, enabling the estimation of NODDI and diffusion tensor imaging (DTI) parameters, were acquired from 20 healthy controls (HC), 22 cirrhotic patients without MHE (NHE), and 15 cirrhotic patients with MHE. Tract-based spatial statistics were used to determine differences in DTI (including fractional anisotropy [FA] and mean/axial/radial diffusivity [MD/AD/RD]) and NODDI parameters (including neurite density index [NDI], orientation dispersion index [ODI], and isotropic volume fraction [ISO]). Voxel-wise analyses of correlations between diffusion parameters and neurocognitive performance determined by Psychometric Hepatic Encephalopathy Score (PHES) were completed. MHE patients had extensive NDI reduction and rare ODI reduction, primarily involving the genu and body of corpus callosum and the bilateral frontal lobe, corona radiata, external capsule, anterior limb of internal capsule, temporal lobe, posterior thalamic radiation, and brainstem. The extent of NDI and ODI reduction expanded from NHE to MHE. In both MHE and NHE groups, the extent of NDI change was quite larger than that of FA change. No significant intergroup difference in ISO/MD/AD/RD was observed. Tissue specificity afforded by NODDI revealed the underpinning of FA reduction in MHE. The NDI in left frontal lobe was significantly correlated with PHES. MHE is characterized by diffuse WM microstructural impairment (especially neurite density reduction). NODDI can improve the detection of WM microstructural impairments in MHE and provides more precise information about MHE-related pathology than DTI.

Mapping acute neuroinflammation in vivo with diffusion-MRI in rats given a systemic lipopolysaccharide challenge

It is becoming increasingly apparent that neuroinflammation plays a critical role in an array of neurological and psychiatric disorders. Recent studies have demonstrated the potential of diffusion MRI (dMRI) to characterize changes in microglial density and morphology associated with neuroinflammation, but these were conducted mostly ex vivo and/or in extreme, non-physiological animal models. Here, we build upon these studies by investigating the utility of well-established dMRI methods to detect neuroinflammation in vivo in a more clinically relevant animal model of sickness behavior. We show that diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) indicate widespread increases in diffusivity in the brains of rats given a systemic lipopolysaccharide challenge (n = 20) vs. vehicle-treated controls (n = 12). These diffusivity changes correlated with histologically measured changes in microglial morphology, confirming the sensitivity of dMRI to neuroinflammatory processes. This study marks a further step towards establishing a noninvasive indicator of neuroinflammation, which would greatly facilitate early diagnosis and treatment monitoring in various neurological and psychiatric diseases.

Neurite orientation dispersion and density imaging of white matter microstructure in sensory processing dysfunction with versus without comorbid ADHD.

Sensory Processing Dysfunction (SPD) is common yet understudied, affecting up to one in six children with 40% experiencing co-occurring challenges with attention. The neural architecture of SPD with Attention Deficit and Hyperactivity Disorder (ADHD) (SPD+ADHD) versus SPD without ADHD (SPD-ADHD) has yet to be explored in diffusion tensor imaging (DTI) and Neurite Orientation Dispersion and Density Imaging (NODDI) has yet to be examined. The present study computed DTI and NODDI biophysical model parameter maps of one hundred children with SPD. Global, regional and voxel-level white matter tract measures were analyzed and compared between SPD+ADHD and SPD-ADHD groups. SPD+ADHD children had global WM Fractional Anisotropy (FA) and Neurite Density Index (NDI) that trended lower than SPD-ADHD children, primarily in boys only. Data-driven voxelwise and WM tract-based analysis revealed statistically significant decreases of NDI in boys with SPD+ADHD compared to those with SPD-ADHD, primarily in projection tracts of the internal capsule and commissural fibers of the splenium of the corpus callosum. We conclude that WM microstructure is more delayed/disrupted in boys with SPD+ADHD compared to SPD-ADHD, with NODDI showing a larger effect than DTI. This may represent the combined WM pathology of SPD and ADHD, or it may result from a greater degree of SPD WM pathology causing the development of ADHD.

