Regional homogeneity analysis of major Parkinson’s disease subtypes based on functional magnetic resonance imaging

Multimodal data fusion reveals functional and neurochemical correlates of Parkinson's disease

BACKGROUND

Neurotransmitter deficits and spatial associations among neurotransmitter distribution, brain activity, and clinical features in Parkinson's disease (PD) remain unclear. Better understanding of neurotransmitter impairments in PD may provide potential therapeutic targets. Therefore, we aimed to investigate the spatial relationship between PD-related patterns and neurotransmitter deficits.

METHODS

We included 59 patients with PD and 41 age- and sex-matched healthy controls (HCs). The voxel-wise mean amplitude of the low-frequency fluctuation (mALFF) was calculated and compared between the two groups. The JuSpace toolbox was used to test whether spatial patterns of mALFF alterations in patients with PD were associated with specific neurotransmitter receptor/transporter densities.

RESULTS

Compared to HCs, patients with PD showed reduced mALFF in the sensorimotor- and visual-related regions. In addition, mALFF alteration patterns were significantly associated with the spatial distribution of the serotonergic, dopaminergic, noradrenergic, glutamatergic, cannabinoid, and acetylcholinergic neurotransmitter systems (p < 0.05, false discovery rate-corrected).

CONCLUSIONS

Our results revealed abnormal brain activity patterns and specific neurotransmitter deficits in patients with PD, which may provide new insights into the mechanisms and potential targets for pharmacotherapy.

Structural and Functional Alterations of Motor-Thalamus in Different Motor Subtype of Parkinson's Disease: An Individual Study

RATIONALE AND OBJECTIVES

This study aimed to investigate the structural and functional alterations occurring within bilateral premotor thalamus (mPMtha) in motor subtypes of Parkinson's disease (PD).

MATERIALS AND METHODS

Sixty-one individuals with instability and gait difficulty (PIGD) subtype, 60 individuals with tremor-dominant (TD) subtype and 66 healthy controls (HCs) participated in the study. All participants underwent resting-state functional magnetic resonance imaging (rs-fMRI) and 3D T1-weighted (3DT1) scans. Functional connectivity (FC) analysis and Voxel-based morphometry (VBM) analysis were performed to evaluate the function and volume of mPMtha. Additionally, correlations between motor performance and FC values, volumes were examined separately. Support vector machine (SVM) model based on FC values and thalamic volumes was conducted to assist in the clinical diagnosis of PD motor subtype.

RESULTS

Compared to HCs and PIGD, TD subtype showed increased FC between the bilateral mPMtha and left middle occipital gyrus, left inferior parietal lobule (IPL). While PIGD subtype demonstrated decreased FC between right mPMtha and precentral gyrus (PreCG), supramarginal, IPL and superior parietal lobule. FC of bilateral mPMtha with the identified regions were significantly correlated with motor performance scores in PD patients. The SVM classification based on FC values demonstrated a high level of efficiency (AUC=0.874). The volumes of the bilateral mPMtha were indifferent among three groups.

CONCLUSION

We noted distinct FC alterations of mPMtha in TD and PIGD subtypes, and these changes were correlated with motor performance. Furthermore, the machine learning based on statistically significant FC might be served as an alternative approach for automatically classifying PD motor subtypes individually.

Functional and structural gradients reveal atypical hierarchical organization of Parkinson's disease

Parkinson's disease (PD) patients exhibit deficits in primary sensorimotor and higher-order executive functions. The gradient reflects the functional spectrum in sensorimotor-associated areas of the brain. We aimed to determine whether the gradient is disrupted in PD patients and how this disruption is associated with treatment outcome. Seventy-six patients (mean age, 59.2 ± 12.4 years [standard deviation], 44 women) and 34 controls participants (mean age, 58.1 ± 10.0 years [standard deviation], 19 women) were evaluated. We explored functional and structural gradients in PD patients and control participants. Patients were followed during 2 weeks of multidisciplinary intensive rehabilitation therapy (MIRT). The Unified Parkinson's Disease Rating Scale Part III (UPDRS-III) was administered to patients before and after treatment. We investigated PD-related alterations in the principal functional and structural gradients. We further used a support vector machine (SVM) and correlation analysis to assess the classification ability and treatment outcomes related to PD gradient alterations, respectively. The gradients showed significant differences between patients and control participants, mainly in somatosensory and visual networks involved in primary function, and higher-level association networks (dorsal attentional network (DAN) and default mode network (DMN)) related to motor control and execution. On the basis of the combined functional and structural gradient features of these networks, the SVM achieved an accuracy of 91.2% in discriminating patients from control participants. Treatment reduced the gradient difference. The altered gradient exhibited a significant correlation with motor improvement and was mainly distributed across the visual network, DAN and DMN. This study revealed damage to gradients in the brain characterized by sensorimotor and executive control deficits in PD patients. The application of gradient features to neurological disorders could lead to the development of potential diagnostic and treatment markers for PD.

