Diffusion tensor imaging and correlations to Parkinson rating scales

Microstructure predicts non-motor outcomes following deep brain stimulation in Parkinson's disease

Deep brain stimulation of the subthalamic nucleus (STN-DBS) effectively treats motor and non-motor symptoms in advanced Parkinson's disease (PD). As considerable interindividual variability of outcomes exists, neuroimaging-based biomarkers, including microstructural metrics, have been proposed to anticipate treatment response. In this prospective open-label study, we sought to detect microstructural properties of brain areas associated with short-term non-motor outcomes following STN-DBS. Thirty-seven PD patients underwent diffusion MRI and clinical assessments at preoperative baseline and 6-month follow-up. Whole brain voxel-wise analysis assessed associations between microstructural metrics and non-motor outcomes. Intact microstructure within specific areas, including the right insular cortex, right putamen, right cingulum, and bilateral corticospinal tract were associated with greater postoperative improvement of non-motor symptom burden. Furthermore, microstructural properties of distinct brain regions were associated with postoperative changes in sleep, attention/memory, urinary symptoms, and apathy. In conclusion, diffusion MRI could support preoperative patient counselling by identifying patients with above- or below-average non-motor responses.

Utility of diffusion tensor imaging and generalized q-sampling imaging for predicting short-term clinical effect of deep brain stimulation in Parkinson's disease

PURPOSE

To assess whether diffusion tensor imaging (DTI) and generalized q-sampling imaging (GQI) metrics could preoperatively predict the clinical outcome of deep brain stimulation (DBS) in patients with Parkinson's disease (PD).

METHODS

In this single-center retrospective study, from September 2021 to March 2023, preoperative DTI and GQI examinations of 44 patients who underwent DBS surgery, were analyzed. To evaluate motor functions, the Unified Parkinson's Disease Rating Scale (UPDRS) during on- and off-medication and Parkinson's Disease Questionnaire-39 (PDQ-39) scales were used before and three months after DBS surgery. The study population was divided into two groups according to the improvement rate of scales: ≥ 50% and < 50%. Five target regions, reported to be affected in PD, were investigated. The parameters having statistically significant difference were subjected to a receiver operating characteristic (ROC) analysis.

RESULTS

Quantitative anisotropy (qa) values from globus pallidus externus, globus pallidus internus (qa_Gpi), and substantia nigra exhibited significant distributional difference between groups in terms of the improvement rate of UPDRS-3 scale during on-medication (p = 0.003, p = 0.0003, and p = 0.0008, respectively). In ROC analysis, the best parameter in predicting DBS response included qa_Gpi with a cut-off value of 0.01370 achieved an area under the ROC curve, accuracy, sensitivity, and specificity of 0.810, 73%, 62.5%, and 85%, respectively. Optimal cut-off values of ≥ 0.01864 and ≤ 0.01162 yielded a sensitivity and specificity of 100%, respectively.

CONCLUSION

The imaging parameters acquired from GQI, particularly qa_Gpi, may have the ability to non-invasively predict the clinical outcome of DBS surgery.

Cortical thickness and white matter microstructure predict freezing of gait development in Parkinson's disease

The clinical applications of the association of cortical thickness and white matter fiber with freezing of gait (FoG) are limited in patients with Parkinson's disease (PD). In this retrospective study, using white matter fiber from diffusion-weighted imaging and cortical thickness from structural-weighted imaging of magnetic resonance imaging, we investigated whether a machine learning-based model can help assess the risk of FoG at the individual level in patients with PD. Data from the Parkinson's Disease Progression Marker Initiative database were used as the discovery cohort, whereas those from the Fujian Medical University Union Hospital Parkinson's Disease database were used as the external validation cohort. Clinical variables, white matter fiber, and cortical thickness were selected by random forest regression. The selected features were used to train the support vector machine(SVM) learning models. The median area under the receiver operating characteristic curve (AUC) was calculated. Model performance was validated using the external validation cohort. In the discovery cohort, 25 patients with PD were defined as FoG converters (15 men, mean age 62.1 years), whereas 60 were defined as FoG nonconverters (38 men, mean age 58.5 years). In the external validation cohort, 18 patients with PD were defined as FoG converters (8 men, mean age 66.9 years), whereas 37 were defined as FoG nonconverters (21 men, mean age 65.1 years). In the discovery cohort, the model trained with clinical variables, cortical thickness, and white matter fiber exhibited better performance (AUC, 0.67-0.88). More importantly, SVM-radial kernel models trained using random over-sampling examples, incorporating white matter fiber, cortical thickness, and clinical variables exhibited better performance (AUC, 0.88). This model trained using the above mentioned features was successfully validated in an external validation cohort (AUC, 0.91). Furthermore, the following minimal feature sets that were used: fractional anisotropy value and mean diffusivity value for right thalamic radiation, age at baseline, and cortical thickness for left precentral gyrus and right dorsal posterior cingulate gyrus. Therefore, machine learning-based models using white matter fiber and cortical thickness can help predict the risk of FoG conversion at the individual level in patients with PD, with improved performance when combined with clinical variables.

Parkinson's Disease Risk Variant rs9638616 is Non-Specifically Associated with Altered Brain Structure and Function

Background

A genome-wide association study (GWAS) variant associated with Parkinson's disease (PD) risk in Asians, rs9638616, was recently reported, and maps to WBSCR17/GALNT17, which is involved in synaptic transmission and neurite development.

Objective

To test the association of the rs9638616 T allele with imaging-derived measures of brain microstructure and function.

Methods

We analyzed 3-Tesla MRI and genotyping data from 116 early PD patients (aged 66.8±9.0 years; 39% female; disease duration 1.25±0.71 years) and 57 controls (aged 68.7±7.4 years; 54% female), of Chinese ethnicity. We performed voxelwise analyses for imaging-genetic association of rs9638616 T allele with white matter tract fractional anisotropy (FA), grey matter volume and resting-state network functional connectivity.

