Diffusion tensor and restriction spectrum imaging reflect different aspects of neurodegeneration in Parkinson's disease

Environmental enrichment reduces restricted repetitive behavior by altering gray matter microstructure

Restricted, repetitive behaviors are common symptoms in neurodevelopmental disorders including autism spectrum disorder. Despite being associated with poor developmental outcomes, repetitive behaviors remain poorly understood and have limited treatment options. Environmental enrichment attenuates the development of repetitive behaviors, but the exact mechanisms remain obscure. Using the C58 mouse model of repetitive behavior, we performed diffusion tensor imaging to examine microstructural alterations associated with the development of repetitive behavior and its attenuation by environmental enrichment. The C57BL/6 mouse strain, which displays little or no repetitive behavior, was used as a control group. We observed widespread differences in diffusion metrics between C58 mice and C57BL/6 mice. In juvenile C58 mice, repetitive motor behavior displayed strong negative correlations with fractional anisotropy in multiple gray matter regions, whereas in young adult C58 mice, high repetitive motor behavior was most strongly associated with lower fractional anisotropy and higher radial diffusivity in the striatum. Environmental enrichment increased fractional anisotropy and axial diffusivity throughout gray matter regions in the brains of juvenile C58 mice and overlapped predominantly with cerebellar and sensory regions associated with repetitive behavior. Our results suggest environmental enrichment reduces repetitive behavior development by altering gray matter microstructure in the cerebellum, medial entorhinal cortex, and sensory processing regions in juvenile C58 mice. Under standard laboratory conditions, early pathology in these regions appears to contribute to later striatal and white matter dysfunction in adult C58 mice. Future studies should examine the role these regions play in the development of repetitive behavior and the relationship between sensory processing and cerebellar deficits and repetitive behavior.

Diagnostic Utility of Restriction Spectrum Imaging in Head and Neck Tumors: A Pilot Study

OBJECTIVE

Imaging is crucial in the assessment of head and neck cancers for site, extension, and enlarged lymph nodes. Restriction spectrum imaging (RSI) is a new diffusion-weighted magnetic resonance imaging (MRI) technique that enhances the ability to differentiate aggressive cancer from low-grade or benign tumors and helps guide treatment and biopsy. Its contribution to imaging of brain and prostate tumors has been previously published. However, there are no prior studies using RSI sequence in head and neck tumors. The purpose of this study was to evaluate the feasibility of performing RSI in head and neck cancer.

METHODS

An additional RSI sequence was added in the routine MRI neck protocol for 13 patients diagnosed with head and neck cancer between November 2018 and April 2019. Restriction spectrum imaging sequence was performed with b values of 0, 500, 1500, and 3000 s/mm 2 and 29 directions on 1.5T magnetic resonance scanners.Diffusion-weighted imaging (DWI) images and RSI images were compared according to their ability to detect the primary malignancy and possible metastatic lymph nodes.

RESULTS

In 71% of the patients, RSI outperformed DWI in detecting the primary malignancy and possible metastatic lymph nodes, whereas in the remaining cases, the 2 were comparable. In 66% of the patients, RSI detected malignant lymph nodes that DWI/apparent diffusion coefficient failed to detect.

CONCLUSIONS

This is the first study of RSI in head and neck imaging and showed its superiority over the conventional DWI sequence. Because of its ability to differentiate benign and malignant lymph nodes in some cases, the addition of RSI to routine head and neck MRI should be considered.

Associations between N-Acetylaspartate and white matter integrity in individuals with schizophrenia and unaffected relatives