Distinct changes in global brain synchronization in different motor subtypes of Parkinson's disease

This study investigated alterations in degree centrality (DC) in different motor subtypes of Parkinson's disease (PD) and analyzed its clinical significance during disease occurrence. A total of 146 subjects were recruited in the study, including 90 patients with PD [51 and 39 with tremor dominant (TD) and akinetic-rigid dominant (ARD) disease, respectively] and 56 healthy controls (HCs). The resting-state functional magnetic resonance imaging data of all the subjects were obtained by 3.0 T magnetic resonance scans. The DC values, an indicator of whole brain synchronization, were calculated and compared among the TD, ARD, and HC groups. Disparities in DC values among the three groups were evaluated by analysis of variance and post hoc two-sample t-tests. Correlation between brain regions with DC differences and clinical variables were performed using partial correlation analysis after controlling for age, gender, and disease duration. Compared to the HCs, both TD and ARD groups demonstrated increased DC values bilaterally in the cerebellum; DC values were decreased in the left putamen and paracentral lobule in the TD group and in the left anterior cingulate gyrus and right supplementary motor area in the ARD group. Compared to the ARD group, the TD group showed decreased DC values in bilateral cerebellar hemispheres and increased DC values in the left anterior cingulate gyrus and right supplementary motor area. The DC of the whole brain showed inconsistencies and shared neural bases among patients with the two subtypes of PD. The differences between brain regions with abnormal DC values may be closely related to different clinical presentations of the two motor subtypes. Our findings provide new insights into the clinical heterogeneity of PD with respect to different motor subtypes.

Structural and functional differences of the thalamus between drug-naïve Parkinson's disease motor subtypes

Objective

The thalamus is an integrative hub of motor circuits in Parkinson's disease (PD). This study aimed to investigate the alterations of structure and functional connectivity (FC) of the thalamic subregions in the tremor-dominant (TD) subtype and the postural instability and gait difficulty (PIGD) subtype in PD.

Methods

A total of 59 drug-naïve patients (24 TD and 35 PIGD) and 37 healthy controls were recruited. The volumes of the thalamus and the thalamic subregions were calculated using FreeSurfer. Functional connectivity (FC) analysis of the resting-state functional MRI (rsfMRI) was conducted on the thalamic subregions. Finally, the altered structure and FC were used for correlation analysis with clinical motor scores and for further motor subtypes differentiation.

Results

The volumes of the left posterior parietal thalamus (PPtha) in TD patients were significantly lower than those of PIGD patients. Compared with PIGD patients, TD patients exhibited higher FC between the thalamic subregions, the left middle temporal gyrus (MTG), the right dorsolateral superior frontal gyrus (SFGdl), the left middle occipital gyrus (MOG), and the right superior temporal gyrus (STG). Compared with HCs, TD patients showed higher FC between the thalamic subregions and the right SFGdl, as well as the left MOG. Compared with HCs, PIGD patients showed lower FC between the thalamic subregions and the left MTG. In addition, the altered FC was closely related to clinical symptoms and performed high-discriminative power in differentiating the motor subtypes.

Conclusion

Increased FC between the thalamic subregions and the sensory cortices in TD patients may indicate a better compensatory capacity for impairment of sensory information integration than that in PIGD patients. The altered FC between the thalamus and the MTG was a potential biomarker for the distinction of the PD motor subtypes.

BLENDS: Augmentation of Functional Magnetic Resonance Images for Machine Learning Using Anatomically Constrained Warping

