Parkinson's disease and local atrophy in subcortical nuclei: insight from shape analysis

Fine hippocampal morphology analysis with a multi-dataset cross-sectional study on 2911 subjects

CA1 subfield and subiculum of the hippocampus contain a series of dentate bulges, which are also called hippocampus dentation (HD). There have been several studies demonstrating an association between HD and brain disorders. Such as the number of hippocampal dentation correlates with temporal lobe epilepsy. And epileptic hippocampus have a lower number of dentation compared to contralateral hippocampus. However, most studies rely on subjective assessment by manual searching and counting in HD areas, which is time-consuming and labor-intensive to process large amounts of samples. And to date, only one objective method for quantifying HD has been proposed. Therefore, to fill this gap, we developed an automated and objective method to quantify HD and explore its relationship with neurodegenerative diseases. In this work, we performed a fine-scale morphological characterization of HD in 2911 subjects from four different cohorts of ADNI, PPMI, HCP, and IXI to quantify and explore differences between them in MR T1w images. The results showed that the degree of right hippocampal dentation are lower in patients with Alzheimer's disease than samples in mild cognitive impairment or cognitively normal, whereas this change is not significant in Parkinson's disease progression. The innovation of this paper that we propose a quantitative, robust, and fully automated method. These methodological innovation and corresponding results delineated above constitute the significance and novelty of our study. What's more, the proposed method breaks through the limitations of manual labeling and is the first to quantitatively measure and compare HD in four different brain populations including thousands of subjects. These findings revealed new morphological patterns in the hippocampal dentation, which can help with subsequent fine-scale hippocampal morphology research.

The longitudinal volumetric and shape changes of subcortical nuclei in Parkinson's disease

Brain structural changes in Parkinson's disease (PD) are progressive throughout the disease course. Changes in surface morphology with disease progression remain unclear. This study aimed to assess the volumetric and shape changes of the subcortical nuclei during disease progression and explore their association with clinical symptoms. Thirty-four patients and 32 healthy controls were enrolled. The global volume and shape of the subcortical nuclei were compared between patients and controls at baseline. The volume and shape changes of the subcortical nuclei were also explored between baseline and 2 years of follow-up. Association analysis was performed between the volume of subcortical structures and clinical symptoms. In patients with PD, there were significantly atrophied areas in the left pallidum and left putamen, while in healthy controls, the right putamen was dilated compared to baseline. The local morphology of the left pallidum was correlated with Mini Mental State Examination scores. The left putamen shape variation was negatively correlated with changes in Unified Parkinson's Disease Rating Scale PART III scores. Local morphological atrophy of the putamen and pallidum is an important pathophysiological change in the development of PD, and is associated with motor symptoms and cognitive status in patients with PD.

Structural neuroimaging markers of normal pressure hydrocephalus versus Alzheimer's dementia and Parkinson's disease, and hydrocephalus versus atrophy in chronic TBI-a narrative review

Introduction

Normal Pressure Hydrocephalus (NPH) is a prominent type of reversible dementia that may be treated with shunt surgery, and it is crucial to differentiate it from irreversible degeneration caused by its symptomatic mimics like Alzheimer's Dementia (AD) and Parkinson's Disease (PD). Similarly, it is important to distinguish between (normal pressure) hydrocephalus and irreversible atrophy/degeneration which are among the chronic effects of Traumatic Brain Injury (cTBI), as the former may be reversed through shunt placement. The purpose of this review is to elucidate the structural imaging markers which may be foundational to the development of accurate, noninvasive, and accessible solutions to this problem.

Methods

By searching the PubMed database for keywords related to NPH, AD, PD, and cTBI, we reviewed studies that examined the (1) distinct neuroanatomical markers of degeneration in NPH versus AD and PD, and atrophy versus hydrocephalus in cTBI and (2) computational methods for their (semi-) automatic assessment on Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) scans.

Results

Structural markers of NPH and those that can distinguish it from AD have been well studied, but only a few studies have explored its structural distinction between PD. The structural implications of cTBI over time have been studied. But neuroanatomical markers that can predict shunt response in patients with either symptomatic idiopathic NPH or post-traumatic hydrocephalus have not been reliably established. MRI-based markers dominate this field of investigation as compared to CT, which is also reflected in the disproportionate number of MRI-based computational methods for their automatic assessment.