Compromised white matter has been reported in schizophrenia; however, few studies have investigated neurochemical abnormalities underlying microstructural differences. N-acetylaspartate (NAA) is used to synthesize myelin and is often reduced in persons with schizophrenia (PSZ) and their unaffected first-degree relatives (REL). Low levels of NAA could affect white matter by preventing the synthesis or repair of myelin. We used magnetic resonance spectroscopy and diffusion tensor imaging to investigate the relationship between NAA and white matter integrity in PSZ. REL were included to examine whether putative relationships are associated with symptom expression or illness liability. 52 controls, 23 REL and 25 PSZ underwent 7T proton magnetic resonance spectroscopy and/or 3T diffusion tensor imaging. NAA in the visual cortex and basal ganglia were measured and compared across groups. Diffusivity measures were compared across groups using tract-based spatial statistics and related to NAA concentrations. Visual cortex NAA was significantly reduced in PSZ compared to controls. White matter integrity did not differ between groups. Reduced cortical and subcortical NAA were associated with diffusivity measures of poor white matter microstructure. These data suggest that levels of neural NAA may be related to white matter integrity similarly across individuals with schizophrenia, those at genetic risk, and controls.

Ambient fine particulate exposure and subcortical gray matter microarchitecture in 9- and 10-year-old children across the United States

Neuroimaging studies showing the adverse effects of air pollution on neurodevelopment have largely focused on smaller samples from limited geographical locations and have implemented univariant approaches to assess exposure and brain macrostructure. Herein, we implement restriction spectrum imaging and a multivariate approach to examine how one year of annual exposure to daily fine particulate matter (PM_2.5), daily nitrogen dioxide (NO₂), and 8-h maximum ozone (O₃) at ages 9-10 years relates to subcortical gray matter microarchitecture in a geographically diverse subsample of children from the Adolescent Brain Cognitive Development (ABCD) Study^℠. Adjusting for confounders, we identified a latent variable representing 66% of the variance between one year of air pollution and subcortical gray matter microarchitecture. PM_2.5 was related to greater isotropic intracellular diffusion in the thalamus, brainstem, and accumbens, which related to cognition and internalizing symptoms. These findings may be indicative of previously identified air pollution-related risk for neuroinflammation and early neurodegenerative pathologies.

Language impairment in Parkinson’s disease: fMRI study of sentence reading comprehension

Parkinson’s disease (PD) affects the language processes, with a significant impact on the patients’ daily communication. We aimed to describe specific alterations in the comprehension of syntactically complex sentences in patients with PD (PwPD) as compared to healthy controls (HC) and to identify the neural underpinnings of these deficits using a functional connectivity analysis of the striatum. A total of 20 patients PwPD and 15 HC participated in the fMRI study. We analyzed their performance of a Test of sentence comprehension (ToSC) adjusted for fMRI. A task-dependent functional connectivity analysis of the striatum was conducted using the psychophysiological interaction method (PPI). On the behavioral level, the PwPD scored significantly lower (mean ± sd: 77.3 ± 12.6) in the total ToSC score than the HC did (mean ± sd: 86.6 ± 8.0), p = 0.02, and the difference was also significant specifically for sentences with a non-canonical word order (PD-mean ± sd: 69.9 ± 14.1, HC-mean ± sd: 80.2 ± 11.5, p = 0.04). Using PPI, we found a statistically significant difference between the PwPD and the HC in connectivity from the right striatum to the supplementary motor area [SMA, (4 8 53)] for non-canonical sentences. This PPI connectivity was negatively correlated with the ToSC accuracy of non-canonical sentences in the PwPD. Our results showed disturbed sentence reading comprehension in the PwPD with altered task-dependent functional connectivity from the right striatum to the SMA, which supports the synchronization of the temporal and sequential aspects of language processing. The study revealed that subcortical-cortical networks (striatal-frontal loop) in PwPD are compromised, leading to impaired comprehension of syntactically complex sentences.

Multivariate genome-wide association study on tissue-sensitive diffusion metrics highlights pathways that shape the human brain

The molecular determinants of tissue composition of the human brain remain largely unknown. Recent genome-wide association studies (GWAS) on this topic have had limited success due to methodological constraints. Here, we apply advanced whole-brain analyses on multi-shell diffusion imaging data and multivariate GWAS to two large scale imaging genetic datasets (UK Biobank and the Adolescent Brain Cognitive Development study) to identify and validate genetic association signals. We discover 503 unique genetic loci that have impact on multiple regions of human brain. Among them, more than 79% are validated in either of two large-scale independent imaging datasets. Key molecular pathways involved in axonal growth, astrocyte-mediated neuroinflammation, and synaptogenesis during development are found to significantly impact the measured variations in tissue-specific imaging features. Our results shed new light on the biological determinants of brain tissue composition and their potential overlap with the genetic basis of neuropsychiatric disorders.