Introduction: Data augmentation improves the accuracy of deep learning models when training data are scarce by synthesizing additional samples. This work addresses the lack of validated augmentation methods specific for synthesizing anatomically realistic four-dimensional (4D) (three-dimensional [3D] + time) images for neuroimaging, such as functional magnetic resonance imaging (fMRI), by proposing a new augmentation method. Methods: The proposed method, Brain Library Enrichment through Nonlinear Deformation Synthesis (BLENDS), generates new nonlinear warp fields by combining intersubject coregistration maps, computed using symmetric normalization, through spatial blending. These new warp fields can be applied to existing 4D fMRI to create new augmented images. BLENDS was tested on two neuroimaging problems using de-identified data sets: (1) the prediction of antidepressant response from task-based fMRI (original data set n = 163), and (2) the prediction of Parkinson's disease (PD) symptom trajectory from baseline resting-state fMRI regional homogeneity (original data set n = 43). Results: BLENDS readily generates hundreds of new fMRI from existing images, with unique anatomical variations from the source images, that significantly improve prediction performance. For antidepressant response prediction, augmenting each original image once (2 × the original training data) significantly increased prediction R2 from 0.055 to 0.098 (p < 1 e - 6 ), whereas at 10 × augmentation R2 increased to 0.103. For the prediction of PD trajectory, 10 × augmentation R2 increased from -0.044 to 0.472 (p < 1 e - 6 ). Conclusions: Augmentation of fMRI through nonlinear transformations with BLENDS significantly improved the performance of deep learning models on clinically relevant predictive tasks. This method will help neuroimaging researchers overcome data set size limitations and achieve more accurate predictive models.

Amplitude of low-frequency fluctuation-based regional radiomics similarity network: Biomarker for Parkinson's disease

Parkinson's disease (PD) is a highly heterogeneous disorder that is difficult to diagnose. Therefore, reliable biomarkers are needed. We implemented a method constructing a regional radiomics similarity network (R2SN) based on the amplitude of low-frequency fluctuation (ALFF). We classified patients with PD and healthy individuals by using a machine learning approach in accordance with the R2SN connectome. The ALFF-based R2SN exhibited great reproducibility with different brain atlases and datasets. Great classification performances were achieved both in primary (AUC = 0.85 ± 0.02 and accuracy = 0.81 ± 0.03) and independent external validation (AUC = 0.77 and accuracy = 0.70) datasets. The discriminative R2SN edges correlated with the clinical evaluations of patients with PD. The nodes of discriminative R2SN edges were primarily located in the default mode, sensorimotor, executive control, visual and frontoparietal network, cerebellum and striatum. These findings demonstrate that ALFF-based R2SN is a robust potential neuroimaging biomarker for PD and could provide new insights into connectome reorganization in PD.

Association between susceptibility value and cerebral blood flow in the bilateral putamen in patients undergoing hemodialysis

Hemodialysis (HD) is the most regularly applied replacement therapy for end-stage renal disease, but it may result in brain injuries. The correlation between cerebral blood flow (CBF) alteration and iron deposition has not been investigated in patients undergoing HD. Ferritin level may be a dominant factor in CBF and iron deposition change. We hypothesize that ferritin level might be the key mediator between iron deposition and CBF alteration. The correlation in the putamen was estimated between the susceptibility values and CBF in patients undergoing HD. Compared with healthy controls, patients showed more altered global susceptibility values and CBF. The susceptibility value was negatively correlated with CBF in the putamen in patients. Moreover, the susceptibility value was negatively correlated with ferritin level and positively correlated with serum iron level in the putamen of patients. CBF was positively correlated with ferritin level and negatively correlated with serum iron level in the putamen of patients. These findings indicate that iron dyshomeostasis and vascular damage might exist in the putamen in patients. The results revealed that iron dyshomeostasis and vascular damage in the putamen may be potential neural mechanisms for neurodegenerative processes in patients undergoing HD.

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.

Altered brain connectivity in hyperkinetic movement disorders: A review of resting-state fMRI

BACKGROUND

Hyperkinetic movement disorders (HMD) manifest as abnormal and uncontrollable movements. Despite reported involvement of several neural circuits, exact connectivity profiles remain elusive.

OBJECTIVES

Providing a comprehensive literature review of resting-state brain connectivity alterations using resting-state fMRI (rs-fMRI). We additionally discuss alterations from the perspective of brain networks, as well as correlations between connectivity and clinical measures.

METHODS

A systematic review was performed according to PRISMA guidelines and searching PubMed until October 2022. Rs-fMRI studies addressing ataxia, chorea, dystonia, myoclonus, tics, tremor, and functional movement disorders (FMD) were included. The standardized mean difference was used to summarize findings per region in the Automated Anatomical Labeling atlas for each phenotype. Furthermore, the activation likelihood estimation meta-analytic method was used to analyze convergence of significant between-group differences per phenotype. Finally, we conducted hierarchical cluster analysis to provide additional insights into commonalities and differences across HMD phenotypes.