Conclusion

Along with an up-to-date literature review on the structural neurodegeneration due to NPH versus AD/PD, and hydrocephalus versus atrophy in cTBI, this article sheds light on the potential of structural imaging markers as (differential) diagnostic aids for the timely recognition of patients with reversible (normal pressure) hydrocephalus, and opportunities to develop computational tools for their objective assessment.

Evaluation of putamen area and cerebral peduncle with surrounding cistern in patients with Parkinson's disease: is there a difference from controls in cranial MRI?

OBJECTIVES

Nigrostriatal dopaminergic neuron loss is essential in pathogenesis of Parkinson's disease (PD). The purpose of this study was to evaluate nigrostriatal structures including the putamen, cerebral peduncle, widths of interpeduncular cistern, and ambient cistern around the midbrain with conventional cranial magnetic resonance images (MRI) in patients with PD.

METHODS

The MRI of 56 subjects was included, which was selected from the radiological data system for this retrospective study. The 29 patients with idiopathic PD were included and their disease duration, Hoehn&Yahr stage, and Levodopa equivalent dose (LED) were recorded. The 27 controls had a normal neurologic examination and cranial MRI. All subjects in the patient and control groups had right-hand dominance. Putamen and cerebral peduncle areas and widths of interpeduncular and ambient cisterns were measured in T2 sequences of MRI. Further statistical analysis was applied to exclude gender and age effect on areas.

RESULTS

The areas of putamen and cerebral peduncles were significantly reduced in patients with PD compared to the control bilaterally (p < 0.001). Enlargement of interpeduncular and ambient cisterns in patients was higher than in controls, and it was significant (p < 0.001). A correlation was not observed between measurement results and clinical characteristics of patients with PD. Only the cerebral peduncle area/ambient cistern width ratio was significantly correlated with disease duration positively (right r = 0.46 p = 0.012, left r = 0.389 p = 0.037).

CONCLUSION

Clinicians should be careful with conventional MRIs of patients with idiopathic PD in practice. It may be different from controls without any neurological disorder, particularly putamen, cerebral peduncles, interpeduncular, and ambient cisterns.

Multi-parametric radiomics of conventional T1 weighted and susceptibility-weighted imaging for differential diagnosis of idiopathic Parkinson's disease and multiple system atrophy

OBJECTIVES

This study aims to investigate the potential of radiomics with multiple parameters from conventional T1 weighted imaging (T1WI) and susceptibility weighted imaging (SWI) in distinguishing between idiopathic Parkinson's disease (PD) and multiple system atrophy (MSA).

METHODS

A total of 201 participants, including 57 patients with PD, 74 with MSA, and 70 healthy control (HCs) individuals, underwent T1WI and SWI scans. From the 12 subcortical nuclei (e.g. red nucleus, substantia nigra, subthalamic nucleus, putamen, globus pallidus, and caudate nucleus), 2640 radiomic features were extracted from both T1WI and SWI scans. Three classification models - logistic regression (LR), support vector machine (SVM), and light gradient boosting machine (LGBM) - were used to distinguish between MSA and PD, as well as among MSA, PD, and HC. These classifications were based on features extracted from T1WI, SWI, and a combination of T1WI and SWI. Five-fold cross-validation was used to evaluate the performance of the models with metrics such as sensitivity, specificity, accuracy, and area under the receiver operating curve (AUC). During each fold, the ANOVA and least absolute shrinkage and selection operator (LASSO) methods were used to identify the most relevant subset of features for the model training process.

RESULTS

The LGBM model trained by the features combination of T1WI and SWI exhibited the most outstanding differential performance in both the three-class classification task of MSA vs. PD vs. HC and the binary classification task of MSA vs. PD, with an accuracy of 0.814 and 0.854, and an AUC of 0.904 and 0.881, respectively. The texture-based differences (GLCM) of the SN and the shape-based differences of the GP were highly effective in discriminating between the three classes and two classes, respectively.

CONCLUSIONS

Radiomic features combining T1WI and SWI can achieve a satisfactory differential diagnosis for PD, MSA, and HC groups, as well as for PD and MSA groups, thus providing a useful tool for clinical decision-making based on routine MRI sequences.

