Disruption of Inferior Longitudinal Fasciculus Microstructure in Parkinson's Disease: A Systematic Review of Diffusion Tensor Imaging Studies

Structural and Functional Imaging Correlates of Visual Hallucinations in Parkinson's Disease

PURPOSE OF REVIEW

To review recent structural and functional MRI studies of visual hallucinations in Parkinson's disease.

RECENT FINDINGS

Previously, neuroimaging had shown inconsistent findings in patients with Parkinson's hallucinations, especially in studies examining grey matter volume. However, recent advances in structural and functional MRI techniques allow better estimates of structural connections, as well as the direction of connectivity in functional MRI. These provide more sensitive measures of changes in structural connectivity and allow models of the changes in directional functional connectivity to be tested. We identified 27 relevant studies and found that grey matter imaging continues to show heterogeneous findings in Parkinson's patients with visual hallucinations. Newer approaches in diffusion imaging and functional MRI are consistent with emerging models of Parkinson's hallucinations, suggesting shifts in attentional networks. In particular, reduced bottom-up, incoming sensory information, and over-weighting of top-down signals appear to be important drivers of visual hallucinations in Parkinson's disease.

The interplay between structural and functional connectivity in early stage Parkinson's disease patients

The mechanisms underlying cognitive disturbances in Parkinson's disease (PD) are poorly understood but likely to depend on the ongoing degenerative processes affecting structural and functional connectivity (FC). This pilot study examined patterns of FC alterations during a cognitive task using EEG and structural characteristics of white matter (WM) pathways connecting these activated regions in early-stage PD. Eleven PD patients and nine healthy controls (HCs) underwent EEG recording during an auditory oddball task and MRI scans. Source localization was performed and Gaussian mixture model was fitted to identify brain regions with high power during task performance. These areas served as seed regions for connectivity analysis. FC among these regions was assessed by measures of magnitude squared coherence (MSC), and phase-locking value (PLV), while structural connectivity was evaluated using fiber tracking based on diffusion tensor imaging (DTI). The paracentral lobule (PL), superior parietal lobule (SPL), superior and middle frontal gyrus (SMFG), parahippocampal gyrus, superior and middle temporal gyri (STG, MTG) demonstrated increased activation during task performance. Compared to HCs, PD showed lower FC between SMFG and PL and between SMFG and SPL in MSC (p = 0.012 and p = 0.036 respectively). No significant differences between the groups were observed in PLV and the measured DTI metrics along WM tracts. These findings demonstrate that in early PD, cognitive performance changes might be attributed to FC alterations, suggesting that FC is affected early on in the degenerative process, whereas structural damage is more prominent in advanced stages as a result of the disease burden accumulation.

Cerebellar Microstructural Abnormalities in Parkinson's Disease: a Systematic Review of Diffusion Tensor Imaging Studies

Diffusion tensor imaging (DTI) is now having a strong momentum in research to evaluate the neural fibers of the CNS. This technique can study white matter (WM) microstructure in neurodegenerative disorders, including Parkinson's disease (PD). Previous neuroimaging studies have suggested cerebellar involvement in the pathogenesis of PD, and these cerebellum alterations can correlate with PD symptoms and stages. Using the PRISMA 2020 framework, PubMed and EMBASE were searched to retrieve relevant articles. Our search revealed 472 articles. After screening titles and abstracts, and full-text review, and implementing the inclusion criteria, 68 papers were selected for synthesis. Reviewing the selected studies revealed that the patterns of reduction in cerebellum WM integrity, assessed by fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity measures can differ symptoms and stages of PD. Cerebellar diffusion tensor imaging (DTI) changes in PD patients with "postural instability and gait difficulty" are significantly different from "tremor dominant" PD patients. Freezing of the gate is strongly related to cerebellar involvement depicted by DTI. The "reduced cognition," "visual disturbances," "sleep disorders," "depression," and "olfactory dysfunction" are not related to cerebellum microstructural changes on DTI, while "impulsive-compulsive behavior" can be linked to cerebellar WM alteration. Finally, higher PD stages and longer disease duration are associated with cerebellum white matter alteration depicted by DTI. Depiction of cerebellar white matter involvement in PD is feasible by DTI. There is an association with disease duration and severity and several clinical presentations with DTI findings. This clinical-imaging association may eventually improve disease management.