Results

The rs9638616 T allele was associated with widespread lower white matter FA (t = -1.75, p = 0.042) and lower functional connectivity of the supplementary motor area (SMA) (t = -5.05, p = 0.001), in both PD and control groups. Interaction analysis comparing the association of rs9638616 and FA between PD and controls was non-significant. These imaging-derived phenotypes mediated the association of rs9638616 to digit span (indirect effect: β= -0.21 [-0.42,-0.05], p = 0.031) and motor severity (indirect effect: β= 0.15 [0.04,0.26], p = 0.045).

Conclusions

We have shown that a novel GWAS variant which is biologically linked to synaptic transmission is associated with white matter tract and functional connectivity dysfunction in the SMA, supported by changes in clinical motor scores. This provides pathophysiologic clues linking rs9638616 to PD risk and might contribute to future risk stratification models.

The challenging quest of neuroimaging: From clinical to molecular-based subtyping of Parkinson disease and atypical parkinsonisms

The current framework of Parkinson disease (PD) focuses on phenotypic classification despite its considerable heterogeneity. We argue that this method of classification has restricted therapeutic advances and therefore limited our ability to develop disease-modifying interventions in PD. Advances in neuroimaging have identified several molecular mechanisms relevant to PD, variation within and between clinical phenotypes, and potential compensatory mechanisms with disease progression. Magnetic resonance imaging (MRI) techniques can detect microstructural changes, disruptions in neural pathways, and metabolic and blood flow alterations. Positron emission tomography (PET) and single-photon emission computed tomography (SPECT) imaging have informed the neurotransmitter, metabolic, and inflammatory dysfunctions that could potentially distinguish disease phenotypes and predict response to therapy and clinical outcomes. However, rapid advancements in imaging techniques make it challenging to assess the significance of newer studies in the context of new theoretical frameworks. As such, there needs to not only be a standardization of practice criteria in molecular imaging but also a rethinking of target approaches. In order to harness precision medicine, a coordinated shift is needed toward divergent rather than convergent diagnostic approaches that account for interindividual differences rather than similarities within an affected population, and focus on predictive patterns rather than already lost neural activity.

Microstructure of Brain Nuclei in Early Parkinson's Disease: Longitudinal Diffusion Kurtosis Imaging

BACKGROUND

Diffusion kurtosis imaging provides in vivo measurement of microstructural tissue characteristics and could help guide management of Parkinson's disease.

OBJECTIVE

To investigate longitudinal diffusion kurtosis imaging changes on magnetic resonance imaging in the deep grey nuclei in people with early Parkinson's disease over two years, and whether they correlate with disease progression.

METHODS

We conducted a longitudinal case-control study of early Parkinson's disease. 262 people (Parkinson's disease: n = 185, aged 67.5±9.1 years; 43% female; healthy controls: n = 77, aged 66.6±8.1 years; 53% female) underwent diffusion kurtosis imaging and clinical assessment at baseline and two-year timepoints. We automatically segmented five nuclei, comparing the mean kurtosis and other diffusion kurtosis imaging indices between groups and over time using repeated-measures analysis of variance, and Pearson correlation with the two-year change in Movement Disorder Society Unified Parkinson's Disease Rating Scale Part III.

RESULTS

At baseline, mean kurtosis was higher in Parkinson's disease than controls in the substantia nigra, putamen, thalamus and globus pallidus when adjusting for age, sex, and levodopa equivalent daily dose (p < 0.027). These differences grew over two years, with mean kurtosis increasing for the Parkinson's disease group while remaining stable for the control group; evident in significant "group ×time" interaction effects for the putamen, thalamus and globus pallidus (ηp2= 0.08-0.11, p < 0.015). However, we did not detect significant correlations between increasing mean kurtosis and declining motor function in the Parkinson's disease group.

CONCLUSION

Diffusion kurtosis imaging of specific grey matter structures shows abnormal microstructure in PD at baseline and abnormal progression in PD over two years.

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.

Microstructural alterations predict impaired bimanual control in Parkinson’s disease

Bimanual coordination is impaired in Parkinson’s disease affecting patients’ ability to perform activities of daily living and to maintain independence. Conveyance of information between cortical and subcortical areas is essential for bimanual coordination and relies on the integrity of cerebral microstructure. As pathological deposition of alpha-synuclein compromises microstructure in Parkinson’s disease, we investigated the relationship between microstructural integrity and bimanual coordination using diffusion-weighted MRI in 23 patients with Parkinson’s disease (mean age ± standard deviation: 56.0 ± 6.45 years; 8 female) and 26 older adults (mean age ± standard deviation: 58.5 ± 5.52 years). Whole-brain analysis revealed specific microstructural alterations between patients and healthy controls matched for age, sex, handedness, and cognitive status congruent with the literature and known Parkinson’s disease pathology. A general linear model revealed distinct microstructural alterations associated with poor bimanual coordination in Parkinson’s disease, corrected for multiple comparisons using a permutation-based approach. Integrating known functional topography, we conclude that distinct changes in microstructure cause an impediment of structures involved in attention, working memory, executive function, motor planning, motor control, and visual processing contributing to impaired bimanual coordination in Parkinson’s disease.

White matter changes in drug-naïve Parkinson's disease patients with impulse control & probable REM sleep behavior disorders

BACKGROUND

According to epidemiological studies, Parkinson's disease (PD) patients with probable REM sleep behavior disorder (pRBD) are more prone to develop impulse control disorders (ICDs), which is shown to be present in drug-naïve PD patients, and vice versa.

OBJECTIVES

To investigate white-matter integrity differences, with and without comorbid pRBD and ICDs.