RESULTS

Most articles concerned tremor (51), followed by dystonia (46), tics (19), chorea (12), myoclonus (11), FMD (11), and ataxia (8). Altered resting-state connectivity was found in several brain regions: in ataxia mainly cerebellar areas; for chorea, the caudate nucleus; for dystonia, sensorimotor and basal ganglia regions; for myoclonus, the thalamus and cingulate cortex; in tics, the basal ganglia, cerebellum, insula, and frontal cortex; for tremor, the cerebello-thalamo-cortical circuit; finally, in FMD, frontal, parietal, and cerebellar regions. Both decreased and increased connectivity were found for all HMD. Significant spatial convergence was found for dystonia, FMD, myoclonus, and tremor. Correlations between clinical measures and resting-state connectivity were frequently described.

CONCLUSION

Key brain regions contributing to functional connectivity changes across HMD often overlap. Possible increases and decreases of functional connections of a specific region emphasize that HMD should be viewed as a network disorder. Despite the complex interplay of physiological and methodological factors, this review serves to gain insight in brain connectivity profiles across HMD phenotypes.

Topological disruption of high-order functional networks in cognitively preserved Parkinson's disease

AIMS

This study aimed to characterize the topological alterations and classification performance of high-order functional connectivity (HOFC) networks in cognitively preserved patients with Parkinson's disease (PD), relative to low-order FC (LOFC) networks.

METHODS

The topological metrics of the constructed networks (LOFC and HOFC) obtained from fifty-one cognitively normal patients with PD and 60 matched healthy control subjects were analyzed. The discriminative abilities were evaluated using machine learning approach.

RESULTS

The HOFC networks in the PD group showed decreased segregation and integration. The normalized clustering coefficient and small-worldness in the HOFC networks were correlated to motor performance. The altered nodal centralities (distributed in the precuneus, putamen, lingual gyrus, supramarginal gyrus, motor area, postcentral gyrus and inferior occipital gyrus) and intermodular FC (frontoparietal and visual networks, sensorimotor and subcortical networks) were specific to HOFC networks. Several highly connected nodes (thalamus, paracentral lobule, calcarine fissure and precuneus) and improved classification performance were found based on HOFC profiles.

CONCLUSION

This study identified disrupted topology of functional interactions at a high level with extensive alterations in topological properties and improved differentiation ability in patients with PD prior to clinical symptoms of cognitive impairment, providing complementary insights into complex neurodegeneration in PD.

Cerebro-cerebellar motor networks in clinical subtypes of Parkinson’s disease

Parkinson’s disease (PD) patients can be classified in tremor-dominant (TD) and postural-instability-and-gait-disorder (PIGD) motor subtypes. PIGD represents a more aggressive form of the disease that TD patients have a potentiality of converting into. This study investigated functional alterations within the cerebro-cerebellar system in PD-TD and PD-PIGD patients using stepwise functional connectivity (SFC) analysis and identified neuroimaging features that predict TD to PIGD conversion. Thirty-two PD-TD, 26 PD-PIGD patients and 60 healthy controls performed clinical/cognitive evaluations and resting-state functional MRI (fMRI). Four-year clinical follow-up data were available for 28 PD-TD patients, who were classified in 10 converters (cTD-PD) and 18 non-converters (ncTD-PD) to PIGD. The cerebellar seed-region was identified using a fMRI motor task. SFC analysis, characterizing regions that connect brain areas to the cerebellar seed at different levels of link-step distances, evaluated similar and divergent alterations in PD-TD and PD-PIGD. The discriminatory power of clinical data and/or SFC in distinguishing cPD-TD from ncPD-TD patients was assessed using ROC curve analysis. Compared to PD-TD, PD-PIGD patients showed decreased SFC in temporal lobe and occipital lobes and increased SFC in cerebellar cortex and ponto-medullary junction. Considering the subtype-conversion analysis, cPD-TD patients were characterized by increased SFC in temporal and occipital lobes and in cerebellum and ponto-medullary junction relative to ncPD-TD group. Combining clinical and SFC data, ROC curves provided the highest classification power to identify conversion to PIGD. These findings provide novel insights into the pathophysiology underlying different PD motor phenotypes and a potential tool for early characterization of PD-TD patients at risk of conversion to PIGD.

Alterations of Regional Homogeneity in Parkinson’s Disease: A Resting-State Functional Magnetic Resonance Imaging (fMRI) Study

Objective

The objective of this study is to investigate the regional homogeneity (ReHo) of spontaneous brain activities in Parkinson’s disease (PD) patients.