Striatal and thalamic automatic segmentation, morphology, and clinical correlates in Parkinsonism: Parkinson's disease, multiple system atrophy and progressive supranuclear palsy

Parkinson's disease (PD), multisystem atrophy (MSA), and progressive supranuclear palsy (PSP) present similarly with bradykinesia, tremor, rigidity, and cognitive impairments. Neuroimaging studies have found differential changes in the nigrostriatal pathway in these disorders, however whether the volume and shape of specific regions within this pathway can distinguish between atypical Parkinsonian disorders remains to be determined. This paper investigates striatal and thalamic volume and morphology as distinguishing biomarkers, and their relationship to neuropsychiatric symptoms. Automatic segmentation to calculate volume and shape analysis of the caudate nucleus, putamen, and thalamus were performed in 18 PD patients, 12 MSA, 15 PSP, and 20 healthy controls, then correlated with clinical measures. PSP bilateral thalami and right putamen were significantly smaller than controls, but not MSA or PD. The left caudate and putamen significantly correlated with the Neuropsychiatric Inventory total score. Bilateral thalamus, caudate, and left putamen had significantly different morphology between groups, driven by differences between PSP and healthy controls. This study demonstrated that PSP patient striatal and thalamic volume and shape are significantly different when compared with controls. Parkinsonian disorders could not be differentiated on volumetry or morphology, however there are trends for volumetric and morphological changes associated with PD, MSA, and PSP.

Morphological changes in Parkinson's disease based on magnetic resonance imaging: A mini-review of subcortical structures segmentation and shape analysis

Parkinson's disease (PD) is a neurodegenerative disorder caused by the loss of dopaminergic neurons in the substantia nigra, resulting in clinical symptoms, including bradykinesia, resting tremor, rigidity, and postural instability. The pathophysiological changes in PD are inextricably linked to the subcortical structures. Shape analysis is a method for quantifying the volume or surface morphology of structures using magnetic resonance imaging. In this review, we discuss the recent advances in morphological analysis techniques for studying the subcortical structures in PD in vivo. This approach includes available pipelines for volume and shape analysis, focusing on the morphological features of volume and surface area.

Local striatal volume and motor reserve in drug-naïve Parkinson's disease

Motor reserve (MR) may explain why individuals with similar pathological changes show marked differences in motor deficits in Parkinson's disease (PD). In this study, we investigated whether estimated individual MR was linked to local striatal volume (LSV) in PD. We analyzed data obtained from 333 patients with drug naïve PD who underwent dopamine transporter scans and high-resolution 3-tesla T1-weighted structural magnetic resonance images. Using a residual model, we estimated individual MRs on the basis of initial UPDRS-III score and striatal dopamine depletion. We performed a correlation analysis between MR estimates and LSV. Furthermore, we assessed the effect of LSV, which is correlated with MR estimates, on the longitudinal increase in the levodopa-equivalent dose (LED) during the 4-year follow-up period using a linear mixed model. After controlling for intracranial volume, there was a significant positive correlation between LSV and MR estimates in the bilateral caudate, anterior putamen, and ventro-posterior putamen. The linear mixed model showed that the large local volume of anterior and ventro-posterior putamen was associated with the low requirement of LED initially and accelerated LED increment thereafter. The present study demonstrated that LSV is crucial to MR in early-stage PD, suggesting LSV as a neural correlate of MR in PD.

Alteration of brain nuclei in obese children with and without Prader-Willi syndrome

Introduction: Prader-Willi syndrome (PWS) is a multisystem genetic imprinting disorder mainly characterized by hyperphagia and childhood obesity. Extensive structural alterations are expected in PWS patients, and their influence on brain nuclei should be early and profound. To date, few studies have investigated brain nuclei in children with PWS, although functional and structural alterations of the cortex have been reported widely.