METHODS

149 de-novo PD patients and 30 age- and gender-matched controls from the Parkinson's Progression Markers Initiative were studied. PD subjects were categorized into four groups with and without these comorbidities. We investigated the white matter integrity differences between these groups.

RESULTS

PDs with only ICDs manifested greater fractional anisotropy (FA) and lower mean diffusivity (MD) in ipsilateral cerebellar connections when compared to controls and to Parkinson's with both comorbid disorders. In contrast, significantly lower FA and higher MD in the ipsilateral fornix-stria-terminalis was observed in PDs with only pRBD compared to controls and to PDs without either comorbid disorder. Also, PDs with only pRBD manifested greater FA in contralateral putamen when compared to controls.

CONCLUSIONS

Our results suggest the presence of an underlying neural network in PDs with ICDs, particularly involving cerebellar connections, which makes the subjects susceptible to pRBD. Lower white-matter integrity in the fornix of PDs with only pRBD suggests a neuropathological pathway specific to sleep behavior disorder, independent of impulse control disorders. Greater white-matter integrity observed in PDs without comorbid ICDs, regardless of their comorbid pRBD status, might reflect compensatory mechanisms. Targeted therapies for this particular neuropathology may help prevent these comorbidities.

Neuroimaging Detectable Differences between Parkinson's Disease Motor Subtypes: A Systematic Review

BACKGROUND

The neuroanatomical substrates of Parkinson's disease (PD) with tremor-dominance (TD) and those with non-tremor dominance (nTD), postural instability and gait difficulty (PIGD), and akinetic-rigid (AR) are not fully differentiated. A better understanding of symptom specific pathoanatomical markers of PD subtypes may result in earlier diagnosis and more tailored treatment. Here, we aim to give an overview of the neuroimaging literature that compared PD motor subtypes.

METHODS

A systematic literature review on neuroimaging studies of PD subtypes was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Search terms submitted to the PubMed database included: "Parkinson's disease", "MRI" and "motor subtypes" (TD, nTD, PIGD, AR). The results are first discussed from macro to micro level of organization (i.e., (1) structural; (2) functional; and (3) molecular) and then by applied imaging methodology.

FINDINGS

Several neuroimaging methods including diffusion imaging and positron emission tomography (PET) distinguish specific PD motor subtypes well, although findings are mixed. Furthermore, our review demonstrates that nTD-PD patients have more severe neuroalterations compared to TD-PD patients. More specifically, nTD-PD patients have deficits within striato-thalamo-cortical (STC) circuitry and other thalamocortical projections related to cognitive and sensorimotor function, while TD-PD patients tend to have greater cerebello-thalamo-cortical (CTC) circuitry dysfunction.

CONCLUSIONS

Based on the literature, STC and CTC circuitry deficits seem to be the key features of PD and the subtypes. Future research should make greater use of multimodal neuroimaging and techniques that have higher sensitivity in delineating subcortical structures involved in motor diseases.

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.

Investigation of local white matter abnormality in Parkinson's disease by using an automatic fiber tract parcellation

The deficits of white matter (WM) microstructure are involved during Parkinson's disease (PD) progression. Most current methods identify key WM tracts relying on cortical regions of interest (ROIs). However, such ROI methods can be challenged due to low diffusion anisotropy near the gray matter (GM), which could result in a low sensitivity of tract identification. This work proposes an automatic WM parcellation method to improve the accuracy of WM tract identification and locate abnormal tracts by using sensitive features. The proposed method consists of 1) whole brain WM parcellation using an established fiber clustering method, without using any ROIs, 2) features of fasciculus were calculated to quantify diffusion measures at each equal cross-section along the whole cluster. Then, we use the proposed features to investigate the WM difference in PD compared with healthy controls (HC). We also use these features to investigate the relationship of clinical symptoms and specific fiber tracts. The novelty of the proposed method is that it automatically identifies the abnormal WM fibers in cluster degree. Experiment results indicated that the proposed method had advantage in detecting the local WM abnormality by performing between-group statistical analysis in 30 patients with PD and 28 HC. We found 13 hemisphere clusters and 8 commissural clusters had significant group difference (p < 0.05, corrected by FDR method) in local regions, which belonged to multiple fiber tracts including cingulum bundle (CB), inferior occipito-frontal fasciculus (IoFF), corpus callosum (CC), external capsule (EC), uncinate fasciculus (UF), superior longitudinal fasciculus (SLF) and thalamo front (TF). We also found clusters that had relevance with clinical indices of cognitive function (2 clusters), athletic function (6 clusters), and depressive state (2 clusters) in these significant clusters. From the experiment results, it confirmed the ability of the proposed method to identify potential WM microstructure abnormality.

Effects of Subthalamic Deep Brain Stimulation With Different Frequencies in a Parkinsonian Rat Model

OBJECTIVE

Subthalamic deep brain stimulation (STN-DBS) could be an effective alternative treatment for patients with Parkinson's disease (PD). However, the mechanisms of deep brain stimulation (DBS) at different frequencies are still unclear. In this study, diffusion tensor imaging (DTI) was used to detect parameter changes in different regions of rat brains after DBS, and rat exercise capacity and brain tissue immunohistochemistry were evaluated.

MATERIALS AND METHODS

The 6-hydroxydopamine-induced hemi-parkinsonian rat models were made and divided into four groups: a control group, sham group, low-frequency group, and high-frequency group. Low-frequency (30 Hz) and high-frequency (130 Hz) DBS were given to the STN in rats. First, an open-field experiment was used to evaluate changes in exercise performance. Then, the DTI was used to measure parameter changes in the substantia nigra (SN). Finally, immunohistochemistry was used to analyze the expression of tyrosine hydroxylase (TH), NeuN, and α-synuclein (α-syn) in the SN in the rats.