Methods

In total, 20 PD patients and 20 matched normal controls (NCs) participants were recruited for this study. The regional homogeneity (ReHo) approach based on resting-state functional magnetic resonance imaging on a 3T MRI system was used to investigate local brain activity. We examined activity in two frequency bands, slow‐4 (0.027-0.073 Hz) and slow‐5 (0.010-0.027 Hz). Two-sample t-tests were used to determine the between-group differences in the ReHo data. Pearson correlation analysis was used to explore the relationships between the ReHo values and clinical indices in PD patients.

Results

Compared with NCs, PD patients showed decreased ReHo values in the right middle occipital gyrus, right cuneus, and left superior occipital gyrus, and increased ReHo values in the right middle frontal gyrus in slow‐4. PD patients showed decreased ReHo values in the right calcarine, left calcarine, and right precentral gyrus compared with NCs in slow‐5. Correlation analysis showed that disease duration was negatively correlated with ReHo values in the right precentral gyrus in PD patients.

Conclusions

These results indicate that several brain regions were altered in PD patients. The regions are associated with the visual network-related cortex, motor cortex, and default mode network. The findings provide new insights into the neuropathophysiology of PD.

Classification of Parkinson's disease using a region-of-interest- and resting-state functional magnetic resonance imaging-based radiomics approach

To investigate the value of combining amplitude of low-frequency fluctuations-based radiomics and the support vector machine classifier method in distinguishing patients with Parkinson's disease from healthy controls. A total of 123 patients with Parkinson's disease and 90 healthy controls from three centers with functional and structural MRI images were included in this study. We extracted radiomics features using the Brainnetome 246 atlas from the mean amplitude of low-frequency fluctuations maps. Two-sample t-tests and recursive feature elimination combined with support vector machine method were applied for feature selection and dimensionality reduction. We used support vector machine classifier to construct model and identify the discriminative features. The automated anatomical labeling 90 atlas and fivefold cross-validation were used to evaluate the robustness and generalization of the classifier. We found our model obtained a high classification performance with an accuracy of 78.07%, and AUC, sensitivity, and specificity of 0.8597, 78.80%, and 76.08%, respectively. We detected 7 discriminative brain subregions. The fivefold cross-validation and automated anatomical labeling 90 atlas also got high classification accuracy, and we found Brainnetome 246 atlas achieved a higher classification performance than the automated anatomical labeling 90 atlas both with tenfold and fivefold cross-validation. Our findings may help the early diagnosis of Parkinson's disease and provide support for research on Parkinson's disease mechanisms and clinical evaluation.

Parkinson's Disease Subtyping Using Clinical Features and Biomarkers: Literature Review and Preliminary Study of Subtype Clustering

The second most common progressive neurodegenerative disorder, Parkinson’s disease (PD), is characterized by a broad spectrum of symptoms that are associated with its progression. Several studies have attempted to classify PD according to its clinical manifestations and establish objective biomarkers for early diagnosis and for predicting the prognosis of the disease. Recent comprehensive research on the classification of PD using clinical phenotypes has included factors such as dominance, severity, and prognosis of motor and non-motor symptoms and biomarkers. Additionally, neuroimaging studies have attempted to reveal the pathological substrate for motor symptoms. Genetic and transcriptomic studies have contributed to our understanding of the underlying molecular pathogenic mechanisms and provided a basis for classifying PD. Moreover, an understanding of the heterogeneity of clinical manifestations in PD is required for a personalized medicine approach. Herein, we discuss the possible subtypes of PD based on clinical features, neuroimaging, and biomarkers for developing personalized medicine for PD. In addition, we conduct a preliminary clustering using gait features for subtyping PD. We believe that subtyping may facilitate the development of therapeutic strategies for PD.

Disrupted dynamic pattern of regional neural activity in early-stage cognitively normal Parkinson's disease

BACKGROUND

Neuroimaging studies on Parkinson's disease (PD) mainly focus on static neural activity. However, the dynamic pattern of regional brain activity in early-stage cognitively normal PD has rarely been elucidated.

PURPOSE

To identify altered dynamic amplitude of low-frequency fluctuation (dALFF) in PD before the onset of cognitive impairment and verify its differentiating ability between patients with PD and healthy controls (HC).

MATERIAL AND METHODS

dALFF and static ALFF (sALFF) derived from functional magnetic resonance imaging data of 51 patients with PD and 50 matched HCs were analyzed. The correlations between aberrant regions and clinical performance were investigated using Spearman correlation analysis. Multivariate pattern analysis was conducted to detect the differentiating ability of both ALFF features.

