Progressive microstructural alterations in subcortical nuclei in Parkinson's disease: A diffusion magnetic resonance imaging study

Microstructural alterations of the hypothalamus in Parkinson's disease and probable REM sleep behavior disorder

BACKGROUND

Whether there is hypothalamic degeneration in Parkinson's disease (PD) and its association with clinical symptoms and pathophysiological changes remains controversial.

OBJECTIVES

We aimed to quantify microstructural changes in hypothalamus using a novel deep learning-based tool in patients with PD and those with probable rapid-eye-movement sleep behavior disorder (pRBD). We further assessed whether these microstructural changes associated with clinical symptoms and free thyroxine (FT4) levels.

METHODS

This study included 186 PD, 67 pRBD, and 179 healthy controls. Multi-shell diffusion MRI were scanned and mean kurtosis (MK) in hypothalamic subunits were calculated. Participants were assessed using Unified Parkinson's Disease Rating Scale (UPDRS), RBD Questionnaire-Hong Kong (RBDQ-HK), Hamilton Depression Rating Scale (HAMD), and Activity of Daily Living (ADL) Scale. Additionally, a subgroup of PD (n = 31) underwent assessment of FT4.

RESULTS

PD showed significant decreases of MK in anterior-superior (a-sHyp), anterior-inferior (a-iHyp), superior tubular (supTub), and inferior tubular hypothalamus when compared with healthy controls. Similarly, pRBD exhibited decreases of MK in a-iHyp and supTub. In PD group, MK in above four subunits were significantly correlated with UPDRS-I, HAMD, and ADL. Moreover, MK in a-iHyp and a-sHyp were significantly correlated with FT4 level. In pRBD group, correlations were observed between MK in a-iHyp and UPDRS-I.

CONCLUSIONS

Our study reveals that microstructural changes in the hypothalamus are already significant at the early neurodegenerative stage. These changes are associated with emotional alterations, daily activity levels, and thyroid hormone levels.

Application of diffusional kurtosis imaging for insights into structurally aberrant topology in Parkinson's disease

BACKGROUND

Parkinson's disease (PD) has been regarded as a disconnection syndrome with functional and structural disturbances. However, as the anatomic determinants, the structural disconnections in PD have yet to be fully elucidated.

PURPOSE

To non-invasively construct structural networks based on microstructural complexity and to further investigate their potential topological abnormalities in PD given the technical superiority of diffusion kurtosis imaging (DKI) to the quantification of microstructure.

MATERIAL AND METHODS

The microstructural data of gray matter in both the PD group and the healthy control (HC) group were acquired using DKI. The structural networks were constructed at the group level by a covariation approach, followed by the calculation of topological properties based on graph theory and statistical comparisons between groups.

RESULTS

A total of 51 patients with PD and 50 HCs were enrolled. Individuals were matched between groups with respect to demographic characteristics (P >0.05). The constructed structural networks in both the PD and HC groups featured small-world properties. In comparison with the HC group, the PD group exhibited significantly altered global properties, with higher normalized characteristic path lengths, clustering coefficients, local efficiency values, and characteristic path lengths and lower global efficiency values (P <0.05). In terms of nodal centralities, extensive nodal disruptions were observed in patients with PD (P <0.05); these disruptions were mainly distributed in the sensorimotor network, default mode network, frontal-parietal network, visual network, and subcortical network.

CONCLUSION

These findings contribute to the technical application of DKI and the elucidation of disconnection syndrome in PD.