Association of retinal nerve layers thickness and brain imaging in healthy young subjects from the i-Share-Bordeaux study.

Given the anatomical and functional similarities between the retina and the brain, the retina could be a "window" for viewing brain structures. We investigated the association between retinal nerve fiber layers (peripapillary retinal nerve fiber layer, ppRNFL; macular ganglion cell-inner plexiform layer, GC-IPL; and macular ganglion cell complex, GCC), and brain magnetic resonance imaging (MRI) parameters in young health adults. We included 857 students (mean age: 23.3 years, 71.3% women) from the i-Share study. We used multivariate linear models to study the cross-sectional association of each retinal nerve layer thickness assessed by spectral-domain optical coherence tomography (SD-OCT) with structural (volumes and cortical thickness), and microstructural brain markers, assessed on MRI globally and regionally. Microstructural MRI parameters included diffusion tensor imaging (DTI) and Neurite Orientation Dispersion and Density Imaging (NODDI). On global brain analysis, thicker ppRNFL, GC-IPL and GCC were all significantly associated with patterns of diffusion metrics consistent with higher WM microstructural integrity. In regional analyses, after multiple testing corrections, our results suggested significant associations of some retinal nerve layers with brain regional gray matter occipital volumes and with diffusion MRI parameters in a region involved in the visual pathway and in regions containing associative tracts. No associations were found with global volumes or with global or regional cortical thicknesses. Results of this study suggest that some retinal nerve layers may reflect brain structures. Further studies are needed to confirm these results in young subjects.

Astrogliosis, neuritic microstructure, and sex effects: GFAP is an indicator of neuritic orientation in women

BackgroundData from human studies suggest that immune dysregulation is associated with Alzheimer’s disease (AD) pathology and cognitive decline and that neurites may be affected early in the disease trajectory. Data from animal studies further indicate that dysfunction in astrocytes and inflammation may have a pivotal role in facilitating dendritic damage, which has been linked with negative cognitive outcomes. To elucidate these relationships further, we have examined the relationship between astrocyte and immune dysregulation, AD-related pathology, and neuritic microstructure in AD-vulnerable regions in late life. MethodsWe evaluated panels of immune, vascular, and AD-related protein markers in blood and conducted in vivo multi-shell neuroimaging using Neurite Orientation Dispersion and Density Imaging (NODDI) to assess indices of neuritic density (NDI) and dispersion (ODI) in brain regions vulnerable to AD in a cohort of older adults (n = 109). ResultsWhen examining all markers in tandem, higher plasma GFAP levels were strongly related to lower neurite dispersion (ODI) in grey matter. No biomarker associations were found with higher neuritic density. Associations between GFAP and neuritic microstructure were not significantly impacted by symptom status, APOE status, or plasma Aβ42/40 ratio; however, there was a large sex effect observed for neurite dispersion, wherein negative associations between GFAP and ODI were only observed in females. DiscussionThis study provides a comprehensive, concurrent appraisal of immune, vascular, and AD-related biomarkers in the context of advanced grey matter neurite orientation and dispersion methodology. Sex may be an important modifier of the complex associations between astrogliosis, immune dysregulation, and brain microstructure in older adults.

ID: 219715 Correlating Multi-Spectral Diffusion Weighted Imaging Quantitative Maps With Unified Parkinson's Disease Rating Scale Scores

The Unified Parkinson’s Disease Rating Scale (UPDRS) is used to rate the severity and course of disease in patients with Parkinson’s disease (PD), though assessment scores can vary due to subjectivity. However, quantitative maps such as diffusion tensor imaging (DTI), neurite orientation dispersion and density imaging (NODDI), or diffusion kurtosis imaging (DKI) can serve as objective assessments. Aiming to provide greater consistency and ability to predict the severity of UPDRS scores, we correlated quantitative maps with UPDRS-III scores to determine the ability to generate non-invasive biomarkers.