Simulating the progression of brain structural alterations in Parkinson's disease

Considering brain structural alterations as neurodegenerative consequences of Parkinson's disease (PD), we sought to infer the progression of PD via the ordering of brain structural alterations from cross-sectional MRI observations. Having measured cortical thinning in gray matter (GM) regions and disintegrity in white matter (WM) regions as MRI markers of structural alterations for 130 patients with PD (69 ± 10 years, 72 men), stochastic simulation based on the probabilistic relationship between the brain regions was conducted to infer the ordering of structural alterations across all brain regions and the staging of structural alterations according to changes in clinical status. The ordering of structural alterations represented WM disintegrity tending to occur earlier than cortical thinning. The staging of structural alterations indicated structural alterations happening mostly before major disease complications such as postural instability and dementia. Later disease states predicted by the sequence of structural alterations were significantly related to more severe clinical symptoms. The relevance of the ordering of brain structural alterations to the severity of clinical symptoms suggests the clinical feasibility of predicting PD progression states.

Identifying Depression in Parkinson's Disease by Using Combined Diffusion Tensor Imaging and Support Vector Machine

Objective

To investigate white matter microstructural alterations in Parkinson's disease (PD) patients with depression using the whole-brain diffusion tensor imaging (DTI) method and to explore the DTI–based machine learning model in identifying depressed PD (dPD).

Methods

The DTI data were collected from 37 patients with dPD and 35 patients with non-depressed PD (ndPD), and 25 healthy control (HC) subjects were collected as the reference. An atlas-based analysis method was used to compare fractional anisotropy (FA) and mean diffusivity (MD) among the three groups. A support vector machine (SVM) was trained to examine the probability of discriminating between dPD and ndPD.

Results

As compared with ndPD, dPD group exhibited significantly decreased FA in the bilateral corticospinal tract, right cingulum (cingulate gyrus), left cingulum hippocampus, bilateral inferior longitudinal fasciculus, and bilateral superior longitudinal fasciculus, and increased MD in the right cingulum (cingulate gyrus) and left superior longitudinal fasciculus-temporal part. For discriminating between dPD and ndPD, the SVM model with DTI features exhibited an accuracy of 0.70 in the training set [area under the receiver operating characteristic curve (ROC) was 0.78] and an accuracy of 0.73 in the test set (area under the ROC was 0.71).

Conclusion

Depression in PD is associated with white matter microstructural alterations. The SVM machine learning model based on DTI parameters could be valuable for the individualized diagnosis of dPD.

Depression in Patients with Parkinson's Disease: Current Understanding of its Neurobiology and Implications for Treatment

Depression is one of the most frequent and burdensome non-motor symptoms in Parkinson’s disease (PD), across all stages. Even when its severity is mild, PD depression has a great impact on quality of life for these patients and their caregivers. Accordingly, accurate diagnosis, supported by validated scales, identification of risk factors, and recognition of motor and non-motor symptoms comorbid to depression are critical to understanding the neurobiology of depression, which in turn determines the effectiveness of dopaminergic drugs, antidepressants and non-pharmacological interventions. Recent advances using in vivo functional and structural imaging demonstrate that PD depression is underpinned by dysfunction of limbic networks and monoaminergic systems, depending on the stage of PD and its associated symptoms, including apathy, anxiety, rapid eye movement sleep behavior disorder (RBD), cognitive impairment and dementia. In particular, the evolution of serotonergic, noradrenergic, and dopaminergic dysfunction and abnormalities of limbic circuits across time, involving the anterior cingulate and orbitofrontal cortices, amygdala, thalamus and ventral striatum, help to delineate the variable expression of depression in patients with prodromal, early and advanced PD. Evidence is accumulating to support the use of dual serotonin and noradrenaline reuptake inhibitors (desipramine, nortriptyline, venlafaxine) in patients with PD and moderate to severe depression, while selective serotonin reuptake inhibitors, repetitive transcranial magnetic stimulation and cognitive behavioral therapy may also be considered. In all patients, recent findings advocate that optimization of dopamine replacement therapy and evaluation of deep brain stimulation of the subthalamic nucleus to improve motor symptoms represents an important first step, in addition to physical activity. Overall, this review indicates that increasing understanding of neurobiological changes help to implement a roadmap of tailored interventions for patients with PD and depression, depending on the stage and comorbid symptoms underlying PD subtypes and their prognosis.