Optimization of structural connectomes and scaled patterns of structural-functional decoupling in Parkinson's disease

Parkinson's disease (PD) is manifested with disrupted topology of the structural connection network (SCN) and the functional connection network (FCN). However, the SCN and its interactions with the FCN remain to be further investigated. This multimodality study attempted to precisely characterize the SCN using diffusion kurtosis imaging (DKI) and further identify the neuropathological pattern of SCN-FCN decoupling, underscoring the neurodegeneration of PD. Diffusion-weighted imaging and resting-state functional imaging were available for network constructions among sixty-nine patients with PD and seventy demographically matched healthy control (HC) participants. The classification performance and topological prosperities of both the SCN and the FCN were analyzed, followed by quantification of the SCN-FCN couplings across scales. The SCN constructed by kurtosis metrics achieved optimal classification performance (area under the curve 0.89, accuracy 80.55 %, sensitivity 78.40 %, and specificity 80.65 %). Along with diverse alterations of structural and functional network topology, the PD group exhibited decoupling across scales including: reduced global coupling; increased nodal coupling within the sensorimotor network (SMN) and subcortical network (SN); higher intramodular coupling within the SMN and SN and lower intramodular coupling of the default mode network (DMN); decreased coupling between the modules of DMN-fronto-parietal network and DMN-visual network, but increased coupling between the SMN-SN module. Several associations between the coupling coefficient and topological properties of the SCN, as well as between network values and clinical scores, were observed. These findings validated the clinical implementation of DKI for structural network construction with better differentiation ability and characterized the SCN-FCN decoupling as supplementary insight into the pathological process underlying PD.

Histogram analysis of diffusion kurtosis imaging of deep brain nuclei in Parkinson's disease with different motor subtypes

AIM

To evaluate the diagnostic and differential efficacy of diffusion kurtosis imaging (DKI) histogram analysis for different motor subtypes of Parkinson's disease (PD).

MATERIALS AND METHODS

Seventy PD patients including 40 with postural instability and gait disorder (PIGD) and 30 with tremor-dominant (TD) and 36 healthy controls (HC) were enrolled prospectively and underwent MRI examinations. The regions of interest (ROI) in the deep brain nuclei were delineated and features were extracted on the map of mean kurtosis (MK), axial kurtosis (Ka), and radial kurtosis (Kr), respectively. The differences in histogram features between PD patients and HC and between patients with PIGD and TD were compared. The areas under the curve (AUCs) were calculated to evaluate the diagnostic efficacy of all histogram features. The correlations between histogram features and clinical indicators were evaluated.

RESULTS

Some DKI histogram features were significantly different between PD patients and HC, and also different between patients with PIGD and TD (all p<0.05). MK of the substantia nigra pars reticulate (SNprkurtosis), Ka of the substantia nigra pars compacta (SNpc) 50 percentile (SNpcP50), and Kr of SNpc 90th percentile showed the highest AUC for distinguishing patients with PIGD from HC. MK-SNpc 10th percentile, Ka-SNpc 25th percentile, and Kr of the head of the caudate nucleus (CN) 90th percentile had the highest AUC for distinguishing patients with TD from HC. MK of the putamen 10th percentile combined with Ka of the bilateral red nucleus RNkurtosis yielded the highest diagnostic performance with an AUC of 0.762 for distinguishing patients with PIGD from TD. Certain DKI histogram features were correlated with Hoehn-Yahr (H&Y) stage, Mini Mental State Examination (MMSE) score, tremor score, and PIGD score (all p<0.05).

CONCLUSION

DKI histogram analysis was useful to diagnose and discriminate different motor subtypes of PD. Certain DKI histogram features correlated with clinical indicators.

MR imaging and outcome in neonatal HIBD models are correlated with sex: the value of diffusion tensor MR imaging and diffusion kurtosis MR imaging

Objective

Hypoxic-ischemic encephalopathy can lead to lifelong morbidity and premature death in full-term newborns. Here, we aimed to determine the efficacy of diffusion kurtosis (DK) [mean kurtosis (MK)] and diffusion tensor (DT) [fractional anisotropy (FA), mean diffusion (MD), axial diffusion (AD), and radial diffusion (RD)] parameters for the early diagnosis of early brain histopathological changes and the prediction of neurodegenerative events in a full-term neonatal hypoxic-ischemic brain injury (HIBD) rat model.

Methods

The HIBD model was generated in postnatal day 7 Sprague-Dawley rats to assess the changes in DK and DT parameters in 10 specific brain structural regions involving the gray matter, white matter, and limbic system during acute (12 h) and subacute (3 d and 5 d) phases after hypoxic ischemia (HI), which were validated against histology. Sensory and cognitive parameters were assessed by the open field, novel object recognition, elevated plus maze, and CatWalk tests.