Methods: In the current study, we used T1-weighted magnetic resonance imaging to investigate alterations in brain nuclei by three automated analysis methods: shape analysis to evaluate the shape of 14 cerebral nuclei (bilateral thalamus, caudate, putamen, globus pallidus, hippocampus, amygdala, and nucleus accumbens), automated segmentation methods integrated in Freesurfer 7.2.0 to investigate the volume of hypothalamic subregions, and region of interest-based analysis to investigate the volume of deep cerebellar nuclei (DCN). Twelve age- and sex-matched children with PWS, 18 obese children without PWS (OB) and 18 healthy controls participated in this study.

Results: Compared with control and OB individuals, the PWS group exhibited significant atrophy in the bilateral thalamus, pallidum, hippocampus, amygdala, nucleus accumbens, right caudate, bilateral hypothalamus (left anterior-inferior, bilateral posterior, and bilateral tubular inferior subunits) and bilateral DCN (dentate, interposed, and fastigial nuclei), whereas no significant difference was found between the OB and control groups.

Discussion: Based on our evidence, we suggested that alterations in brain nuclei influenced by imprinted genes were associated with clinical manifestations of PWS, such as eating disorders, cognitive disability and endocrine abnormalities, which were distinct from the neural mechanisms of obese children.

Gray Matter Volume Loss in Proposed Brain-First and Body-First Parkinson's Disease Subtypes

BACKGROUND

α-Synuclein pathology is associated with neuronal degeneration in Parkinson's disease (PD) and considered to sequentially spread across the brain (Braak stages). According to a new hypothesis of distinct α-synuclein spreading directions based on the initial site of pathology, the "brain-first" spreading subtype would be associated with a more asymmetric cerebral and nigrostriatal pathology than the "body-first" subtype.

OBJECTIVE

Here, we tested if proposed markers of brain-first PD (ie, higher dopamine transporter [DaT] asymmetry; absence of rapid eye movement sleep behavior disorder [RBD]) are associated with a greater or more asymmetric reduction in gray matter volume (GMV) in comparison to body-first PD.

METHODS

Data of 255 de novo PD patients and 110 healthy controls (HCs) were retrieved from the Parkinson's Progression Markers Initiative. Structural magnetic resonance images were preprocessed, and GMVs and their hemispherical asymmetry were obtained for each of the neuropathologically defined Braak stages. Group and correlation comparisons were performed to assess differences in GMV and GMV asymmetry between PD subtypes.

RESULTS

PD patients demonstrated significantly smaller bilateral GMVs compared to HCs, in a pattern denoting stage-dependent disease-related brain atrophy. However, the degree of putaminal DaT asymmetry was not associated with reduced GMV or higher GMV asymmetry. Furthermore, RBD-negative and RBD-positive patients did not demonstrate a significant difference in GMV or GMV asymmetry.

CONCLUSIONS

Our findings suggest that putative brain-first and body-first patients do not present diverging brain atrophy patterns. Although certainly not disproving the brain-first/body-first spreading hypothesis, this study fails to provide evidence in support of it. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Contracted thalamic shape is associated with early development of levodopa-induced dyskinesia in Parkinson's disease

Levodopa-induced dyskinesia (LID), a long-term motor complication in Parkinson’s disease (PD), is attributable to both presynaptic and postsynaptic mechanisms. However, no studies have evaluated the baseline structural changes associated with LID at a subcortical level in PD. A total of 116 right-handed PD patients were recruited and based on the LID latency of 5 years, we classified patients into those vulnerable to LID (PD-vLID, n = 49) and those resistant to LID (PD-rLID, n = 67). After adjusting for covariates including dopamine transporter (DAT) availability of the posterior putamen, we compared the subcortical shape between the groups and investigated its association with the onset of LID. The PD-vLID group had lower DAT availability in the posterior putamen, higher parkinsonian motor deficits, and faster increment in levodopa equivalent dose than the PD-rLID group. The PD-vLID group had significant inward deformation in the right thalamus compared to the PD-rLID group. Inward deformation in the thalamus was associated with an earlier onset of LID at baseline. This study suggests that independent of presynaptic dopamine depletion, the thalamus is a major neural substrate for LID and that a contracted thalamic shape at baseline is closely associated with an early development of LID.