Association of Outdoor Ambient Fine Particulate Matter With Intracellular White Matter Microstructural Properties Among Children

Importance

Outdoor particulate matter 2.5 μm or less in diameter (PM2.5) is a ubiquitous environmental neurotoxicant that may affect the developing brain. Little is known about associations between PM2.5 and white matter connectivity.

Objectives

To assess associations between annual residential PM2.5 exposure and white matter microstructure health in a US sample of children 9 to 10 years of age and to examine whether associations are specific to certain white matter pathways or vary across neuroimaging diffusion markers reflective of intracellular and extracellular microstructural processes.

Design, Setting, and Participants

This cross-sectional study, the Adolescent Brain and Cognitive Development (ABCD) Study, was composed of 21 study sites across the US and used baseline data collected from children 9 to 10 years of age from September 1, 2016, to October 15, 2018. Data analysis was performed from September 15, 2020, to June 30, 2021.

Exposures

Annual mean PM2.5 exposure estimated by ensemble-based models and assigned to the primary residential addresses at baseline.

Main Outcomes and Measures

Diffusion-weighted imaging (DWI) and tractography were used to delineate white matter tracts. The biophysical modeling technique of restriction spectrum imaging (RSI) was implemented to examine total hindered diffusion and restricted isotropic and anisotropic intracellular diffusion in each tract. Hierarchical mixed-effects models with natural splines were used to analyze the associations between PM2.5 exposure and DWI.

Results

In a study population of 7602 children (mean [SD] age, 119.1 [7.42] months; 3955 [52.0%] female; 160 [ 21.%] Asian, 1025 [13.5%] Black, 1616 [21.3%] Hispanic, 4025 [52.9%] White, and 774 [10.2%] other [identified by parents as American Indian/Native American or Alaska Native; Native Hawaiian, Guamanian, Samoan, other Pacific Islander; Asian Indian, Chinese, Filipino, Japanese, Korean, Vietnamese, or other Asian; or other race]), associations were seen between annual ambient PM2.5 and hemispheric differences in white matter microstructure. Hemisphere-stratified models revealed significant associations between PM2.5 exposure and restricted isotropic intracellular diffusion in the left cingulum, in the left superior longitudinal fasciculus, and bilaterally in the fornix and uncinate fasciculus. In tracts with strong positive associations, a PM2.5 increase from 8 to 12 μg/m3 was associated with increases of 2.16% (95% CI, 0.49%-3.84%) in the left cingulum, 1.95% (95% CI, 0.43%-3.47%) in the left uncinate, and 1.68% (95% CI, 0.01%-3.34%) in the right uncinate. Widespread negative associations were observed between PM2.5 and mean diffusivity.

Conclusions and Relevance

The findings of this cross-sectional study suggest that annual mean PM2.5 exposure during childhood is associated with increased restricted isotropic diffusion and decreased mean diffusivity of specific white matter tracts, potentially reflecting differences in the composition of white matter microarchitecture.

Diffusion tensor imaging-based pontine damage as a degeneration marker in synucleinopathy

The pons is one of the earliest affected regions in patients with synucleinopathies. We aimed to investigate the diagnostic value of measuring pontine damage using diffusion tensor imaging (DTI) in these patients. We enrolled 49 patients with Parkinson's disease (PD), 16 patients with idiopathic rapid eye movement sleep behavior disorder (iRBD), 23 patients with multiple system atrophy (MSA), and 39 healthy controls in this study. All the participants underwent high-resolution T1-weighted imaging and DTI. Mean diffusivity (MD) and fraction anisotropy (FA) values in the pons were calculated to characterize structural damage. The discriminatory power of pontine MD and FA values to differentiate patients with synucleinopathies from healthy controls was examined using receiver operating characteristics (ROC) analyses. Compared to healthy controls, patients with PD, iRBD, and MSA had increased MD values and decreased FA values in the pons, although no correlation was observed between these DTI measures and disease severity. The ROC analyses showed that MD values in the pons had a fair discriminatory power to differentiate healthy controls from patients with PD (area under the curve [AUC], 0.813), iRBD (AUC, 0.779), and MSA (AUC, 0.951). The AUC for pontine FA values was smaller than that for pontine MD values when differentiating healthy controls from patients with PD (AUC, 0.713; p = 0.054) and iRBD (AUC, 0.686; p = 0.045). Our results suggest that MD values in the pons may be a useful marker of brain stem neurodegeneration in patients with synucleinopathies.