Relationship between White Matter Alterations and Pathophysiological Symptoms in Patients with Ultra-High Risk of Psychosis, First-Episode, and Chronic Schizophrenia

Some symptoms of schizophrenia might be present before full-blown psychosis, so white matter changes must be studied both in individuals with emerging psychosis and chronic schizophrenia. A total of 86 patients—12 ultra-high risk of psychosis (UHR), 20 first episode psychosis (FEP), 54 chronic schizophrenia (CS), and 33 healthy controls (HC)—underwent psychiatric examination and diffusion tensor imaging (DTI) in a 3-Tesla MRI scanner. We assessed fractional anisotropy (FA) and mean diffusivity (MD) of the superior longitudinal fasciculus (SLF) and inferior longitudinal fasciculus (ILS). We found that CS patients had lower FA than FEP patients (p = 0.025) and HC (p = 0.088), and higher MD than HC (p = 0.037) in the right SLF. In the CS group, we found positive correlations of MD in both right ILF (rho = 0.39, p < 0.05) and SLF (rho = 0.43, p < 0.01) with disorganization symptoms, as well as negative correlation of FA in the right ILF with disorganization symptoms (rho = −0.43, p < 0.05). Among UHR individuals, we found significant negative correlations between MD in the left ILF and negative (r = −0.74, p < 0.05) and general symptoms (r = −0.77, p < 0.05). However promising, these findings should be treated as preliminary, and further research must verify whether they can be treated as potential biomarkers of psychosis.

Metabolic correlates of olfactory dysfunction in COVID-19 and Parkinson's disease (PD) do not overlap

Purpose

Hyposmia is a common feature of COVID-19 and Parkinson’s disease (PD). As parkinsonism has been reported after COVID-19, a link has been hypothesized between SARS-CoV2 infection and PD. We aimed to evaluate brain metabolic correlates of isolated persistent hyposmia after mild-to-moderate COVID-19 and to compare them with metabolic signature of hyposmia in drug-naïve PD patients.

Methods

Forty-four patients who experienced hyposmia after SARS-COV2 infection underwent brain [¹⁸F]-FDG PET in the first 6 months after recovery. Olfaction was assessed by means of the 16-item “Sniffin’ Sticks” test and patients were classified as with or without persistent hyposmia (COVID-hyposmia and COVID-no-hyposmia respectively). Brain [¹⁸F]-FDG PET of post-COVID subgroups were compared in SPM12. COVID-hyposmia patients were also compared with eighty-two drug-naïve PD patients with hyposmia. Multiple regression analysis was used to identify correlations between olfactory test scores and brain metabolism in patients’ subgroups.

Results

COVID-hyposmia patients (n = 21) exhibited significant hypometabolism in the bilateral gyrus rectus and orbitofrontal cortex with respect to COVID-non-hyposmia (n = 23) (p < 0.002) and in middle and superior temporal gyri, medial/middle frontal gyri, and right insula with respect to PD-hyposmia (p < 0.012). With respect to COVID-hyposmia, PD-hyposmia patients showed hypometabolism in inferior/middle occipital gyri and cuneus bilaterally. Olfactory test scores were directly correlated with metabolism in bilateral rectus and medial frontal gyri and in the right middle temporal and anterior cingulate gyri in COVID-hyposmia patients (p < 0.006) and with bilateral cuneus/precuneus and left lateral occipital cortex in PD-hyposmia patients (p < 0.004).