Subthalamic Beta Activity in Parkinson's Disease May Be Linked to Dorsal Striatum Gray Matter Volume and Prefrontal Cortical Thickness: A Pilot Study

Background

Excessive oscillations at beta frequencies (13–35 Hz) in the subthalamic nucleus (STN) represent a pathophysiological hallmark of Parkinson's disease (PD), which correlates well with parkinsonian symptoms and is reduced in response to standard disease treatments. However, the association of disease-specific regional gray matter (GM) atrophy or cortical thickness (CT) with the presence of STN beta oscillatory activity has been poorly investigated but is of relevance given the potential of these variables for extracting information about PD pathophysiology. This exploratory study investigated the involvement of regional GM volume and CT in the basal ganglia-cortical network and its potential association with the presence of STN beta oscillatory activity in PD.

Methods

We acquired preoperative GM densities on T1-weighted magnetic resonance imaging scans and we carried out regional estimation of GM volume and CT. LFP activities from the STN were recorded post-operatively in 7 cognitively preserved PD patients off dopaminergic medication undergoing deep-brain stimulation surgery. Oscillatory beta power was determined by power spectral density of 4-min resting state STN LFP activity. Spearman partial correlations and regression analysis were used to screen the presence of STN beta power for their relationship with GM volume and CT measurements.

Results

After controlling for the effects of age, educational level, and disease duration, and after correcting for multiple testing, enhanced STN beta power showed significant and negative correlations between, first, volume of the right putamen and left caudate nucleus, and second, smaller CT in frontal regions involving the left rostral middle frontal gyrus (MFG) and left medial orbitofrontal gyrus. A lower volume in the right putamen and a lower CT in the left MFG demonstrated the strongest associations with increased STN beta power.

Conclusions

These tentative results seem to suggest that STN LFP beta frequencies may be mainly linked to different but ongoing parallel neurodegenerative processes, on the one hand, to GM volume reduction in dorsal striatum, and on the other hand, to CT reduction of prefrontal-“associative” regions. These findings could further delineate the brain structural interactions underpinning the exaggerated STN beta activity commonly observed in PD patients.

Mining imaging and clinical data with machine learning approaches for the diagnosis and early detection of Parkinson's disease

Parkinson’s disease (PD) is a common, progressive, and currently incurable neurodegenerative movement disorder. The diagnosis of PD is challenging, especially in the differential diagnosis of parkinsonism and in early PD detection. Due to the advantages of machine learning such as learning complex data patterns and making inferences for individuals, machine-learning techniques have been increasingly applied to the diagnosis of PD, and have shown some promising results. Machine-learning-based imaging applications have made it possible to help differentiate parkinsonism and detect PD at early stages automatically in a number of neuroimaging studies. Comparative studies have shown that machine-learning-based SPECT image analysis applications in PD have outperformed conventional semi-quantitative analysis in detecting PD-associated dopaminergic degeneration, performed comparably well as experts’ visual inspection, and helped improve PD diagnostic accuracy of radiologists. Using combined multi-modal (imaging and clinical) data in these applications may further enhance PD diagnosis and early detection. To integrate machine-learning-based diagnostic applications into clinical systems, further validation and optimization of these applications are needed to make them accurate and reliable. It is anticipated that machine-learning techniques will further help improve differential diagnosis of parkinsonism and early detection of PD, which may reduce the error rate of PD diagnosis and help detect PD at pre-motor stage to make it possible for early treatments (e.g., neuroprotective treatment) to slow down PD progression, prevent severe motor symptoms from emerging, and relieve patients from suffering.

Changes in the Shape and Volume of Subcortical Structures in Patients With End-Stage Renal Disease

Introduction: End-stage renal disease (ESRD) typically causes changes in brain structure, and patients with ESRD often experience cognitive and sleep disorders. We aimed to assess the changes in the subcortical structure of patients with ESRD and how they are associated with cognitive and sleep disorders.

Methods: We involved 36 adult patients for maintenance hemodialysis and 35 age- and gender-matched control individuals. All participants underwent neuropsychological examination and 3T magnetic resonance imaging (MRI) to acquire T1 anatomical images. The laboratory blood tests were performed in all patients with ESRD close to the time of the MR examination. We used volumetric and vertex-wise shape analysis approaches to investigate the volumes of 14 subcortical structural (e.g., bilateral accumbens, amygdala, hippocampus, caudate, globus pallidus, putamen, and thalamus) abnormalities in the two groups. Analyses of partial correlations and shape correlations were performed in order to identify the associations between subcortical structure, cognition, and sleep quality in patients with ESRD.