Results

Repeated-measures ANOVA revealed that specific brain structures showed similar trends to the lesion, and the temporal pattern of MK was substantially more varied than DT parameters, particularly in the deep gray matter. The change rate of MK in the acute phase (12 h) was significantly higher than that of DT parameters. We noted a delayed pseudo-normalization for MK. Additionally, MD, AD, and RD showed more pronounced differences between males and females after HI compared to MK, which was confirmed in behavioral tests. HI females exhibited anxiolytic hyperactivity-like baseline behavior, while the memory ability of HI males was affected in the novel object recognition test. CatWalk assessments revealed chronic deficits in limb gait parameters, particularly the left front paw and right hind paw, as well as poorer performance in HI males than HI females.

Conclusions

Our results suggested that DK and DT parameters were complementary in the immature brain and provided great value in assessing early tissue microstructural changes and predicting long-term neurobehavioral deficits, highlighting their ability to detect both acute and long-term changes. Thus, the various diffusion coefficient parameters estimated by the DKI model are powerful tools for early HIBD diagnosis and prognosis assessment, thus providing an experimental and theoretical basis for clinical treatment.

Brain microstructural changes in essential tremor patients and correlations with clinical characteristics: a diffusion kurtosis imaging study

OBJECTIVE

Essential tremor (ET) is the second most common movement disorder; however, the pathophysiological mechanism of ET is unclear. We aimed to investigate the microstructural degeneration of gray matter (GM) and white matter (WM) and their correlations with cognition and tremor in patients with ET.

METHODS

The participants were 63 patients with ET and 63 matched healthy controls (HCs) who underwent 3D-T1 weighted and diffusion kurtosis images (DKI). Microstructural degeneration was measured using high-level diffusion parameters derived from DKI. A voxel-wise analysis of the means of the GM-based spatial statistics and tract-based spatial statistics were conducted to assess differences in diffusion parameters between the ET and HC groups. The volume differences between the two groups were also assessed, and tremor severity and multi-domain cognitive performance were evaluated. Finally, the relationship between microstructural degeneration and clinical characteristics were assessed.

RESULTS

The ET group had significantly lower mean kurtosis of the temporal, parietal, and occipital lobes and the cerebellum and lower radial kurtosis in several tracts. These microstructural changes in GM and WM were correlated with tremor and cognitive scores. However, no significant difference in volume was found between the groups.

CONCLUSION

Our findings suggest that ET entails extensive GM and WM microstructural alterations, which support the neurodegenerative hypothesis of ET. Our study contributes to a better understanding of the mechanisms underlying tremor and cognitive impairment in ET.

Functional and structural alterations as diagnostic imaging markers for depression in de novo Parkinson's disease

Background

Depression in Parkinson's disease (PD) is identified and diagnosed with behavioral observations and neuropsychological measurements. Due to the large overlaps of depression and PD symptoms in clinical manifestations, it is challenging for neurologists to distinguish and diagnose depression in PD (DPD) in the early clinical stage of PD. The advancement in magnetic resonance imaging (MRI) technology provides potential clinical utility in the diagnosis of DPD. This study aimed to explore the alterations of functional and structural MRI in DPD to produce neuroimaging markers in discriminating DPD from non-depressed PD (NDPD) and healthy controls (HC).

Methods

We recruited 20 DPD, 37 NDPD, and 41 HC matched in age, gender, and education years. The patients' diagnosis with PD was de novo. The differences in regional homogeneity (ReHo), voxel-wise degree centrality (DC), cortical thickness, cortical gray matter (GM) volumes, and subcortical GM volumes among these groups were detected, and the relationship between altered indicators and depression was analyzed. Moreover, the receiver operating characteristic (ROC) analysis was performed to assess the diagnostic efficacy of altered indicators for DPD.