RESULTS

There were significant differences in movement distance changes between the high-frequency stimulation (HFS) group and low-frequency stimulation (LFS) group, the HFS group and Ctrl group, and the Sham group and Ctrl group (all p < 0.05) after one week of stimulation. In the HFS group, the fractional anisotropy value of the SN was significantly higher than that of the other groups (p < 0.05), and the apparent diffusion coefficient and radial diffusion coefficient values were significantly lower than those of the other groups (p < 0.01). Immunohistochemical analysis showed that the integral optical density values of SN TH staining (p < 0.01) and NeuN staining (p < 0.05) in the HFS group were both significantly higher than those in the other groups.

CONCLUSION

STN-HFS (130 Hz) and sham operation for one week can significantly improve the exercise performance of PD rats. The exercise performance of PD rats in LFS group (30 Hz) is worse compared with HFS group (130 Hz). HFS plays a role in neuroprotection and improvement of exercise performance of PD rats. Moreover, DTI can be used as an effective technique to assess the therapeutic effects and severity of PD.

NfL as a biomarker for neurodegeneration and survival in Parkinson disease

OBJECTIVE

To determine whether neurofilament light chain protein in CSF (cNfL), a sensitive biomarker of neuroaxonal damage, reflects disease severity or can predict survival in Parkinson disease (PD).

METHODS

We investigated whether disease severity, phenotype, or survival in patients with new-onset PD correlates with cNfL concentrations around the time of diagnosis in the population-based New Parkinsonism in Umeå (NYPUM) study cohort (n = 99). A second, larger new-onset PD cohort (n = 194) was used for independent validation. Association of brain pathology with the cNfL concentration was examined with striatal dopamine transporter imaging and repeated diffusion tensor imaging at baseline and 1 and 3 years.

RESULTS

Higher cNfL in the early phase of PD was associated with greater severity of all cardinal motor symptoms except tremor in both cohorts and with shorter survival and impaired olfaction. cNfL concentrations above the median of 903 ng/L conferred an overall 5.8 times increased hazard of death during follow-up. After adjustment for age and sex, higher cNfL correlated with striatal dopamine transporter uptake deficits and lower fractional anisotropy in diffusion tensor imaging of several axonal tracts.

CONCLUSIONS

cNfL shows usefulness as a biomarker of disease severity and to predict survival in PD. The present results indicate that the cNfL concentration reflects the intensity of the neurodegenerative process, which could be important in future clinical trials.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that in patients with PD, cNfL concentrations are associated with more severe disease and shorter survival.

Clinical Progression of Parkinson's Disease: Insights from the NINDS Common Data Elements

BACKGROUND/OBJECTIVE

To synchronize data collection, the National Institute of Neurological Disorders and Stroke (NINDS) recommended Common Data Elements (CDEs) for use in Parkinson's disease (PD) research. This study delineated the progression patterns of these CDEs in a cohort of PD patients.

METHODS

One hundred-twenty-five PD patients participated in the PD Biomarker Program (PDBP) at Penn State. CDEs, including MDS-Unified PD Rating Scale (UPDRS)-total, questionnaire-based non-motor (-I) and motor (-II), and rater-based motor (-III) subscales; Montreal Cognitive Assessment (MoCA); Hamilton Depression Rating Scale (HDRS); University of Pennsylvania Smell Identification Test (UPSIT); and PD Questionnaire (PDQ-39) were obtained at baseline and three annual follow-ups. Annual change was delineated for PD or subgroups [early = PDE, disease duration (DD) <1 y; middle = PDM, DD = 1-5 y; and late = PDL, DD > 5 y] using mixed effects model analyses.

RESULTS

UPDRS-total, -II, and PDQ-39 scores increased significantly, and UPSIT decreased, whereas UPDRS-I, -III, MoCA, and HDRS did not change, over 36 months in the overall PD cohort. In the PDE subgroup, UPDRS-II increased and UPSIT decreased significantly, whereas MoCA and UPSIT decreased significantly in the PDM subgroup. In the PDL subgroup, UPDRS-II and PDQ-39 increased significantly. Other metrics within each individual subgroup did not change. Sensitivity analyses using subjects with complete data confirmed these findings.

CONCLUSION

Among CDEs, UPDRS-total, -II, PDQ-39, and UPSIT all are sensitive metrics to track PD progression. Subgroup analyses revealed that these CDEs have distinct stage-dependent sensitivities, with UPSIT for DD < 5 y, PDQ-39 for DD > 5 y, UPDRS-II for early (DD < 1) or later stages (DD > 5).

Free-Water Imaging in White and Gray Matter in Parkinson's Disease

This study aimed to discriminate between neuroinflammation and neuronal degeneration in the white matter (WM) and gray matter (GM) of patients with Parkinson’s disease (PD) using free-water (FW) imaging. Analysis using tract-based spatial statistics (TBSS) of 20 patients with PD and 20 healthy individuals revealed changes in FW imaging indices (i.e., reduced FW-corrected fractional anisotropy (FA_T), increased FW-corrected mean, axial, and radial diffusivities (MD_T, AD_T, and RD_T, respectively) and fractional volume of FW (FW) in somewhat more specific WM areas compared with the changes of DTI indices. The region-of-interest (ROI) analysis further supported these findings, whereby those with PD showed significantly lower FA_T and higher MD_T, AD_T, and RD_T (indices of neuronal degeneration) in anterior WM areas as well as higher FW (index of neuroinflammation) in posterior WM areas compared with the controls. Results of GM-based spatial statistics (GBSS) analysis revealed that patients with PD had significantly higher MD_T, AD_T, and FW than the controls, whereas ROI analysis showed significantly increased MD_T and FW and a trend toward increased AD_T in GM areas, corresponding to Braak stage IV. These findings support the hypothesis that neuroinflammation precedes neuronal degeneration in PD, whereas WM microstructural alterations precede changes in GM.