Results: The volumetric analysis showed that compared with the healthy control group, patients with ESRD had less bilateral thalamus (left: p < 0.001; right: p < 0.001), bilateral accumbens (left: p < 0.001; right: p = 0.001), and right amygdala (p = 0.002) volumes. In the vertex-wise shape analysis, patients with ESRD had abnormal regional surface atrophy in the bilateral thalamus, right accumbens, left putamen, and bilateral caudate. Moreover, the Montreal Cognitive Assessment (MoCA) score was associated with volume reduction in the bilateral thalamus (left: Spearman ρ = 0.427, p = 0.009; right: ρ = 0.319, p = 0.018), and the Pittsburgh Sleep Quality Index (PSQI) score was associated with volume reduction in the bilateral accumbens (left: ρ = −0.546, p = 0.001; right: ρ = −0.544, p = 0.001). In vertex-wise shape correlation analysis, there was a positive significant correlation between regional shape deformations on the bilateral thalamus and MoCA score in patients with ESRD.

Conclusion: Our study suggested that patients with ESRD have subcortical structural atrophy, which is related to impaired cognitive performance and sleep disturbances. These findings may help to further understand the underlying neural mechanisms of brain changes in patients with ESRD.

Can Dopamine Responsiveness Be Predicted in Parkinson's Disease Without an Acute Administration Test?

BACKGROUND

Dopamine responsiveness (dopa-sensitivity) is an important parameter in the management of patients with Parkinson's disease (PD). For quantification of this parameter, patients undergo a challenge test with acute Levodopa administration after drug withdrawal, which may lead to patient discomfort and use of significant resources.

OBJECTIVE

Our objective was to develop a predictive model combining clinical scores and imaging.

METHODS

350 patients, recruited by 13 specialist French centers and considered for deep brain stimulation, underwent an acute L-dopa challenge (dopa-sensitivity > 30%), full assessment, and MRI investigations, including T1w and R2* images. Data were randomly divided into a learning base from 10 centers and data from the remaining centers for testing. A machine selection approach was applied to choose the optimal variables and these were then used in regression modeling. Complexity of the modelling was incremental, while the first model considered only clinical variables, the subsequent included imaging features. The performances were evaluated by comparing the estimated values and actual valuesResults:Whatever the model, the variables age, sex, disease duration, and motor scores were selected as contributors. The first model used them and the coefficients of determination (R2) was 0.60 for the testing set and 0.69 in the learning set (p < 0.001). The models that added imaging features enhanced the performances: with T1w (R2 = 0.65 and 0.76, p < 0.001) and with R2* (R2 = 0.60 and 0.72, p < 0.001).

CONCLUSION

These results suggest that modeling is potentially a simple way to estimate dopa-sensitivity, but requires confirmation in a larger population, including patients with dopa-sensitivity < 30.

Morphological analysis of subcortical structures for assessment of cognitive dysfunction in Parkinson's disease using multi-atlas based segmentation

Cognitive impairment in Parkinson's Disease (PD) is the most prevalent non-motor symptom that requires analysis of anatomical associations to cognitive decline in PD. The objective of this study is to analyse the morphological variations of the subcortical structures to assess cognitive dysfunction in PD. In this study, T1 MR images of 58 Healthy Control (HC) and 135 PD subjects categorised as 91 Cognitively normal PD (NC-PD), 25 PD with Mild Cognitive Impairment (PD-MCI) and 19 PD with Dementia (PD-D) subjects, based on cognitive scores are utilised. The 132 anatomical regions are segmented using spatially localized multi-atlas model and volumetric analysis is carried out. The morphological alterations through textural features are captured to differentiate among the HC and PD subjects under different cognitive domains. The volumetric differences in the segmented subcortical structures of accumbens, amygdala, caudate, putamen and thalamus are able to predict cognitive impairment in PD. The volumetric distribution of the subcortical structures in PD-MCI subjects exhibit an overlap with the HC group due to lack of spatial specificity in their atrophy levels. The 3D GLCM features extracted from the significant subcortical structures could discriminate HC, NC-PD, PD-MCI and PD-D subjects with better classification accuracies. The disease related atrophy levels of the subcortical structures captured through morphological analysis provide sensitive evaluation of cognitive impairment in PD.

