A full-brain, bootstrapped analysis of diffusion tensor imaging robustly differentiates Parkinson disease from healthy controls

White Matter Microstructural Alterations in Newly Diagnosed Parkinson’s Disease: A Whole-Brain Analysis Using dMRI

Parkinson’s disease (PD) is a neurodegenerative disorder characterized by cardinal motor symptoms and other non-motor symptoms. Studies have investigated various brain areas in PD by detecting white matter alterations using diffusion magnetic resonance imaging processing techniques, which can produce diffusion metrics such as fractional anisotropy and quantitative anisotropy. In this study, we compared the quantitative anisotropy of whole brain regions throughout the subcortical and cortical areas between newly diagnosed PD patients and healthy controls. Additionally, we evaluated the correlations between the quantitative anisotropy of each region and respective neuropsychological test scores to identify the areas most affected by each neuropsychological dysfunction in PD. We found significant quantitative anisotropy differences in several subcortical structures such as the basal ganglia, limbic system, and brain stem as well as in cortical structures such as the temporal lobe, occipital lobe, and insular lobe. Additionally, we found that quantitative anisotropy of some subcortical structures such as the basal ganglia, cerebellum, and brain stem showed the highest correlations with motor dysfunction, whereas cortical structures such as the temporal lobe and occipital lobe showed the highest correlations with olfactory dysfunction in PD. Our study also showed evidence regarding potential neural compensation by revealing higher diffusion metric values in early-stage PD than in healthy controls. We anticipate that our results will improve our understanding of PD’s pathophysiology.

Diffusion Measure Changes of Substantia Nigra Subregions and the Ventral Tegmental Area in Newly Diagnosed Parkinson's Disease

Historically, studies have extensively examined the basal ganglia in Parkinson’s disease for specific characteristics that can be observed with medical imaging. One particular methodology used for detecting changes that occur in Parkinson’s disease brains is diffusion tensor imaging, which yields diffusion indices such as fractional anisotropy and radial diffusivity that have been shown to correlate with axonal damage. In this study, we compare the diffusion measures of basal ganglia structures (with substantia nigra divided into subregions, pars compacta, and pars reticula), as well as the diffusion measures of the diffusion tracts that pass through each pair of basal ganglia structures to see if significant differences in diffusion measures can be observed in structures or tracts in newly diagnosed Parkinson’s disease patients. Additionally, we include the ventral tegmental area, a structure connected to various basal ganglia structures affected by dopaminergic neuronal loss and have historically shown significant alterations in Parkinson’s disease, in our analysis. We found significant fractional anisotropy differences in the putamen, and in the diffusion tracts that pass through pairs of both substantia nigra subregions, subthalamic nucleus, parabrachial pigmental nucleus, ventral tegmental area. Additionally, we found significant radial diffusivity differences in diffusion tracts that pass through the parabrachial nucleus, putamen, both substantia nigra subregions, and globus pallidus externa. We were able to find significant diffusion measure differences in structures and diffusion tracts, potentially due to compensatory mechanisms in response to dopaminergic neuronal loss that occurs in newly diagnosed Parkinson’s disease patients.

Diffusion Tensor Imaging in Parkinson's Disease and Parkinsonian Syndrome: A Systematic Review

Diffusion tensor imaging (DTI) allows measuring fractional anisotropy and similar microstructural indices of the brain white matter. Lower than normal fractional anisotropy as well as higher than normal diffusivity is associated with loss of microstructural integrity and neurodegeneration. Previous DTI studies in Parkinson's disease (PD) have demonstrated abnormal fractional anisotropy in multiple white matter regions, particularly in the dopaminergic nuclei and dopaminergic pathways. However, DTI is not considered a diagnostic marker for the earliest Parkinson's disease since anisotropic alterations present a temporally divergent pattern during the earliest Parkinson's course. This article reviews a majority of clinically employed DTI studies in PD, and it aims to prove the utilities of DTI as a marker of diagnosing PD, correlating clinical symptomatology, tracking disease progression, and treatment effects. To address the challenge of DTI being a diagnostic marker for early PD, this article also provides a comparison of the results from a longitudinal, early stage, multicenter clinical cohort of Parkinson's research with previous publications. This review provides evidences of DTI as a promising marker for monitoring PD progression and classifying atypical PD types, and it also interprets the possible pathophysiologic processes under the complex pattern of fractional anisotropic changes in the first few years of PD. Recent technical advantages, limitations, and further research strategies of clinical DTI in PD are additionally discussed.