RESULTS

Compared with HCs, patients with PD demonstrated reduced dALFF variance in bilateral lingual gyrus, left middle occipital gyrus, left postcentral gyrus (PcG), and right supplementary motor area (SMA); and increased dALFF variability in bilateral parahippocampal gyrus. Besides overlapping with these distributions of altered dALFF, the aberrant regions of sALFF were more extensive with decreased sALFF in the right middle temporal gyrus and right PcG, and increased sALFF in the left inferior temporal gyrus and left thalamus were observed in patients with PD. dALFF values in right SMA and left PcG were correlated with UPDRS-III scores (ρ =  -0.29, P = 0.041; ρ =  -0.33, P = 0.018, respectively).

CONCLUSION

This study provides novel insights into the neural basis underlying PD as well as the potential role of dynamic neural activity in the diagnosis and prediction of the disease.

Correlation analysis between regional homogeneity and executive dysfunction in anti-N-methyl-D-aspartate receptor encephalitis patients

BACKGROUND AND PURPOSE

Anti-N-methyl-d-aspartate receptor (NMDAR) encephalitis is characterized by a range of cognitive impairments, especially in executive function. Our study aims to identify the abnormal regional homogeneity (ReHo) in anti-NMDAR encephalitis patients and its relationship with the executive function.

METHODS

Forty patients and 42 healthy volunteers undertook an Attention Network Test and a resting-state functional magnetic resonance imaging scan. ReHo analysis was performed to investigate the neuronal activity synchronization in all subjects. Based on ReHo analysis, a multivariate pattern analysis (MVPA) was carried out to identify the brain regions that differed the most between the two groups.

RESULTS

Compared to controls, the patients had higher executive control scores (p < 0.05). The patients presented reduced ReHo values in the bilateral posterior cerebellar lobe, anterior cerebellar lobe, midbrain, bilateral caudate nucleus, right superior frontal gyrus, right middle temporal gyrus, bilateral inferior parietal lobule and the left middle frontal gyrus. The ReHo values of the bilateral inferior parietal lobule in patients were found to be negatively associated with executive control scores. The classification of patients and controls using MVPA had an accuracy of 76.83%, a sensitivity of 82.50%, a specificity of 71.43% and the area under the curve was 0.83.

CONCLUSIONS

Our study provides evidence of abnormal cerebral function in anti-NMDAR encephalitis patients, which may contribute to unveiling the neuropathological mechanisms of anti-NMDAR encephalitis and their influences on executive dysfunction. The MVPA classifier, based on ReHo, is helpful in identifying anti-NMDAR encephalitis patients from healthy controls.

Differentiating Parkinson's disease motor subtypes: A radiomics analysis based on deep gray nuclear lesion and white matter

OBJECTIVE

To investigate the feasibility of radiomics analysis of brain MR images to differentiate Parkinson's disease motor subtypes.

METHODS

42 postural instability gait difficulty (PIGD) patients, 92 tremor-dominant (TD) patients and 96 healthy controls were included from the Parkinson's Progressive Marker Initiative public database. For each subject, 4850 radiomic features from 148 cortical and 14 subcortical brain regions were extracted. The variance threshold and the least absolute shrinkage and selection operator were used to select the optimal features. Classification models based on Support Vector Machine, Logistic Regrcession, and Multi-Layer Perceptron were constructed to assess the performance of optimal features in the discrimination of the two subtypes. Correlations between radiomic features and clinical scores of the two subtypes were estimated.

RESULTS

The Support Vector Machine demonstrated the best performance in discriminating between the two subtypes, and the mean area under the curve was 0.833 (specificity = 83.3%, sensitivity = 75.0%, and accuracy = 80.7%). For the postural instability gait difficulty patients, these optimal features in the hippocampal showed closed correlations with the Montreal Cognitive Assessment scores (P < 0.05).

CONCLUSION

The results of our study provide preliminary evidence that radiomics analysis of brain MR images could allow discrimination between patients with TD, PIGD and control subjects and has great potential value in the clinical practice.