Structural and functional neuroimaging changes associated with cognitive impairment and dementia in Parkinson's disease

This study seeks a better understanding of possible pathophysiological mechanisms associated with cognitive impairment and dementia in Parkinson's disease using structural and functional MRI. We investigated resting-state functional connectivity of important subdivisions of the caudate nucleus, putamen and thalamus, and also how the morphology of these structures are impacted in the disorder. We found cognitively unimpaired Parkinson's disease subjects (n = 33), compared to controls (n = 26), display increased functional connectivity of the dorsal caudate, anterior putamen and mediodorsal thalamic subdivisions with areas across the frontal lobe, as well as reduced functional connectivity of the dorsal caudate with posterior cortical and cerebellar regions. Compared to cognitively unimpaired subjects, those with mild cognitive impairment (n = 22) demonstrated reduced functional connectivity of the mediodorsal thalamus with the paracingulate cortex, while also demonstrating increased functional connectivity of the mediodorsal thalamus with the posterior cingulate cortex, compared to subjects with dementia (n = 17). Extensive volumetric and surface-based deflation was found in subjects with dementia compared to cognitively unimpaired Parkinson's disease participants and controls. Our research suggests that structures within basal ganglia-thalamocortical circuits are implicated in cognitive impairment and dementia in Parkinson's disease, with cognitive impairment and dementia associated with a breakdown in functional connectivity of the mediodorsal thalamus with para- and posterior cingulate regions of the brain respectively.

A longitudinal study of the association between basal ganglia volumes and psychomotor symptoms in subjects with late life depression undergoing ECT

Psychomotor dysfunction (PMD) is a core element and key contributor to disability in late life depression (LLD), which responds well to electroconvulsive therapy (ECT). The neurobiology of PMD and its response to ECT are not well understood. We hypothesized that PMD in LLD is associated with lower striatal volume, and that striatal volume increase following ECT explains PMD improvement. We analyzed data from a two-center prospective cohort study of 110 LLD subjects (>55 years) receiving ECT. Brain MRI and assessment of mood, cognition, and PMD was performed 1 week before, 1 week after, and 6 months after ECT. Volumetry of the caudate nucleus, putamen, globus pallidus, and nucleus accumbens was derived from automatically segmented brain MRIs using Freesurfer®. Linear multiple regression analyses were used to study associations between basal ganglia volume and PMD. Brain MRI was available for 66 patients 1 week post ECT and in 22 patients also six months post ECT. Baseline PMD was associated with a smaller left caudate nucleus. One week after ECT, PMD improved and volume increases were detected bilaterally in the caudate nucleus and putamen, and in the right nucleus accumbens. Improved PMD after ECT did not relate to the significant volume increases in these structures, but was predicted by a nonsignificant volume change in the right globus pallidus. No volume differences were detected 6 months after ECT, compared to baseline. Although PMD is related to lower striatal volume in LLD, ECT-induced increase of striatal volume does not explain PMD improvement.

Texture-based markers from structural imaging correlate with motor handicap in Parkinson's disease

There is a growing need for surrogate biomarkers for Parkinson’s disease (PD). Structural analysis using magnetic resonance imaging with T1-weighted sequences has the potential to quantify histopathological changes. Degeneration is typically measured by the volume and shape of morphological changes. However, these changes appear late in the disease, preventing their use as surrogate markers. We investigated texture changes in 108 individuals, divided into three groups, matched in terms of sex and age: (1) healthy controls (n = 32); (2) patients with early-stage PD (n = 39); and (3) patients with late-stage PD and severe L-dopa-related complications (n = 37). All patients were assessed in off-treatment conditions. Statistical analysis of first- and second-order texture features was conducted in the substantia nigra, striatum, thalamus and sub-thalamic nucleus. Regions of interest volumetry and voxel-based morphometry were performed for comparison. Significantly different texture features were observed between the three populations, with some showing a gradual linear progression between the groups. The volumetric changes in the two PD patient groups were not significantly different. Texture features were significantly associated with clinical scores for motor handicap. These results suggest that texture features, measured in the nigrostriatal pathway at PD diagnosis, may be useful in predicting clinical progression of motor handicap.