Role of Diffusion Tensor Imaging in Parkinson's Disease Diagnosis

Background: Parkinson's disease (PD) is a chronic and progressive neurodegenerative disease that affects the dopamine-containing neurons. In this study, the role of the Diffusion Tensor imaging (DTI) method was investigated in the detection of PD. Objectives: The purpose of this study was to investigate the microstructural damage of the brain's white matter in PD using a non-invasive DTI technique. Methods: Twenty patients with PD were studied with comprehensive clinical assessments and DTI data. Also, 10 normal subjects were investigated. Fractional anisotropic (FA) and mean diffusivity (MD) values were calculated by drawing region of interest (ROI) on eight distinctive areas of the brain. Results: The level of FA and MD in substantia nigra (SN) was significantly different between the PD and healthy control (HC) groups. Also, differences were found in DTI parameters between PD and HC groups in some regions, such as genu, anterior limb of internal capsule (ALIC), splenium, and putamen. Conclusions: To summarize, DTI as a non-invasive method can be useful in the detection of Parkinson's disease.

Parkinson Disease Propagation Using MRI Biomarkers and Partial Least Squares Path Modeling

OBJECTIVES

The classic Braak neuropathologic staging model in Parkinson disease (PD) suggests that brain lesions progress from the medulla oblongata to the cortex. An alternative model in which neurodegeneration first occurs in the cortex has also been proposed. These 2 models may correspond to different patient phenotypes. To test these 2 models and to investigate whether they were influenced by the presence of REM sleep behavior disorder (RBD), we used multimodal MRI and partial least squares path modeling (PLS-PM) assuming that patients with RBD followed distinct neurodegeneration pattern.

METHODS

Fifty-four patients with PD (34 with RBD) and 25 healthy volunteers were scanned with T1-weighted, diffusion tensor, and neuromelanin-sensitive imaging. Volume, signal, and mean, axial, and radial diffusivities were calculated in brainstem, basal forebrain, and cortical regions. PLS-PM, estimating a network of causal relationships between blocks of variables, was used to build and test an analytical model based on Braak staging. The overall quality of the model was assessed with goodness of fit coefficient (Gof).

RESULTS

PLS-PM was run on patients with PD with RBD and without RBD separately. In PD with RBD, a brainstem-to-cortex model had significant Gof (0.71, p = 0.01), whereas a cortex-to-brainstem model did not. In contrast, in patients with PD without RBD, the brainstem-to-cortex model was not significant (Gof = 0.64, p = 0.27), and the cortex-to-brainstem model was highly significant (Gof = 0.72, p = 0.008).

CONCLUSIONS

With the PLS-PM imaging-based model, the neurodegeneration pattern of patients with PD with RBD was consistent with the Braak brainstem-to-cortex model, whereas that of patients without RBD followed the cortex-to-brainstem model.

White matter microstructure across the adult lifespan: A mixed longitudinal and cross-sectional study using advanced diffusion models and brain-age prediction