ID: 218886 Correlating Multi-Spectral Diffusion Weighted Imaging Quantitative Maps With Gait Disturbances in Parkinson's Disease

Parkinson’s disease (PD) presents with varying gait symptoms. These range from no gait issues (NG) to gait disturbance (GD) to freezing-of-gait (FOG). GD includes slowing gait, shuffling, and instability, while FOG is the inability to take a step, potentially leading to falls. Quantitative maps like diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), and neurite orientation dispersion and density imaging (NODDI) can provide an objective assessment for gait disturbances, potentially serving as non-invasive biomarkers.

Effects of acute alcohol exposure and chronic alcohol use on neurite orientation dispersion and density imaging (NODDI) parameters.

Little is known about how acute and chronic alcohol exposure may alter the in vivo membrane properties of neurons. We employed neurite orientation dispersion and density imaging (NODDI) to examine acute and chronic effects of alcohol exposure on neurite density. Twenty-one healthy social drinkers (CON) and thirteen nontreatment-seeking individuals with alcohol use disorder (AUD) underwent a baseline multi-shell diffusion magnetic resonance imaging (dMRI) scan. A subset (10 CON, 5 AUD) received dMRI during intravenous infusions of saline and alcohol during dMRI. NODDI parametric images included orientation dispersion (OD), isotropic volume fraction (ISOVF), and corrected intracellular volume fraction (cICVF). Diffusion tensor imaging metrics of fractional anisotropy and mean, axial, and radial diffusivity (FA, MD, AD, RD) were also computed. Average parameter values were extracted from white matter (WM) tracts defined by the Johns Hopkins University atlas. There were group differences in FA, RD, MD, OD, and cICVF, primarily in the corpus callosum. Both saline and alcohol had effects on AD and cICVF in WM tracts proximal to the striatum, cingulate, and thalamus. This is the first work to indicate that acute fluid infusions may alter WM properties, which are conventionally believed to be insensitive to acute pharmacological challenges. It also suggests that the NODDI approach may be sensitive to transient changes in WM. The next steps should include determining if the effect on neurite density differs with solute or osmolality, or both, and translational studies to assess how alcohol and osmolality affect the efficiency of neurotransmission.

Corticospinal fibers with different origins impair in amyotrophic lateral sclerosis: A neurite orientation dispersion and density imaging study.

To investigate microstructural impairments of corticospinal tracts (CSTs) with different origins in amyotrophic lateral sclerosis (ALS) using neurite orientation dispersion and density imaging (NODDI). Diffusion-weighted imaging data acquired from 39 patients with ALS and 50 controls were used to estimate NODDI and diffusion tensor imaging (DTI) models. Fine maps of CST subfibers originating from the primary motor area (M1), premotor cortex, primary sensory area, and supplementary motor area (SMA) were segmented. NODDI metrics (neurite density index [NDI] and orientation dispersion index [ODI]) and DTI metrics (fractional anisotropy [FA] and mean/axial/radial diffusivity [MD/AD/RD]) were computed. The patients with ALS showed microstructural impairments (reflected by NDI, ODI, and FA reductions and MD, AD, and RD increases) in CST subfibers, especially in M1 fibers, which correlated with disease severity. Compared with other diffusion metrics, NDI yielded a higher effect size and detected the greatest extent of CST subfibers damage. Logistic regression analyses based on NDI in M1 subfiber yielded the best diagnostic performance compared with other subfibers and the whole CST. Microstructural impairment of CST subfibers (especially those originating from M1) is the key feature of ALS. The combination of NODDI and CST subfibers analysis may improve diagnosing performance for ALS.

Relationship Between Microstructural Alterations and Cognitive Decline After Whole-Brain Radiation Therapy for Brain Metastases: An Exploratory Whole-Brain MR Analysis Based on Neurite Orientation Dispersion and Density Imaging.