Brain imaging of locomotion in neurological conditions

Impaired locomotion is a frequent and major source of disability in patients with neurological conditions. Different neuroimaging methods have been used to understand the brain substrates of locomotion in various neurological diseases (mainly in Parkinson's disease) during actual walking, and while resting (using mental imagery of gait, or brain-behavior correlation analyses). These studies, using structural (i.e., MRI) or functional (i.e., functional MRI or functional near infra-red spectroscopy) brain imaging, electrophysiology (i.e., EEG), non-invasive brain stimulation (i.e., transcranial magnetic stimulation, or transcranial direct current stimulation) or molecular imaging methods (i.e., PET, or SPECT) reveal extended brain networks involving both grey and white matters in key cortical (i.e., prefrontal cortex) and subcortical (basal ganglia and cerebellum) regions associated with locomotion. However, the specific roles of the various pathophysiological mechanisms encountered in each neurological condition on the phenotype of gait disorders still remains unclear. After reviewing the results of individual brain imaging techniques across the common neurological conditions, such as Parkinson's disease, dementia, stroke, or multiple sclerosis, we will discuss how the development of new imaging techniques and computational analyses that integrate multivariate correlations in "large enough datasets" might help to understand how individual pathophysiological mechanisms express clinically as an abnormal gait. Finally, we will explore how these new analytic methods could drive our rehabilitative strategies.

Progressive Decline in Gray and White Matter Integrity in de novo Parkinson's Disease: An Analysis of Longitudinal Parkinson Progression Markers Initiative Diffusion Tensor Imaging Data

Background: Progressive neuronal loss in neurodegenerative diseases such as Parkinson's disease (PD) is associated with progressive degeneration of associated white matter tracts as measured by diffusion tensor imaging (DTI). These findings may have diagnostic and functional implications but their value in de novo PD remains unknown. Here we analyzed longitudinal DTI data from Parkinson's Progression Markers Initiative de novo PD patients for changes over time relative to healthy control (HC) participants. Methods: Baseline and 1-year follow-up DTI MRI data from 71 PD patients and 45 HC PPMI participants were included in the analyses. Whole-brain fractional anisotropy (FA) and mean diffusivity (MD) images were compared for baseline group differences and group-by-time interactions. Baseline and 1-year changes in DTI values were correlated with changes in DTI measures and symptom severity, respectively. Results: At baseline, PD patients showed significantly increased FA in brainstem, cerebellar, anterior corpus callosal, inferior frontal and inferior fronto-occipital white matter and increased MD in primary sensorimotor and supplementary motor regions. Over 1 year PD patients showed a significantly stronger decline in FA compared to HC in the optic radiation and corpus callosum and parietal, occipital, posterior temporal, posterior thalamic, and vermis gray matter. Significant increases in MD were observed in white matter of the midbrain, optic radiation and corpus callosum, while gray matter of prefrontal, insular and posterior thalamic regions. Baseline brainstem FA white matter (WM) values predicted 1-year changes in FA white matter and MD gray matter values. White but not gray matter changes in both FA and MD were significantly associated with changes in symptom severity. Conclusion: Significant gray and white matter DTI alterations are observable at the time of PD diagnosis and expand in the first year of de novo PD to other cortical and white matter regions. This pattern of DTI changes is in line with preclinical and neuroanatomical studies suggesting that the increased spatial spread of alpha-synuclein neuropathology is the key mechanism of PD progression. Taken together, these findings suggest that DTI may serve as a sensitive biomarker of disease progression in early-stage PD.

Is Diffusion Tensor Imaging a Good Biomarker for Early Parkinson's Disease?

Objectives: To assess white matter abnormalities in Parkinson's disease (PD).

Methods: A hundred and thirty-two patients with PD (mean age 60.93 years; average disease duration 7.8 years) and 137 healthy controls (HC; mean age 57.8 years) underwent the same MRI protocol. Patients were assessed by clinical scales and a complete neurological evaluation. We performed a TBSS analysis to compare patients and controls, and we divided patients into early PD, moderate PD, and severe PD and performed an ROI analysis using tractography.

Results: With TBSS we found lower FA in patients in corpus callosum, internal and external capsule, corona radiata, thalamic radiation, sagittal stratum, cingulum and superior longitudinal fasciculus. Increased AD was found in the corpus callosum, fornix, corticospinal tract, superior cerebellar peduncle, cerebral peduncle, internal and external capsules, corona radiata, thalamic radiation and sagittal stratum and increased RD were seen in the corpus callosum, internal and external capsules, corona radiata, sagittal stratum, fornix, and cingulum. Regarding the ROIs, a GLM analysis showed abnormalities in all tracts, mainly in the severe group, when compared to HC, mild PD and moderate PD.

Conclusions: Since major abnormalities were found in the severe PD group, we believe DTI analysis might not be the best tool to assess early alterations in PD, and probably, functional and other structural analysis might suit this purpose better. However it can be used to differentiate disease stages, and as a surrogate marker to assess disease progression, being an important measure that could be used in clinical trials.

HIGHLIGHTS

DTI is not the best tool to identify early PD

DTI can differentiate disease stages

DTI analysis may be a useful marker for disease progression

Global, Yet Incomplete Overview of Cohort Studies in Parkinson's disease

BACKGROUND

Parkinson's disease (PD) is characterized by heterogeneity and multifactorial longitudinal changes. To identify PD subtypes and factors influencing the disease course, multiple cohort studies have been designed globally. Knowledge about existing cohorts is pivotal to foster collaboration, which may help to advance the understanding of PD.

OBJECTIVE

To raise the awareness about PD cohorts and potential global collaboration opportunities.