Conclusion

Metabolic signature of persistent hyposmia after COVID-19 encompasses cortical regions involved in olfactory perception and does not overlap metabolic correlates of hyposmia in PD.

Association of brain white matter microstructure with cognitive performance in major depressive disorder and healthy controls: a diffusion-tensor imaging study

Cognitive deficits are central attendant symptoms of major depressive disorder (MDD) with a crucial impact in patients' everyday life. Thus, it is of particular clinical importance to understand their pathophysiology. The aim of this study was to investigate a possible relationship between brain structure and cognitive performance in MDD patients in a well-characterized sample. N = 1007 participants (N_MDD = 482, healthy controls (HC): N_HC = 525) were selected from the FOR2107 cohort for this diffusion-tensor imaging study employing tract-based spatial statistics. We conducted a principal component analysis (PCA) to reduce neuropsychological test results, and to discover underlying factors of cognitive performance in MDD patients. We tested the association between fractional anisotropy (FA) and diagnosis (MDD vs. HC) and cognitive performance factors. The PCA yielded a single general cognitive performance factor that differed significantly between MDD patients and HC (P < 0.001). We found a significant main effect of the general cognitive performance factor in FA (P_tfce-FWE = 0.002) in a large bilateral cluster consisting of widespread frontotemporal-association fibers. In MDD patients this effect was independent of medication intake, the presence of comorbid diagnoses, the number of previous hospitalizations, and depressive symptomatology. This study provides robust evidence that white matter disturbances and cognitive performance seem to be associated. This association was independent of diagnosis, though MDD patients show more pronounced deficits and lower FA values in the global white matter fiber structure. This suggests a more general, rather than the depression-specific neurological basis for cognitive deficits.

Cognitive Training in Parkinson's Disease Induces Local, Not Global, Changes in White Matter Microstructure

Previous studies showed that cognitive training can improve cognitive performance in various neurodegenerative diseases but little is known about the effects of cognitive training on the brain. Here, we investigated the effects of our cognitive training paradigm, COGTIPS, on regional white matter microstructure and structural network topology. We previously showed that COGTIPS has small, positive effects on processing speed. A subsample of 79 PD patients (N = 40 cognitive training group, N = 39 active control group) underwent multi-shell diffusion-weighted imaging pre- and post-intervention. Our pre-registered analysis plan (osf.io/cht6g) entailed investigating white matter microstructural integrity (e.g., fractional anisotropy) in five tracts of interest, including the anterior thalamic radiation (ATR), whole-brain tract-based spatial statistics (TBSS), and the topology of the structural network. Relative to the active control condition, cognitive training had no effect on topology of the structural network or whole-brain TBSS. Cognitive training did lead to a reduction in fractional anisotropy in the ATR (B [SE]: - 0.32 [0.12], P = 0.01). This reduction was associated with faster responses on the Tower of London task (r = 0.42, P = 0.007), but this just fell short of our statistical threshold (P < 0.006). Post hoc "fixel-based" analyses showed that this was not due to changes in fiber density and cross section. This suggests that the observed effect in the ATR is due to training-induced alterations in neighboring fibers running through the same voxels, such as intra-striatal and thalamo-striatal fibers. These results indicate that 8 weeks of cognitive training does not alter network topology, but has subtle local effects on structural connectivity.