The macro- and microstructural architecture of human brain white matter undergoes substantial alterations throughout development and ageing. Most of our understanding of the spatial and temporal characteristics of these lifespan adaptations come from magnetic resonance imaging (MRI), including diffusion MRI (dMRI), which enables visualisation and quantification of brain white matter with unprecedented sensitivity and detail. However, with some notable exceptions, previous studies have relied on cross-sectional designs, limited age ranges, and diffusion tensor imaging (DTI) based on conventional single-shell dMRI. In this mixed cross-sectional and longitudinal study (mean interval: 15.2 months) including 702 multi-shell dMRI datasets, we combined complementary dMRI models to investigate age trajectories in healthy individuals aged 18 to 94 years (57.12% women). Using linear mixed effect models and machine learning based brain age prediction, we assessed the age-dependence of diffusion metrics, and compared the age prediction accuracy of six different diffusion models, including diffusion tensor (DTI) and kurtosis imaging (DKI), neurite orientation dispersion and density imaging (NODDI), restriction spectrum imaging (RSI), spherical mean technique multi-compartment (SMT-mc), and white matter tract integrity (WMTI). The results showed that the age slopes for conventional DTI metrics (fractional anisotropy [FA], mean diffusivity [MD], axial diffusivity [AD], radial diffusivity [RD]) were largely consistent with previous research, and that the highest performing advanced dMRI models showed comparable age prediction accuracy to conventional DTI. Linear mixed effects models and Wilk's theorem analysis showed that the 'FA fine' metric of the RSI model and 'orientation dispersion' (OD) metric of the NODDI model showed the highest sensitivity to age. The results indicate that advanced diffusion models (DKI, NODDI, RSI, SMT mc, WMTI) provide sensitive measures of age-related microstructural changes of white matter in the brain that complement and extend the contribution of conventional DTI.

Modern Brainstem MRI Techniques for the Diagnosis of Parkinson's Disease and Parkinsonisms

The brainstem is the earliest vulnerable structure in many neurodegenerative diseases like in Multiple System Atrophy (MSA) or Parkinson's disease (PD). Up-to-now, MRI studies have mainly focused on whole-brain data acquisition. Due to its spatial localization, size, and tissue characteristics, brainstem poses particular challenges for MRI. We provide a brief overview on recent advances in brainstem-related MRI markers in Parkinson's disease and Parkinsonism's. Several MRI techniques investigating brainstem, mainly the midbrain, showed to be able to discriminate PD patients from controls or to discriminate PD patients from atypical parkinsonism patients: iron-sensitive MRI, nigrosome imaging, neuromelanin-sensitive MRI, diffusion tensor imaging and advanced diffusion imaging. A standardized multimodal brainstem-dedicated MRI approach at high resolution able to quantify microstructural modification in brainstem nuclei would be a promising tool to detect early changes in parkinsonian syndromes.

Neural and dopaminergic correlates of fatigue in Parkinson's disease

Fatigue is one of the most common non-motor symptoms in Parkinson's disease (PD). Despite its clinical importance, there are few studies on the cause or mechanism of fatigue. Our aim was to find brain areas related to fatigue and to explore the association between striatal dopaminergic dysfunction and fatigue. We consecutively screened forty-seven patients with de novo PD from 2012 to 2017 and enrolled 32 patients. The gray matter volumes, white matter tracts, and striatal dopaminergic activity between PD without fatigue and with fatigue were compared. The correlation between fatigue and striatal dopaminergic activity was also analyzed. Our data did not show any significant difference in gray matter volume between PD without fatigue and with fatigue (familywise error [FWE] corrected p > 0.05) but revealed significantly higher mean fractional anisotropy (FA) values for all analyzed white matter tracts in PD with fatigue (false discovery rate [FDR] corrected p < 0.05), except left cingulum-hippocampus (CH), right superior longitudinal fasciculus, and right longitudinal fasciculus temporal part (FDR corrected p > 0.06); lower mean diffusivity (MD) values for all analyzed white matter tracts in PD with fatigue (FDR corrected p < 0.05), except in the left CH and uncinate fasciculus (FDR corrected p > 0.05). The mean radial diffusivity (RD) values, except for the left CH (FDR corrected p = 0.0576), were also significantly lower (FDR corrected p < 0.05). There was no difference in dopaminergic deficits between PD without fatigue and PD with fatigue (p > 0.50). The alteration of the white matter tract may reflect the degree of fatigue in PD. This is not true of the gray matter and striatal dopaminergic activity. These results show the possibility that white matter changes can be used as a biomarker for fatigue.