Cognitive impairment frequently occurs in patients with brain metastases (BM) after whole-brain radiotherapy (WBRT). It is crucial to explore the underlying mechanisms of cognitive impairment in BM patients receiving WBRT. To detect brain microstructural alterations in patients after WBRT by neurite orientation dispersion and density imaging (NODDI), and evaluate the performance of microstructural alterations in predicting cognitive impairment. Prospective. Twenty-six patients (seven female; mean age, 60.9 years). 3-T, multi-shell diffusion-weighted single-shot echo-planar sequence. Three-dimensional magnetization-prepared rapid acquisition with gradient echo sequence. Mini-mental state examination (MMSE) evaluations were conducted prior to, following, 1 and 3 months after WBRT. The diffusion data were collected twice, 1 week before and 1 week after WBRT. NODDI analysis was conducted to assess microstructural alterations in whole brain (orientation dispersion index, neurite density index, volume fraction of isotropic water molecules). Reliable change indices (RCI) of MMSE were used to measure cognitive decline. The performance of support vector machine models based on NODDI parameters and clinical features (prednisone usage, tumor volume, etc.) in predicting MMSE-RCI was evaluated. Paired t-test to assess alterations of NODDI measures and MMSE during follow-up. Statistical significance level of P-value <0.05. Significantly decreased MMSE score was found at 3 months after WBRT. After WBRT, corpus callosum, medial prefrontal cortex, limbic lobe, occipital lobe, parietal lobe, putamen, globus pallidus lentiform, and thalamus demonstrated damage in NODDI parameters. The predicted MMSE-RCI based on NODDI features was significantly associated with the measured MMSE-RCI at 1 month (R = 0.573; P = 0.003) and 3 months (R = 0.687; P < 0.0001) after WBRT. Microstructural alterations in several brain regions including the middle prefrontal and limbic cortexes were observed in patients with BM following WBRT, which may contribute to subsequent cognitive decline. 2 TECHNICAL EFFICACY: Stage 2.

A comparison of altered white matter microstructure in youth born with congenital heart disease or born preterm.

Alterations to white matter microstructure as detected by diffusion tensor imaging have been documented in both individuals born with congenital heart disease (CHD) and individuals born preterm. However, it remains unclear if these disturbances are the consequence of similar underlying microstructural disruptions. This study used multicomponent driven equilibrium single pulse observation of T1 and T2 (mcDESPOT) and neurite orientation dispersion and density imaging (NODDI) to characterize and compare alterations to three specific microstructural elements of white matter - myelination, axon density, and axon orientation - in youth born with CHD or born preterm. Participants aged 16 to 26 years with operated CHD or born ≤33 weeks gestational age and a group of healthy peers of the same age underwent a brain MRI including mcDESPOT and high angular resolution diffusion imaging acquisitions. Using tractometry, average values of myelin water fraction (MWF), neurite density index (NDI), and orientation dispersion index (ODI) were first calculated and compared between groups for 30 white matter bundles. Afterwards, bundle profiling was performed to further characterize the topology of the detected microstructural alterations. The CHD and preterm groups both presented with widespread bundles and bundle segments with lower MWF, accompanied by some occurrences of lower NDI, relative to controls. While there were no differences in ODI between the CHD and control groups, the preterm group presented with both higher and lower ODI compared to the control group and lower ODI compared to the CHD group. While youth born with CHD or born preterm both presented with apparent deficits in white matter myelination and axon density, youth born preterm presented with a unique profile of altered axonal organization. Future longitudinal studies should aim to better understand the emergence of these common and distinct microstructural alterations, which could orient the development of novel therapeutic approaches.

The role of MR diffusion kurtosis and neurite orientation dispersion and density imaging in evaluating gliomas.