Disrupted morphological grey matter networks in early-stage Parkinson's disease

While previous structural-covariance studies have an advanced understanding of brain alterations in Parkinson's disease (PD), brain–behavior relationships have not been examined at the individual level. This study investigated the topological organization of grey matter (GM) networks, their relation to disease severity, and their potential imaging diagnostic value in PD. Fifty-four early-stage PD patients and 54 healthy controls (HC) underwent structural T1-weighted magnetic resonance imaging. GM networks were constructed by estimating interregional similarity in the distributions of regional GM volume using the Kullback–Leibler divergence measure. Results were analyzed using graph theory and network-based statistics (NBS), and the relationship to disease severity was assessed. Exploratory support vector machine analyses were conducted to discriminate PD patients from HC and different motor subtypes. Compared with HC, GM networks in PD showed a higher clustering coefficient (P = 0.014) and local efficiency (P = 0.014). Locally, nodal centralities in PD were lower in postcentral gyrus and temporal-occipital regions, and higher in right superior frontal gyrus and left putamen. NBS analysis revealed decreased morphological connections in the sensorimotor and default mode networks and increased connections in the salience and frontoparietal networks in PD. Connection matrices and graph-based metrics allowed single-subject classification of PD and HC with significant accuracy of 73.1 and 72.7%, respectively, while graph-based metrics allowed single-subject classification of tremor-dominant and akinetic–rigid motor subtypes with significant accuracy of 67.0%. The topological organization of GM networks was disrupted in early-stage PD in a way that suggests greater segregation of information processing. There is potential for application to early imaging diagnosis.

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.

Brain activity alterations in patients with Parkinson's disease with cognitive impairment based on resting-state functional MRI

OBJECTIVE

This study aimed to investigate the differences in regional homogeneity (ReHo) values in patients with Parkinson's disease (PD) with cognitive impairment (PD-CI) and thus explore the neuropathological mechanism of PD-CI.

METHODS

Resting-state functional magnetic resonance imaging scans were obtained from 36 patients with PD and 20 healthy controls (HCs) in this study. The PD group comprised 20 patients with PD-CI and 16 patients with PD with normal cognitive function (PD-NC). The data were analyzed using ReHo analysis to observe the changes in brain activity in patients with PD-CI and PD-NC. Statistical comparison was performed using covariance analysis and post hoc t tests.

RESULTS

The patients in the PD-CI group were older than those in the PD-NC and HC groups. Compared with the HC group, the PD-CI group showed that the ReHo value decreased in the right supplementary motor area, left lingual gyrus, left thalamus, and left precuneus, but increased in the left fusiform gyrus. Compared with the HC group, the PD-NC group showed that the ReHo value decreased in the right cerebellum_6, but increased in the left inferior temporal gyrus, left orbital inferior frontal gyrus, and left precentral gyrus. Compared with the PD-NC group, the PD-CI group showed that the ReHo value decreased in the right precuneus, left triangular inferior frontal gyrus, left middle frontal gyrus, right opercular inferior frontal gyrus, left orbital inferior frontal gyrus, left supramarginal gyrus, left angular gyrus, left inferior temporal gyrus, and right cerebelum_7b, but increased in the left precentral gyrus and left fusiform gyrus.

CONCLUSIONS

Age was a risk factor for cognitive decline in patients with PD. The ReHo value in the default mode network (DMN) was closely related to PD cognitive function, and the DMN was affected before CI and continuously deteriorated with disease progression. The disorder of visual conduction pathway was involved in CI in patients with PD, but these patients could recruit cognitive resources by improving visual-spatial ability. The cognitive function in such patients was related to the dopaminergic, cholinergic, and noradrenergic systems. The information transmission efficiency of the cerebellum-thalamus-cortex loop was reduced and involved in the cognitive decline process in patients with PD.

A study on BOLD fMRI of the brain basic activities of MDD and the first-degree relatives

Introduction: The present study aims to explore the characteristics and differences of the ReHo, ALFF and fALFF of brain in the resting state of depression and first-degree relatives, in order to identify candidate central prodromal biomarkers of depression.Method: Three groups of medication-free patients (39-59 years old) was involved in this study, including the patients with major depression disorder (MDD group, n = 15), healthy volunteers with first-degree relatives with MDD (first-degree relatives group, n = 15), healthy volunteers with no personal or family history of MDD (the control group [HC], n = 15). Participants underwent functional MRI while staying in a resting state after a conventional MRI scanning on a clinical 3 T system(Siemens Skyra, Germany).Results: The ReHo, ALFF and fALFF values are different in brain of MDD, first-degree relatives, and HC (p<.05). MDD patients exhibited abnormal spontaneous activity in multiple brain regions which are closely related to emotion regulation and perception. The present findings provide further insight into the pathological mechanisms underlying MDD.Conclusion: With the widespread abnormal values of brain in MDD and first-degree relatives measured, we can get a hypothesis that these abnormalities may be associated with cognitive network disorders and emotional distress in MDD.Key pointsThe fMRI could increase the early validity of MDD as a new diagnostic and disease-monitoring tool.Monitoring ReHo, ALFF, fALFF values using fMRI can provide insight into the presence and evolution of MDD disease and permit objective evaluation of brain abnormalities.It appears that ReHo, ALFF, fALFF could be used as markers for monitoring disease progression and treatment effects in MDD patients in the future.