METHODS

Observational cohort studies in clinical PD were identified by a European working group (JPND BioLoC-PD) and through literature search. Using a structured survey investigators of 44 cohorts provided basic information on cohorts and assessments performed.

RESULTS

For the 44 cohorts (32% on early/de-novo PD), 14.666 participants (cohorts' median: 138; range: 23-3.090), a median 1.5-year follow-up interval (0.5-4 years) and a median (planned) observational period of 5 years (1-20 years) were indicated. All studies have assessed motor functions often using rating scales (UPDRS-III; 93% of studies) and less frequently quantitative gait/balance (25%) or fine motor assessments (27%). Cognitive (100%), neuropsychiatric (91%), daily living (78%), sleep (70%), sensory (63%), and gastrointestinal/autonomic (55%) assessments were common and often comparable. Neuroimaging data (82%) and biomaterial (69%) have been collected in many studies. Surprisingly, possible disease modifiers, such as sport/physical activity (11%), have rarely been assessed.

CONCLUSIONS

Existing data of PD cohorts provide vast collaboration opportunities. We propose to establish a comprehensive, up-to-date, open-access internet platform with easy-to-use search tools of PD cohort descriptions and potentially available data. Bringing researchers together to enable collaborative joint, meta- and replication analyses is timely and necessary to advance PD research ultimately required for an understanding of PD that can be translated into more effective therapies.

Longitudinal changes in gray matter regions after cranial radiation and comparative analysis with whole body radiation: a DTI study

PURPOSE

Radiation-induced white matter changes are well known and vastly studied. However, radiation-induced gray matter alterations are still a research question. In the present study, these changes were assessed in a longitudinal manner using Diffusion Tensor Imaging (DTI) and further compared for cranial and whole body radiation exposure.

MATERIALS AND METHODS

Male mice (C57BL/6) were irradiated with cranial or whole body radiation followed by DTI study at 7T animal MRI system during predose, subacute and early delayed phases of radiation sickness. Fractional anisotropy (FA) and mean diffusivity (MD) values were obtained from brain's gray matter regions.

RESULTS

Decreased FA with increased MD was observed prominently in animals exposed to cranial radiation showing most changes at 8 months post irradiation. However, whole body radiation induced FA changes were mostly observed at 1 month post irradiation as compared to controls.

CONCLUSIONS

The differential response after whole body and cranial irradiation observed in the study depicts that radiation exposure of 5 Gy could induce permanent alterations in gray matter regions prominently as observed in Caudoputamen region at all the time points. Thus, our study has bolstered the role of DTI to probe microstructural changes in gray matter regions of brain after radiation exposure.

Current Clinical Applications of Diffusion-Tensor Imaging in Neurological Disorders

Diffusion-tensor imaging (DTI) is a noninvasive medical imaging tool used to investigate the structure of white matter. The signal contrast in DTI is generated by differences in the Brownian motion of the water molecules in brain tissue. Postprocessed DTI scalars can be used to evaluate changes in the brain tissue caused by disease, disease progression, and treatment responses, which has led to an enormous amount of interest in DTI in clinical research. This review article provides insights into DTI scalars and the biological background of DTI as a relatively new neuroimaging modality. Further, it summarizes the clinical role of DTI in various disease processes such as amyotrophic lateral sclerosis, multiple sclerosis, Parkinson's disease, Alzheimer's dementia, epilepsy, ischemic stroke, stroke with motor or language impairment, traumatic brain injury, spinal cord injury, and depression. Valuable DTI postprocessing tools for clinical research are also introduced.

Differential White Matter Regional Alterations in Motor Subtypes of Early Drug-Naive Parkinson's Disease Patients

BACKGROUND

Parkinson's disease (PD) can be classified into tremor dominant (TD) and postural instability and gait difficulty (PIGD) subtypes with TD considered as the benign subtype. The neural alterations of the 2 subtypes in the early stages before administration of medications remain elusive.

OBJECTIVE

This study assessed the subtype-related white matter (WM) microstructural features in newly diagnosed and drug-naive PD patients from the Parkinson's Progression Markers Initiative (PPMI).

METHODS

Sixty-five early PDs with stable subtypes (52 TD and 13 PIGD patients) and 61 controls underwent diffusion tensor imaging (DTI) scanning and clinical assessment. Tract-based special statistics (TBSS), graph-theoretical and network-based analyses were used to compare WM regional and network features between groups.

RESULTS

No differences in disease stages and duration were found between the 2 patient groups. TD patients showed increased fractional anisotropy (FA), but decreased radial and axial diffusivities (RD and AD) in several projection, association, and commissural tracts, compared with PIGD patients and controls. Motor severity had mild-to-moderate correlations with FA and RD of the corpus callosum (genu) in TD, but strong correlations with FA and RD of multiple association tracts in PIGD. Conversely, no significant network changes were noted.

CONCLUSIONS

TD patients showed regionally increased FA but decreased diffusivities, implying neural reorganization to compensate PD pathology in early stages. PIGD patients, despite having similar disease stages and duration, exhibited more WM degradation. These results demonstrate differential WM regional features between the 2 subtypes in early PD and support the notion of TD being a benign subtype.