Conventional MRI sequences in neuro-oncology are insufficient for glioma grading. However, newly developed diffusion-weighted imaging techniques have been shown to have a great potential for glioma grading. This study examined the diagnostic performance of diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), neurite orientation dispersion and density imaging (NODDI), and their combinations in glioma grading. Multishell diffusion tensor images were obtained with 3T MRI in 38 glioma patients (22 high-grade glioma [HGG], 16 low-grade glioma [LGG]). DTI (fractional anisotropy [FA], mean diffusivity [MD], axial diffusivity [AD], radial diffusivity [RD]), DKI (Axial kurtosis [AK], mean kurtosis [MK], radial kurtosis [RK]), and NODDI (intracellular volume fraction [ICVF], orientation distribution index, isotropic water fraction [ISO]) images were obtained after preprocessing. The average value of these parameters was calculated in the solid components of the tumors. The receiver operating characteristic curve analyses were performed to investigate the diagnostic performance and the curves were compared with the Delong test. FA shows an increase in HGG, while MD, RD, and AD exhibit a decrease. AK, MK, and RK were higher in HGG than LGG. ICVF increased in HGG, while ISO decreased. AK demonstrated the best diagnostic performance among all parameters, and kurtosis outperformed NODDI but not DTI. Combining these parameters did not yield a statistically significant improvement in diagnostic performance. DTI, DKI, and NODDI approaches can differentiate between HGG and LGG; however, kurtosis parameters perform better and adding NODDI parameters does not improve diagnostic performance. Using multishell b-value has not led to an increase in diagnostic performance.

High-resolution diffusion-weighted imaging at 7 Tesla: Single-shot readout trajectories and their impact on signal-to-noise ratio, spatial resolution and accuracy

Diffusion MRI (dMRI) is a valuable imaging technique to study the connectivity and microstructure of the brain in vivo. However, the resolution of dMRI is limited by the low signal-to-noise ratio (SNR) of this technique. Various multi-shot acquisition strategies have been developed to achieve sub-millimeter resolution, but they require long scan times which can be restricting for patient scans. Alternatively, the SNR of single-shot acquisitions can be increased by using a spiral readout trajectory to minimize the sequence echo time. Imaging at ultra-high fields (UHF) could further increase the SNR of single-shot dMRI; however, the shorter T2* of brain tissue and the greater field non-uniformities at UHFs will degrade image quality, causing image blurring, distortions, and signal loss.In this study, we investigated the trade-off between the SNR and resolution of different k-space trajectories, including echo planar imaging (EPI), partial Fourier EPI, and spiral trajectories, over a range of dMRI resolutions at 7T. The effective resolution, spatial specificity and sharpening effect were measured from the point spread function (PSF) of the simulated diffusion sequences for a nominal resolution range of 0.6–1.8 mm. In-vivo partial brain scans at a nominal resolution of 1.5 mm isotropic were acquired using the three readout trajectories to validate the simulation results. Field probes were used to measure dynamic magnetic fields offline up to the 3rd order of spherical harmonics. Image reconstruction was performed using static ΔB0 field maps and the measured trajectories to correct image distortions and artifacts, leaving T2* effects as the primary source of blurring. The effective resolution was examined in fractional anisotropy (FA) maps calculated from a multi-shell dataset with b-values of 300, 1000, and 2000 s/mm2 in 5, 16, and 48 directions, respectively. In-vivo scans at nominal resolutions of 1, 1.2, and 1.5 mm were acquired and the SNR of the different trajectories calculated using the multiple replica method to investigate the SNR. Finally, in-vivo whole brain scans with an effective resolution of 1.5 mm isotropic were acquired to explore the SNR and efficiency of different trajectories at a matching effective resolution. FA and intra-cellular volume fraction (ICVF) maps calculated using neurite orientation dispersion and density imaging (NODDI) were used for the comparison. The simulations and in vivo imaging results showed that for matching nominal resolutions, EPI trajectories had the highest specificity and effective resolution with maximum image sharpening effect. However, spirals have a significantly higher SNR, in particular at higher resolutions and even when the effective image resolutions are matched. Overall, this work shows that the higher SNR of single-shot spiral trajectories at 7T allows us to achieve higher effective resolutions compared to EPI and PF-EPI to map the microstructure and connectivity of small brain structures.

White Matter Changes after Neurobehavioral Therapy for Functional Seizures.