The Relationship between Side of Onset and Cerebral Regional Homogeneity in Parkinson's Disease: A Resting-State fMRI Study

OBJECTIVE

Motor symptoms are usually asymmetric in Parkinson's disease (PD), and asymmetry in PD may involve widespread brain areas. We sought to evaluate the effect of asymmetry on the whole brain spontaneous activity using the measure regional homogeneity (ReHo) through resting-state functional MRI.

METHODS

We recruited 30 PD patients with left onset (LPD), 27 with right side (RPD), and 32 controls with satisfactory data. Their demographic, clinical, and neuropsychological information were obtained. Resting-state functional MRI was performed, and ReHo was used to determine the brain activity. ANCOVA was utilized to analyze between-group differences in ReHo and the associations between abnormal ReHo, and various clinical and neuropsychological variables were explored by Spearman's correlation.

RESULTS

LPD patients had higher ReHo in the right temporal pole than the controls. RPD patients had increased ReHo in the right temporal pole and decreased ReHo in the primary motor cortex and premotor area, compared with the controls. Directly comparing LPD and RPD patients did not show a significant difference in ReHo. ReHo of the right temporal pole was significantly correlated with depression and anxiety in RPD patients.

CONCLUSIONS

Both LPD and RPD have increased brain activity synchronization in the right temporal pole, and only RPD has decreased brain activity synchronization in the right frontal motor areas. The changed brain activity in the right temporal pole may play a compensatory role for depression and anxiety in PD, and the altered cerebral function in the right frontal motor area in RPD may represent the reorganization of the motor system in RPD.

ALFF and ReHo Mapping Reveals Different Functional Patterns in Early- and Late-Onset Parkinson's Disease

Heterogeneity between late-onset Parkinson's disease (LOPD) and early-onset Parkinson's disease (EOPD) is mainly reflected in the following aspects including genetics, disease progression, drug response, clinical manifestation, and neuropathological change. Although many studies have investigated these differences in relation to clinical significance, the functional processing circuits and underlying neural mechanisms have not been entirely understood. In this study, regional homogeneity (ReHo) and amplitude of low-frequency fluctuation (ALFF) maps were used to explore different spontaneous brain activity patterns in EOPD and LOPD patients. Abnormal synchronizations were found in the motor and emotional circuits of the EOPD group, as well as in the motor, emotional, and visual circuits of the LOPD group. EOPD patients showed functional activity change in the visual, emotional and motor circuits, and LOPD patients only showed increased functional activity in the emotional circuits. In summary, the desynchronization process in the LOPD group was relatively strengthened, and the brain areas with changed functional activity in the EOPD group were relatively widespread. The results might point out different impairments in the synchronization and functional activity for EOPD and LOPD patients.

Evaluation of the brain functional activities in rats various location-endometriosis pain model

Background

Endometriosis (EM) is a common gynecological disease in women of reproductive age. These patients in approximately 80% suffer the various degree pain. This study will investigate synergistically the mechanism of the higher-position central sensitization and offer a pre-clinical experiment evidence for treatment of various location-EM patients with pain.

Methods

Twenty Sprague-Dawley rats were induced three types EM including abdominal EM (n=5), gastrocnemius EM (n=5) and ovary EM group (n=5) and one sham control group (n=5). All groups were measured the pain sensitization by hotplate test, then scanned by the functional magnetic resonance imaging (fMRI). The resting-state fMRI (rs-fMRI) date was analyzed using regional homogeneity (ReHo) approach to find out the abnormal functional activity brain regions. Nissl staining method observed the state of neurons in aberrant ReHo signal brain regions.

Results

Rats with EM pain sensitization were increased in abdominal EM and gastrocnemius EM than ovary EM group and sham control. The ReHo value is decreased in gastrocnemius EM in right thalamus and left olfactory tubercle compared with other three groups. The number of neurons was decreased; cavitation around nucleus, and pyknotic homogenous nuclei. Nissl bodies were stained deeply, and the shape was irregular in gastrocnemius EM by Nissl staining in right thalamus. In left olfactory tubercle, there was no significant difference in 4 groups.

Conclusions

The thalamus may be the potential key brain region for the central sensitization mechanism of various location-EM pain. The oxidative activation may be weakened in thalamus in gastrocnemius EM group with more severe pain. This finding could lend support for future research on the imageology and pathology of various location-EM pain.