Injuries in Left Corticospinal Tracts, Forceps Major, and Left Superior Longitudinal Fasciculus (Temporal) as the Quality Indicators for Major Depressive Disorder

At present, the etiology and pathogenesis of major depressive disorder (MDD) are still not clear. Studies have found that the risk of first-degree relatives of MDD is 2-3 times that of the general population. Diffusion tensor imaging (DTI) has been previously used to explore the pathogenesis of MDD. The purpose of this study is to explore the etiology of MDD by DTI and further to explore the correlation between its clinical characteristics and the structural changes of white matter in the brain. The study included 27 first-episode, drug-naive patients with MDD, 16 first-degree relatives without MDD, and 28 healthy control subjects with no family history of MDD (HC). Results showed that the fractional anisotropy (FA) differences among the three groups were mainly in the left anterior thalamic radiation (LATR), right anterior thalamic radiation (RATR), left corticospinal tracts (LCST), forceps major (FMa), right inferior longitudinal fasciculus (RILF), and left superior longitudinal fasciculus (temporal) (LSLF(T)). Among the 6 sites, LCST, FMa, and LSLF(T) showed significant differences between MDD and First-degree relatives compared to HC. MDD patients had significant emotional symptoms, somatic symptoms, and cognitive impairment. FMa FA was significantly positively correlated with delayed memory score (r = 0.43, P = 0.031), and RILF FA was significantly negatively correlated with the FSS score (r = -0.42, P = 0.028). These results revealed that the white matter characteristics of MDD-susceptible patients were LCST, FMa, and LSLF(T) lesions, all of which may be quality indicators of MDD.

Alteration of brain structural connectivity in progression of Parkinson's disease: A connectome-wide network analysis

Pinpointing the brain dysconnectivity in idiopathic rapid eye movement sleep behaviour disorder (iRBD) can facilitate preventing the conversion of Parkinson's disease (PD) from prodromal phase. Recent neuroimage investigations reported disruptive brain white matter connectivity in both iRBD and PD, respectively. However, the intrinsic process of the human brain structural network evolving from iRBD to PD still remains largely unknown. To address this issue, 151 participants including iRBD, PD and age-matched normal controls were recruited to receive diffusion MRI scans and neuropsychological examinations. The connectome-wide association analysis was performed to detect reorganization of brain structural network along with PD progression. Eight brain seed regions in both cortical and subcortical areas demonstrated significant structural pattern changes along with the progression of PD. Applying machine learning on the key connectivity related to these seed regions demonstrated better classification accuracy compared to conventional network-based statistic. Our study shows that connectome-wide association analysis reveals the underlying structural connectivity patterns related to the progression of PD, and provide a promising distinct capability to predict prodromal PD patients.

Brain Metabolic Correlates of Persistent Olfactory Dysfunction after SARS-Cov2 Infection

We aimed to evaluate the brain hypometabolic signature of persistent isolated olfactory dysfunction after SARS-CoV-2 infection. Twenty-two patients underwent whole-body [¹⁸F]-FDG PET, including a dedicated brain acquisition at our institution between May and December 2020 following their recovery after SARS-Cov2 infection. Fourteen of these patients presented isolated persistent hyposmia (smell diskettes olfaction test was used). A voxel-wise analysis (using Statistical Parametric Mapping software version 8 (SPM8)) was performed to identify brain regions of relative hypometabolism in patients with hyposmia with respect to controls. Structural connectivity of these regions was assessed (BCB toolkit). Relative hypometabolism was demonstrated in bilateral parahippocampal and fusiform gyri and in left insula in patients with respect to controls. Structural connectivity maps highlighted the involvement of bilateral longitudinal fasciculi. This study provides evidence of cortical hypometabolism in patients with isolated persistent hyposmia after SARS-Cov2 infection. [¹⁸F]-FDG PET may play a role in the identification of long-term brain functional sequelae of COVID-19.

Differentiating dementia with Lewy bodies from Alzheimer's disease and Parkinson's disease dementia: an update on imaging modalities

Dementia with Lewy bodies is the second most common cause of neurodegenerative dementia after Alzheimer's disease. Dementia with Lewy bodies can provide a diagnostic challenge due to the frequent overlap of clinical signs with other neurodegenerative conditions, namely Parkinson's disease dementia, and Alzheimer's disease. Part of this clinical overlap is due to the neuropathological overlap. Dementia with Lewy bodies is characterized by the accumulation of aggregated α-synuclein protein in Lewy bodies, similar to Parkinson's disease and Parkinson's disease dementia. However, it is also frequently accompanied by aggregation of amyloid-beta and tau, the pathological hallmarks of Alzheimer's disease. Neuroimaging is central to the diagnostic process. This review is an overview of both established and evolving imaging methods that can improve diagnostic accuracy and improve management of this disorder.