We aimed to prospectively quantify changes in white matter morphology after neurobehavioral therapy (NBT) for functional seizures (FS) using neurite orientation dispersion and density imaging (NODDI). We hypothesized that patients with FS would exhibit white matter plasticity in the uncinate fasciculus, fornix/stria terminalis, cingulum, and corticospinal tract following NBT that would correlate with improvements in affective symptoms, postconcussive symptoms, and quality of life (QOL). Forty-two patients with traumatic brain injury (TBI) and FS (TBI+FS) underwent NBT and provided pre-/postintervention neuroimaging and behavioral data; 47 controls with TBI without FS (TBI-only) completed the same measures but did not receive NBT. Changes in neurite density, orientation dispersion (orientation dispersion index [ODI]), and extracellular free water (FW) were compared between groups. Significant ODI increases in the left uncinate fasciculus in TBI+FS (mean difference = 0.017, p = 0.039) correlated with improvements in posttraumatic symptoms (r = -0.395, p = 0.013), QOL (r = 0.474, p = 0.002), emotional well-being (r = 0.524, p < 0.001), and energy (r = 0.474, p = 0.002). In TBI-only, ODI decreased (mean difference = -0.008, p = 0.047) and FW increased (mean difference = 0.011, p = 0.003) in the right cingulum. FW increases correlated with increased psychological problems (r = 0.383, p = 0.013). In TBI+FS, NBT resulted in FS decreases of 3.5 seizures per week. None of the imaging changes correlated with FS frequency. We identified white matter changes after NBT in patients with FS that were associated with improved psychosocial functioning. NODDI could be incorporated into future mechanistic assessments of interventions in patients with FS. ANN NEUROL 2023;94:350-365.

A microstructure estimation Transformer inspired by sparse representation for diffusion MRI

Diffusion magnetic resonance imaging (dMRI) is an important tool in characterizing tissue microstructure based on biophysical models, which are typically multi-compartmental models with mathematically complex and highly non-linear forms. Resolving microstructures from these models with conventional optimization techniques is prone to estimation errors and requires dense sampling in the q-space with a long scan time. Deep learning based approaches have been proposed to overcome these limitations. Motivated by the superior performance of the Transformer in feature extraction than the convolutional structure, in this work, we present a learning-based framework based on Transformer, namely, a Microstructure Estimation Transformer with Sparse Coding (METSC) for dMRI-based microstructural parameter estimation. To take advantage of the Transformer while addressing its limitation in large training data requirement, we explicitly introduce an inductive bias-model bias into the Transformer using a sparse coding technique to facilitate the training process. Thus, the METSC is composed with three stages, an embedding stage, a sparse representation stage, and a mapping stage. The embedding stage is a Transformer-based structure that encodes the signal in a high-level space to ensure the core voxel of a patch is represented effectively. In the sparse representation stage, a dictionary is constructed by solving a sparse reconstruction problem that unfolds the Iterative Hard Thresholding (IHT) process. The mapping stage is essentially a decoder that computes the microstructural parameters from the output of the second stage, based on the weighted sum of normalized dictionary coefficients where the weights are also learned. We tested our framework on two dMRI models with downsampled q-space data, including the intravoxel incoherent motion (IVIM) model and the neurite orientation dispersion and density imaging (NODDI) model. The proposed method achieved up to 11.25 folds of acceleration while retaining high fitting accuracy for NODDI fitting, reducing the mean squared error (MSE) up to 70% compared with the previous q-space learning approach. METSC outperformed the other state-of-the-art learning-based methods, including the model-free and model-based methods. The network also showed robustness against noise and generalizability across different datasets. The superior performance of METSC indicates its potential to improve dMRI acquisition and model fitting in clinical applications.