Lateralized microstructural changes in early-stage Parkinson's disease in anterior olfactory structures, but not in substantia nigra

Parkinson's disease (PD) is a progressive neurological disorder characterized by motor symptoms as well as severe deficits in olfactory function and microstructural changes in olfactory brain regions. Because of the evidence of asymmetric neuropathological features in early-stage PD, we examined whether lateralized microstructural changes occur in olfactory brain regions and the substantia nigra in a group of early-stage PD patients. Using diffusion tensor imaging (DTI) and the University of Pennsylvania Smell Identification Test (UPSIT), we assessed 24 early-stage PD patients (Hoehn and Yahr stage 1 or 2) and 26 healthy controls (HC). We used DTI and a region of interest (ROI) approach to study the microstructure of the left and right anterior olfactory structures (AOS; comprising the olfactory bulbs and anterior end of the olfactory tracts) and the substantia nigra (SN). PD patients had reduced UPSIT scores relative to HC and showed increased mean diffusivity (MD) in the SN, with no lateralized differences. Significant group differences in fractional anisotropy (FA) and MD were seen in the AOS, but these differences were restricted to the right side and were not associated with the primary side of motor symptoms amongst PD patients. No associations were observed between lateralized motor impairment and lateralized microstructural changes in AOS. Impaired olfaction and microstructural changes in AOS are useful for early identification of PD but asymmetries in AOS microstructure seem unrelated to the laterality of PD motor symptoms.

Frontal white matter injuries predestine gait difficulties in Parkinson's disease

OBJECTIVES

This study applies diffusion tensor imaging (DTI) to determine differences in neuronal integrity between motor phenotypes in Parkinson's disease.

MATERIAL AND METHODS

One hundred and twenty-two patients (47 females, mean age = 70.3 years) were included at baseline. Forty patients were tremor dominant (TD), 64 had postural imbalance and gait difficulty (PIGD), and 18 patients were indeterminate. The DTI was repeated after one, three and 5 years, including reassessment of phenotype. DTI was quantified using fractional anisotropy (FA), and mean, radial and axial diffusion. Targeted white matter involved six regions of interests (ROIs) in prefrontal cortex (PFC), the entrance to the external capsule (EEC) and lateral to the horn of the anterior ventricle (LVAH). Grey matter involved the basal ganglia. Data were analysed using mixed linear models with P < 0.05 (Bonferroni corrected) as significance threshold.

RESULTS

PIGD and Indeterminate had reduced FA and axial diffusion in PFC, EEC and LVAH compared to Tremor dominant (P < 0.05). Basal ganglia showed no differences. Post hoc analysis showed that FA correlated negatively, and mean and radial diffusion positively, to PIGD symptoms in EEC, LVAH and four ROIs in PFC (P < 0.05). Tremor symptoms showed no correlations. Patients converting to PIGD and Indeterminate had lower FA, and higher mean and radial diffusion, at baseline in EEC, LVAH and four areas in PFC compared to non-converting patients (P < 0.05).

CONCLUSION

Degeneration in frontal white matter is connected to PIGD symptoms in Parkinson's disease and if present at an early stage, the risk for conversion to the PIGD phenotype increases.

Microstructural Changes within the Basal Ganglia Differ between Parkinson Disease Subtypes

Diffusion tensor imaging (DTI) of the substantia nigra has shown promise in detecting and quantifying neurodegeneration in Parkinson disease (PD). It remains unknown, however, whether differences in microstructural changes within the basal ganglia underlie PD motor subtypes. We investigated microstructural changes within the basal ganglia of mild to moderately affected PD patients using DTI and sought to determine if microstructural changes differ between the tremor dominant (TD) and postural instability/gait difficulty (PIGD) subtypes. Fractional anisotropy, mean diffusivity, radial, and axial diffusivity were obtained from bilateral caudate, putamen, globus pallidus, and substantia nigra of 21 PD patients (12 TD and 9 PIGD) and 20 age-matched healthy controls. T-tests and ANOVA methods were used to compare PD patients, subtypes, and controls, and Spearman correlations tested for relationships between DTI and clinical measures. We found our cohort of PD patients had reduced fractional anisotropy within the substantia nigra and increased mean and radial diffusivity within the substantia nigra and globus pallidus compared to controls, and that changes within those structures were largely driven by the PIGD subtype. Across all PD patients fractional anisotropy within the substantia nigra correlated with disease stage, while in PIGD patients increased diffusivity within the globus pallidus correlated with disease stage and motor severity. We conclude that PIGD patients have more severely affected microstructural changes within the substantia nigra compared to TD, and that microstructural changes within the globus pallidus may be particularly relevant for the manifestation of the PIGD subtype.

Chemical Exchange Saturation Transfer MR Imaging is Superior to Diffusion-Tensor Imaging in the Diagnosis and Severity Evaluation of Parkinson's Disease: A Study on Substantia Nigra and Striatum

Parkinson's disease (PD) is a neurodegenerative disorder characterized by nigrostriatal cell loss. To date, the diagnosis of PD is still based primarily on the clinical manifestations, which may be typical and obvious only in advanced-stage PD. Thus, it is crucial to find a reliable marker for the diagnosis of PD. We conducted this study to assess the diagnostic efficiency of chemical exchange saturation transfer (CEST) imaging and diffusion-tensor imaging (DTI) in PD at 3 T by evaluating changes on substantia nigra and striatum. Twenty-three PD patients and twenty-three age-matched normal controls were recruited. All patients and controls were imaged on a 3-T MR system, using an eight-channel head coil. CEST imaging was acquired in two transverse slices of the head, including substantia nigra and striatum. The magnetization transfer ratio asymmetry at 3.5 ppm, MTRasym(3.5 ppm), and the total CEST signal intensity between 0 and 4 ppm were calculated. Multi-slice DTI was acquired for all the patients and normal controls. Quantitative analysis was performed on the substantia nigra, globus pallidus, putamen, and caudate. The MTRasym(3.5 ppm) value, the total CEST signal intensity, and fractional anisotropy value of the substantia nigra were all significantly lower in PD patients than in normal controls (P = 0.003, P = 0.004, and P < 0.001, respectively). The MTRasym(3.5 ppm) values of the putamen and the caudate were significantly higher in PD patients than in normal controls (P = 0.010 and P = 0.009, respectively). There were no significant differences for the mean diffusivity in these four regions between PD patients and normal controls. In conclusion, CEST MR imaging provided multiple CEST image contrasts in the substantia nigra and the striatum in PD and may be superior to DTI in the diagnosis of PD.