Visual hallucinations and inferior longitudinal fasciculus in Parkinson's disease

INTRODUCTION

We investigated whether disruption of the inferior longitudinal fasciculus and inferior fronto-occipital fasciculus are associated with visual hallucinations in Parkinson's disease (PD).

METHODS

Sixty consecutive right-handed patients with PD with and without visual hallucinations were enrolled in this cross-sectional study. Diffusion tensor imaging was acquired by 3.0 T magnetic resonance imaging. We measured fractional anisotropy and mean diffusivity of the bilateral inferior longitudinal fasciculus and inferior fronto-occipital fasciculus using diffusion tensor tractography analysis software.

RESULTS

Seventeen patients with PD had visual hallucinations; these patients tended to have lower fractional anisotropy and higher mean diffusivity values in all fasciculi than did patients without visual hallucinations. A univariate logistic analysis showed that the presence of visual hallucinations was significantly associated with lower fractional anisotropy and higher mean diffusivity of the left inferior longitudinal fasciculus, and lower Mini-Mental State Examination (MMSE) scores. A multivariable logistic analysis adjusted by MMSE scores and disease duration showed a significant association between the presence of visual hallucinations and fractional anisotropy and mean diffusivity values of the left inferior longitudinal fasciculus.

CONCLUSIONS

Our results suggest that disruption of left inferior longitudinal fasciculus integrity is associated with visual hallucinations in patients with PD, independent of cognitive impairment and disease duration.

Implicating causal brain imaging endophenotypes in Alzheimer's disease using multivariable IWAS and GWAS summary data

Recent evidence suggests the existence of many undiscovered heritable brain phenotypes involved in Alzheimer's Disease (AD) pathogenesis. This finding necessitates methods for the discovery of causal brain changes in AD that integrate Magnetic Resonance Imaging measures and genotypic data. However, existing approaches for causal inference in this setting, such as the univariate Imaging Wide Association Study (UV-IWAS), suffer from inconsistent effect estimation and inflated Type I errors in the presence of genetic pleiotropy, the phenomenon in which a variant affects multiple causal intermediate risk phenotypes. In this study, we implement a multivariate extension to the IWAS model, namely MV-IWAS, to consistently estimate and test for the causal effects of multiple brain imaging endophenotypes from the Alzheimer's Disease Neuroimaging Initiative (ADNI) in the presence of pleiotropic and possibly correlated SNPs. We further extend MV-IWAS to incorporate variant-specific direct effects on AD, analogous to the existing Egger regression Mendelian Randomization approach, which allows for testing of remaining pleiotropy after adjusting for multiple intermediate pathways. We propose a convenient approach for implementing MV-IWAS that solely relies on publicly available GWAS summary data and a reference panel. Through simulations with either individual-level or summary data, we demonstrate the well controlled Type I errors and superior power of MV-IWAS over UV-IWAS in the presence of pleiotropic SNPs. We apply the summary statistic based tests to 1578 heritable imaging derived phenotypes (IDPs) from the UK Biobank. MV-IWAS detected numerous IDPs as possible false positives by UV-IWAS while uncovering many additional causal neuroimaging phenotypes in AD which are strongly supported by the existing literature.

White Matter Microstructure Changes and Cognitive Impairment in the Progression of Chronic Kidney Disease

Background

Cognitive impairment is a well-defined complication of chronic kidney disease (CKD), but the neural mechanisms are largely unknown.

Objectives

The study aimed to assess white matter (WM) microstructure changes and their relationship with cognitive impairment development during CKD progression.