Characterization of FTLD spectrum through advanced diffusion-weighted MRI metrics: a connectome approach (P11-6.003)

<h3>Objective:</h3> To investigate structural alterations in brain network of patients within the frontotemporal lobar degeneration (FTLD) spectrum using connectome analysis with advanced diffusion-weighted MRI metrics. <h3>Background:</h3> MRI connectomics is a promising tool to describe network-based degeneration in neurodegenerative diseases. Neurite orientation dispersion and density imaging (NODDI) has shown to provide novel insights on structural connectivity alterations. <h3>Design/Methods:</h3> Thirty-four behavioral-variant frontotemporal dementia (bvFTD), 11 semantic variant primary progressive aphasia (svPPA), 11 nonfluent (nfvPPA) patients and 48 healthy controls underwent multi-shell diffusion MRI. Fractional anisotropy (FA) maps were computed. Intra-cellular Volume Fraction (ICVF) maps were also estimated using NODDI, providing a direct quantification of neurite integrity. Graph analysis and connectomics assessed global and local structural topological network properties and regional structural connectivity. <h3>Results:</h3> Overall, widespread structural changes were observed in bvFTD patients relative to healthy controls and svPPA patients in terms of FA-derived network properties. nfvPPA patients also showed altered FA topological properties at global level compared to healthy controls. Sum of node weights (SN) in the sensorimotor lobe revealed that nfvPPA patients showed an altered connection strength compared to svPPA. Moreover, nfvPPA patients showed a significant decreased FA in the left hemispheric fronto-temporal-insular regions relative to controls. Considering ICVF, more severe alterations compared to FA maps allowed to find differences also between svPPA and nfvPPA patients. ICVF graph analysis measures also showed that svPPA had a lower degree centrality and SN in the temporal lobe compared to controls. <h3>Conclusions:</h3> These findings suggest that conventional diffusion-tensor measures might be sensitive enough to highlight vulnerable connections in the FTLD spectrum. However, ICVF demonstrated to be a more specific biomarker to differentiate FTLD syndromes. Specifically, the benefits emerged in the differentiation between svPPA patients and other groups. <b>Disclosure:</b> Federica Agosta has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Philips. Federica Agosta has received personal compensation in the range of $500-$4,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for Elsevier INC. Silvia Basaia has nothing to disclose. Dr. Facente has nothing to disclose. Ms. Cividini has nothing to disclose. Dr. Spinelli has nothing to disclose. The institution of Elisa Canu has received research support from Italian Ministry of Health . Dr. Castelnovo has nothing to disclose. Giuseppe Magnani has nothing to disclose. Dr. Caso has nothing to disclose. Paola Caroppo has nothing to disclose. Sara Prioni has nothing to disclose. Miss Villa has nothing to disclose. Lucio Tremolizzo has nothing to disclose. Dr. Appollonio has nothing to disclose. Dr. Silani has nothing to disclose. Dr. Filippi has received personal compensation in the range of $5,000-$9,999 for serving as a Consultant for Bayer, Biogen Idec, Merck-Serono, Novartis, Roche, Sanofi Genzyme, Takeda, and Teva Pharmaceutical Industries. Dr. Filippi has received personal compensation in the range of $5,000-$9,999 for serving on a Speakers Bureau for Bayer, Biogen Idec, Merck-Serono, Novartis, Roche, Sanofi Genzyme, Takeda, and Teva Pharmaceutical Industries. Dr. Filippi has received personal compensation in the range of $5,000-$9,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for Springer Nature. The institution of Dr. Filippi has received research support from Biogen Idec, Merck-Serono, Novartis, Roche, Teva Pharmaceutical Industries, Italian Ministry of Health, Fondazione Italiana Sclerosi Multipla, and ARiSLA (Fondazione Italiana di Ricerca per la SLA).

Dystonia is Associated with Macro and Microstructural Abnormalities of the Cerebellum: Analysis of Volumetric and Diffusion-Weighted MRI Data in the UK Biobank (P11-11.004)