Fractional anisotropy in the substantia nigra in Parkinson's disease: a complex picture

BACKGROUND AND PURPOSE

This study employs magnetic resonance imaging (MRI) diffusion tensor imaging to compare diffusion measures in the brains of patients with Parkinson's disease (PD) with healthy controls using longitudinal data.

METHODS

One-hundred and twenty-two patients and 34 controls were included at baseline. The MRI investigations were repeated after 1, 3 and 5 years. The diffusion measures were quantified using fractional anisotropy and mean, radial and axial diffusion (FA, MD, RD, AD). Regions of interest included the anterior, middle and posterior substantia nigra (SN), but also other areas. Linear models were used to test for the effect of disease and hemispheric lateralization. The P value was set at 0.05 (Bonferroni corrected).

RESULTS

Fractional anisotropy and AD were increased in the three nigral subareas in PD (P < 0.01), but MD and RD were unaltered. The right SN had higher FA than the left in all subareas (P < 0.01). MD and AD were increased in the right anterior part (P < 0.04), whereas MD and RD were decreased in the right middle and posterior parts (P < 0.001). The left middle cerebellar peduncle had increased FA and AD (P < 0.001) and decreased MD and RD (P < 0.01) compared to the right. Diffusion measures did not progress over time and side differences were not related to disease or lateralization of symptoms.

CONCLUSIONS

Increased FA in the SN in PD indicates gliosis and inflammation in the nuclei, but possibly also intrusion of surrounding fibres into the shrinking structure. The hemispheric side differences of diffusion might reflect natural lateralization of connectivity, but their relation to PD must be studied further.

The intrinsic resting state voice network in Parkinson's disease

Over 90 percent of patients with Parkinson's disease experience speech-motor impairment, namely, hypokinetic dysarthria characterized by reduced pitch and loudness. Resting-state functional connectivity analysis of blood oxygen level-dependent functional magnetic resonance imaging is a useful measure of intrinsic neural functioning. We utilized resting-state functional connectivity modeling to analyze the intrinsic connectivity in patients with Parkinson's disease within a vocalization network defined by a previous meta-analysis of speech (Brown et al., 2009). Functional connectivity of this network was assessed in 56 patients with Parkinson's disease and 56 gender-, age-, and movement-matched healthy controls. We also had item 5 and 18 of the UPDRS, and the PDQ-39 Communication subscale available for correlation with the voice network connectivity strength in patients. The within-group analyses of connectivity patterns demonstrated a lack of subcortical-cortical connectivity in patients with Parkinson's disease. At the cortical level, we found robust (homotopic) interhemispheric connectivity but only inconsistent evidence for many intrahemispheric connections. When directly contrasted to the control group, we found a significant reduction of connections between the left thalamus and putamen, and cortical motor areas, as well as reduced right superior temporal gyrus connectivity. Furthermore, most symptom measures correlated with right putamen, left cerebellum, left superior temporal gyrus, right premotor, and left Rolandic operculum connectivity in the voice network. The results reflect the importance of (right) subcortical nodes and the superior temporal gyrus in Parkinson's disease, enhancing our understanding of the neurobiological underpinnings of vocalization impairment in Parkinson's disease.

Recent imaging advances in neurology

Over the recent years, the application of neuroimaging techniques such as magnetic resonance imaging (MRI) and positron emission tomography (PET) has considerably advanced the understanding of complex neurological disorders. PET is a powerful molecular imaging tool, which investigates the distribution and binding of radiochemicals attached to biologically relevant molecules; as such, this technique is able to give information on biochemistry and metabolism of the brain in health and disease. MRI uses high intensity magnetic fields and radiofrequency pulses to provide structural and functional information on tissues and organs in intact or diseased individuals, including the evaluation of white matter integrity, grey matter thickness and brain perfusion. The aim of this article is to review the most recent advances in neuroimaging research in common neurological disorders such as movement disorders, dementia, epilepsy, traumatic brain injury and multiple sclerosis, and to evaluate their contribution in the diagnosis and management of patients.

Microstructural changes in white matter associated with freezing of gait in Parkinson's disease

In Parkinson's disease (PD), freezing of gait (FOG) is associated with widespread functional and structural gray matter changes throughout the brain. Previous study of freezing-related white matter changes was restricted to brainstem and cerebellar locomotor tracts. This study was undertaken to determine the spatial distribution of white matter damage associated with FOG by combining whole brain and striatofrontal seed-based diffusion tensor imaging. Diffusion-weighted images were collected in 26 PD patients and 16 age-matched controls. Parkinson's disease groups with (n = 11) and without freezing of gait (n = 15) were matched for age and disease severity. We applied tract-based spatial statistics to compare fractional anisotropy and mean diffusivity of white matter structure across the whole brain between groups. Probabilistic tractography was used to evaluate fractional anisotropy and mean diffusivity of key subcortico-cortical tracts. Tract-based spatial statistics revealed decreased fractional anisotropy in PD with FOG in bilateral cerebellar and superior longitudinal fascicle clusters. Increased mean diffusivity values were apparent in the right internal capsule, superior frontal cortex, anterior corona radiata, the left anterior thalamic radiation, and cerebellum. Tractography showed consistent white matter alterations in striatofrontal tracts through the putamen, caudate, pallidum, subthalamic nucleus, and in connections of the cerebellar peduncle with subthalamic nucleus and pedunculopontine nucleus bilaterally. We conclude that FOG is associated with diffuse white matter damage involving major cortico-cortical, corticofugal motor, and several striatofrontal tracts in addition to previously described cerebello-pontine connectivity changes. These distributed white matter abnormalities may contribute to the motor and non-motor correlates of FOG.