Methods

Diffusion tensor imaging (DTI) datasets were acquired from 38 patients with CKD (19 patients were at stage 3; 19 patients were at stage 4) and 22 healthy controls (HCs). Tract-based spatial statistics (TBSS) was implemented to assess the differences in WM integrity among the three groups. The associations between abnormal WM integrity and clinical indicators (digit symbol test scores, the type A number connection test scores, hemoglobin, serum urea, serum creatinine, serum calcium, and serum potassium levels) were also computed.

Results

Compared with patients with CKD at stage 3 and HCs, patients with CKD at stage 4 showed significantly lower fractional anisotropy (FA) and higher mean diffusivity (MD) in the corpus callosum (CC), anterior thalamic radiation, inferior fronto-occipital fasciculus, and inferior longitudinal fasciculus. Correlation analysis showed that the MD in the genu of CC was negatively associated with the digit symbol test scores (r = -0.61, p = 0.01), and the FA in the left anterior thalamic radiation was positively associated with the level of serum calcium (r = 0.58, p = 0.01).

Conclusion

Patients with non-end-stage CKD have multiple abnormalities in WM regions. DTI metrics change with the progression of CKD and are primarily associated with cognitive impairment. The reduced integrity of WM tracts may be related to a low level of blood calcium.

Uncinate fasciculus and word selection processing in Parkinson's disease

We explored with Diffusion Tensor Imaging (DTI) technique whether the ability to select words among competitive alternatives during word production is related to the integrity of the left uncinate fasciculus (UF) in Parkinson's disease (PD). Nineteen PD patients (10 right-sided and 9 left-sided) and 17 matched healthy controls (HC) took part in the study. Participants were asked to derive nouns from verbs (reading from to read) or to generate verbs from nouns (to build from building). Noun and verb production, in this task, differ in the number of lexical entries among which the response is selected, as the noun must be selected from a larger number of alternatives compared to the verb, and thus is more demanding of processing resources. DTI evaluation was obtained for each subject. Fractional anisotropy (FA) and mean diffusivity (MD) maps were derived from DTI and median FA and MD values were computed within the left and right UF. Then, FA and MD of the left and right UF were correlated with noun and verb production. Both the left and right UF-FA correlated with the global (noun + verb) production and noun production in the whole PD group. In right-sided PD, correlations were found with the contralateral UF-FA; in left-sided PD the correlations emerged with both the left and right UF-FA. The most difficult task, noun production, significantly correlated with the right UF-FA in left-sided PD. The left UF is involved in word selection processes, and the right UF intervenes when the selection is particularly demanding of attentional resources.

Altered white matter microarchitecture in Parkinson's disease: a voxel-based meta-analysis of diffusion tensor imaging studies

This study aimed to define the most consistent white matter microarchitecture pattern in Parkinson's disease (PD) reflected by fractional anisotropy (FA), addressing clinical profiles and methodology-related heterogeneity. Web-based publication databases were searched to conduct a meta-analysis of whole-brain diffusion tensor imaging studies comparing PD with healthy controls (HC) using the anisotropic effect size-signed differential mapping. A total of 808 patients with PD and 760 HC coming from 27 databases were finally included. Subgroup analyses were conducted considering heterogeneity with respect to medication status, disease stage, analysis methods, and the number of diffusion directions in acquisition. Compared with HC, patients with PD had decreased FA in the left middle cerebellar peduncle, corpus callosum (CC), left inferior fronto-occipital fasciculus, and right inferior longitudinal fasciculus. Most of the main results remained unchanged in subgroup meta-analyses of medicated patients, early stage patients, voxel-based analysis, and acquisition with 30 diffusion directions. The subgroup meta-analysis of medication-free patients showed FA decrease in the right olfactory cortex. The cerebellum and CC, associated with typical motor impairment, showed the most consistent FA decreases in PD. Medication status, analysis approaches, and the number of diffusion directions have an important impact on the findings, needing careful evaluation in future meta-analyses.

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.