Interventions of natural and synthetic agents in inflammatory bowel disease, modulation of nitric oxide pathways

Inflammatory bowel disease (IBD) refers to a group of disorders characterized by chronic inflammation of the gastrointestinal (GI) tract. The elevated levels of nitric oxide (NO) in serum and affected tissues; mainly synthesized by the inducible nitric oxide synthase (iNOS) enzyme; can exacerbate GI inflammation and is one of the major biomarkers of GI inflammation. Various natural and synthetic agents are able to ameliorate GI inflammation and decrease iNOS expression to the extent comparable with some IBD drugs. Thereby, the purpose of this study was to gather a list of natural or synthetic mediators capable of modulating IBD through the NO pathway. Electronic databases including Google Scholar and PubMed were searched from 1980 to May 2018. We found that polyphenols and particularly flavonoids are able to markedly attenuate NO production and iNOS expression through the nuclear factor κB (NF-κB) and JAK/STAT signaling pathways. Prebiotics and probiotics can also alter the GI microbiota and reduce NO expression in IBD models through a broad array of mechanisms. A number of synthetic molecules have been found to suppress NO expression either dependent on the NF-κB signaling pathway (i.e., dexamethasone, pioglitazone, tropisetron) or independent from this pathway (i.e., nicotine, prednisolone, celecoxib, β-adrenoceptor antagonists). Co-administration of natural and synthetic agents can affect the tissue level of NO and may improve IBD symptoms mainly by modulating the Toll like receptor-4 and NF-κB signaling pathways.

Structural neuroimaging as clinical predictor: A review of machine learning applications

In this paper, we provide an extensive overview of machine learning techniques applied to structural magnetic resonance imaging (MRI) data to obtain clinical classifiers. We specifically address practical problems commonly encountered in the literature, with the aim of helping researchers improve the application of these techniques in future works. Additionally, we survey how these algorithms are applied to a wide range of diseases and disorders (e.g. Alzheimer's disease (AD), Parkinson's disease (PD), autism, multiple sclerosis, traumatic brain injury, etc.) in order to provide a comprehensive view of the state of the art in different fields.

Diffusion tensor imaging in Parkinson's disease: Review and meta-analysis

BACKGROUND

Neuroimaging studies help us better understand the pathophysiology and symptoms of Parkinson's disease (PD). In several of these studies, diffusion tensor imaging (DTI) was used to investigate structural changes in cerebral tissue. Although data have been provided as regards to specific brain areas, a whole brain meta-analysis is still missing.

METHODS

We compiled 39 studies in this meta-analysis: 14 used fractional anisotropy (FA), 1 used mean diffusivity (MD), and 24 used both indicators. These studies comprised 1855 individuals, 1087 with PD and 768 healthy controls. Regions of interest were classified anatomically (subcortical structures; white matter; cortical areas; cerebellum). Our statistical analysis considered the disease effect size (DES) as the main variable; the heterogeneity index (I2) and Pearson's correlations between the DES and co-variables (demographic, clinical and MRI parameters) were also calculated.

RESULTS

Our results showed that FA-DES and MD-DES were able to distinguish between patients and healthy controls. Significant differences, indicating degenerations, were observed within the substantia nigra, the corpus callosum, and the cingulate and temporal cortices. Moreover, some findings (particularly in the corticospinal tract) suggested opposite brain changes associated with PD. In addition, our results demonstrated that MD-DES was particularly sensitive to clinical and MRI parameters, such as the number of DTI directions and the echo time within white matter.

CONCLUSIONS

Despite some limitations, DTI appears as a sensitive method to study PD pathophysiology and severity. The association of DTI with other MRI methods should also be considered and could benefit the study of brain degenerations in PD.

A novel method for evaluating brain function and microstructural changes in Parkinson's disease

In this study, microstructural brain damage in Parkinson's disease patients was examined using diffusion tensor imaging and tract-based spatial statistics. The analyses revealed the presence of neuronal damage in the substantia nigra and putamen in the Parkinson's disease patients. Moreover, disease symptoms worsened with increasing damage to the substantia nigra, confirming that the substantia nigra and basal ganglia are the main structures affected in Parkinson's disease. We also found that microstructural damage to the putamen, caudate nucleus and frontal lobe positively correlated with depression. Based on the tract-based spatial statistics, various white matter tracts appeared to have microstructural damage, and this correlated with cognitive disorder and depression. Taken together, our results suggest that diffusion tensor imaging and tract-based spatial statistics can be used to effectively study brain function and microstructural changes in patients with Parkinson's disease. Our novel findings should contribute to our understanding of the histopathological basis of cognitive dysfunction and depression in Parkinson's disease.

Diffusion MRI and its Role in Neuropsychology

Diffusion Magnetic Resonance Imaging (dMRI) is a popular method used by neuroscientists to uncover unique information about the structural connections within the brain. dMRI is a non-invasive imaging methodology in which image contrast is based on the diffusion of water molecules in tissue. While applicable to many tissues in the body, this review focuses exclusively on the use of dMRI to examine white matter in the brain. In this review, we begin with a definition of diffusion and how diffusion is measured with MRI. Next we introduce the diffusion tensor model, the predominant model used in dMRI. We then describe acquisition issues related to acquisition parameters and scanner hardware and software. Sources of artifacts are then discussed, followed by a brief review of analysis approaches. We provide an overview of the limitations of the traditional diffusion tensor model, and highlight several more sophisticated non-tensor models that better describe the complex architecture of the brain's white matter. We then touch on reliability and validity issues of diffusion measurements. Finally, we describe examples of ways in which dMRI has been applied to studies of brain disorders and how identified alterations relate to symptomatology and cognition.