Results

Compared to NDPD and HC, DPD showed significantly increased ReHo in left dorsolateral superior frontal gyrus (DSFG) and DC in left inferior temporal gyrus (ITG), and decreased GM volumes in left temporal lobe and right Amygdala. Among these altered indicators, ReHo value in left DSFG and DC values in left ITG and left DSFG were significantly correlated with the severity of depression in PD patients. Comparing DPD and NDPD, the ROC analysis revealed a better area under the curve value for the combination of ReHo value in left DSFG and DC value in left ITG, followed by each independent indicator. However, the difference is not statistically significant.

Conclusion

This study demonstrates that both functional and structural impairments are present in DPD. Among them, ReHo value of left DSFG and DC value of left ITG are equally well suited for the diagnosis and differential diagnosis of DPD, with a combination of them being slightly preferable. The multimodal MRI technique represents a promising approach for the classification of subjects with PD.

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.

Nigral Iron Deposition Influences Disease Severity by Modulating the Effect of Parkinson's Disease on Brain Networks

BACKGROUND

In Parkinson's disease (PD), excessive iron deposition in the substantia nigra may exacerbate α-synuclein aggregation, facilitating the degeneration of dopaminergic neurons and their neural projection.

OBJECTIVE

To investigate the interaction effect between nigral iron deposition and PD status on brain networks.

METHODS

Eighty-five PD patients and 140 normal controls (NC) were included. Network function and nigral iron were measured using multi-modality magnetic resonance imaging. According to the median of nigral magnetic susceptibility of NC (0.095 ppm), PD and NC were respectively divided into high and low nigral iron group. The main and interaction effects were investigated by mixed effect analysis.

RESULTS

The main effect of disease was observed in basal ganglia network (BGN) and visual network (VN). The interaction effect between nigral iron and PD status was observed in left inferior frontal gyrus and left insular lobe in BGN, as well as right middle occipital gyrus, right superior temporal gyrus, and bilateral cuneus in VN. Furthermore, multiple mediation analysis revealed that the functional connectivity of interaction effect clusters in BGN and medial VN partially mediated the relationship between nigral iron and Unified Parkinson's Disease Rating Scale II score.

CONCLUSION

Our study demonstrates an interaction of nigral iron deposition and PD status on brain networks, that is, nigral iron deposition is associated with the change of brain network configuration exclusively when in PD. We identified a potential causal mediation pathway for iron to affect disease severity that was mediated by both BGN dysfunction and VN hyperfunction in PD.

Neurodegeneration of the Globus Pallidus Internus as a Neural Correlate to Dopa-Response in Freezing of Gait

BACKGROUND

Background: Parkinson's disease (PD) patients who develop freezing of gait (FOG) have reduced mobility and independence. While some patients experience improvement in their FOG symptoms with dopaminergic therapies, a subset of patients have little to no response. To date, it is unknown what changes in brain structure underlie dopa-response and whether this can be measured using neuroimaging approaches.

OBJECTIVE

We tested the hypothesis that structural integrity of brain regions (subthalamic nucleus and globus pallidus internus, GPi) which link basal ganglia to the mesencephalic locomotor region (MLR), a region involved in automatic gait, would be associated with FOG response to dopaminergic therapy.

METHODS

In this observational study, thirty-six participants with PD and definite FOG were recruited to undergo diffusion kurtosis imaging (DKI) and multiple assessments of dopa responsiveness (UPDRS scores, gait times ON versus OFF medication).

RESULTS

The right GPi in participants with dopa-unresponsive FOG showed reduced fractional anisotropy, mean kurtosis (MK), and increased radial diffusivity relative to those with dopa-responsive FOG. Furthermore, using probabilistic tractography, we observed reduced MK and increased mean diffusivity along the right GPi-MLR tract in dopa-unresponsive FOG. MK in the right GPi was associated with a subjective dopa-response for FOG (r = -0.360, df = 30, p = 0.043) but not overall motor dopa-response.

CONCLUSION

These results support structural integrity of the GPi as a correlate to dopa-response in FOG. Additionally, this study suggests DKI metrics may be a sensitive biomarker for clinical studies targeting dopaminergic circuitry and improvements in FOG behavior.