<h3>Objective:</h3> To determine whether subjects with dystonia in the UK Biobank exhibit MRI-based cerebellar pathology. <h3>Background:</h3> Dystonia is a movement disorder characterized by sustained or intermittent muscle contractions causing abnormal movements and/or postures. Although classically considered a basal-ganglia disorder, neuroimaging studies of dystonia have revealed physiologic, structural, and functional changes in both the (1) pallido-thalamic and (2) cerebello-thalamic networks. Diffusion-weighted-MRI (DWI) analyses of both networks in dystonia have revealed differences in non-specific Diffusion-Tensor metrics such as Fractional Anisotropy. However newer DWI models, such as Neurite Orientation Dispersion and Density Imaging (NODDI), assess more specific and biologically relevant white-matter properties. <h3>Design/Methods:</h3> Using the UK Biobank, 23 subjects with isolated dystonia and diffusion-MRI data were identified, along with 69 control subjects without neurologic (ICD10 G-coded) diagnoses, matched (1:3) on age, sex, imaging site, and medical comorbidities relevant to white-matter integrity (hypertension, hyperlipidemia, and diabetes). Two DTI metrics (mean diffusivity and fractional anisotropy) and three NODDI metrics (intracellular volume fraction, isotropic volume fraction, and orientation dispersion) were extracted from each of four tracts (inferior, middle, and superior cerebellar peduncles, and superior thalamic radiations). Volumetric data consisted of cerebellar (15 regions), basal ganglia (3 regions), and whole-brain grey and white-matter volumes. <h3>Results:</h3> After correcting for multiple-comparisons (40 volumetric and 35 diffusion-related) using the Benjamini-Hochberg procedure (FDR = 0.05), intracellular-volume-fraction (ICVF) of the middle- and superior-cerebellar peduncles was significantly lower in subjects with dystonia, suggesting reduced axon density; volumetric analysis showed significantly reduced volumes of the motor cerebellum (lobules VI and VIII). There were no differences in basal ganglia, cortical, or whole-brain volumes. <h3>Conclusions:</h3> These findings support the hypothesis that abnormalities of cerebellar networks contribute to the pathogenesis of dystonia. <b>Disclosure:</b> Dr. Mason has nothing to disclose. Miss Haddad has nothing to disclose. The institution of Neda Jahanshad has received research support from Biogen Inc.

Atypical developmental trajectories of white matter microstructure in prenatal alcohol exposure: Preliminary evidence from neurite orientation dispersion and density imaging.

Fetal alcohol spectrum disorder (FASD), a life-long condition resulting from prenatal alcohol exposure (PAE), is associated with structural brain anomalies and neurobehavioral differences. Evidence from longitudinal neuroimaging suggest trajectories of white matter microstructure maturation are atypical in PAE. We aimed to further characterize longitudinal trajectories of developmental white matter microstructure change in children and adolescents with PAE compared to typically-developing Controls using diffusion-weighted Neurite Orientation Dispersion and Density Imaging (NODDI). Participants: Youth with PAE (n = 34) and typically-developing Controls (n = 31) ages 8-17 years at enrollment. Participants underwent formal evaluation of growth and facial dysmorphology. Participants also completed two study visits (17 months apart on average), both of which involved cognitive testing and an MRI scan (data collected on a Siemens Prisma 3 T scanner). Age-related changes in the orientation dispersion index (ODI) and the neurite density index (NDI) were examined across five corpus callosum (CC) regions defined by tractography. While linear trajectories suggested similar overall microstructural integrity in PAE and Controls, analyses of symmetrized percent change (SPC) indicated group differences in the timing and magnitude of age-related increases in ODI (indexing the bending and fanning of axons) in the central region of the CC, with PAE participants demonstrating atypically steep increases in dispersion with age compared to Controls. Participants with PAE also demonstrated greater increases in ODI in the mid posterior CC (trend-level group difference). In addition, SPC in ODI and NDI was differentially correlated with executive function performance for PAE participants and Controls, suggesting an atypical relationship between white matter microstructure maturation and cognitive function in PAE. Preliminary findings suggest subtle atypicality in the timing and magnitude of age-related white matter microstructure maturation in PAE compared to typically-developing Controls. These findings add to the existing literature on neurodevelopmental trajectories in PAE and suggest that advanced biophysical diffusion modeling (NODDI) may be sensitive to biologically-meaningful microstructural changes in the CC that are disrupted by PAE. Findings of atypical brain maturation-behavior relationships in PAE highlight the need for further study. Further longitudinal research aimed at characterizing white matter neurodevelopmental trajectories in PAE will be important.