Striatal shape alteration as a staging biomarker for Parkinson's Disease

Parkinson's Disease provokes alterations of subcortical deep gray matter, leading to subtle changes in the shape of several subcortical structures even before the manifestation of motor and non-motor clinical symptoms. We used an automated registration and segmentation pipeline to measure this structural alteration in one early and one advanced Parkinson's Disease (PD) cohorts, one prodromal stage cohort and one healthy control cohort. These structural alterations are then passed to a machine learning pipeline to classify these populations. Our workflow is able to distinguish different stages of PD based solely on shape analysis of the bilateral caudate nucleus and putamen, with balanced accuracies in the range of 59% to 85%. Furthermore, we compared the significance of each of these subcortical structure, compared the performances of different classifiers on this task, thus quantifying the informativeness of striatal shape alteration as a staging bio-marker for PD.

Brain atrophy in Parkinson's disease with polysomnography-confirmed REM sleep behavior disorder

We aimed to investigate cortical and subcortical brain alterations in people with Parkinson's disease with polysomnography-confirmed rapid eye movement (REM) sleep behavior disorder (RBD). Thirty people with Parkinson's disease, including 15 people with RBD, were recruited and compared with 41 healthy controls. Surface-based cortical and subcortical analyses were performed on T1-weighted images to investigate thickness and shape abnormalities between groups, and voxel-based and deformation-based morphometry were performed to investigate local volume. Correlations were performed in patients to investigate the structural correlates of motor activity during REM sleep. People with RBD showed cortical thinning in the right perisylvian and inferior temporal cortices and shape contraction in the putamen compared with people without RBD. Compared with controls, people with RBD had extensive cortical thinning and volume loss, brainstem volume was reduced, and shape contraction was found in the basal ganglia and hippocampus. In comparison to controls, people without RBD showed more restricted thinning in the sensorimotor, parietal, and occipital cortices, reduced volume in the brainstem, temporal and more posterior areas, and shape contraction in the pallidum and hippocampus. In Parkinson's disease, higher tonic and phasic REM sleep motor activity was associated with contraction of the thalamic surface, extensive cortical thinning, and subtle volume reduction in the middle temporal gyrus. In Parkinson's disease, the presence of RBD is associated with extensive cortical and subcortical abnormalities, suggesting more severe neurodegeneration in people with RBD. This provides potential neuroanatomical correlates for the more severe clinical phenotype reported in people with Parkinson's disease with RBD.

MRI biomarkers of motor and non-motor symptoms in Parkinson's disease

Parkinson's disease is a heterogeneous disorder with both motor and non-motor symptoms that contribute to functional impairment. To develop effective, disease modifying treatments for these symptoms, biomarkers are necessary to detect neuropathological changes early in the disease course and monitor changes over time. Advances in MRI scan sequences and analytical techniques present numerous promising metrics to detect changes within the nigrostriatal system, implicated in the cardinal motor symptoms of the disease, and detect broader dysfunction involved in the non-motor symptoms, such as cognitive impairment. There is emerging evidence that iron sensitive, neuromelanin sensitive, diffusion sensitive, and resting state functional magnetic imaging measures can capture changes within the nigrostriatal system. Iron, neuromelanin, and diffusion sensitive measures demonstrate high specificity and sensitivity in distinguishing Parkinson's disease relative to controls, with inconsistent results differentiating Parkinson's disease relative to atypical parkinsonian disorders. They may also serve as useful monitoring biomarkers, with each possibly detecting different aspects of the disease course (early nigrosome changes versus broader substantia nigra changes). Investigations of non-motor symptoms, such as cognitive impairment, require careful consideration of the nature of cognitive deficits to characterize regional and network specific impairment. While the early, executive dysfunction observed is consistent with nigrostriatal degeneration, the memory and visuospatial impairments, the harbingers of a dementia process reflect dopaminergic independent dysfunction involving broader regions of the brain.

Striatum Shape Hypertrophy in Early Stage Parkinson's Disease With Excessive Daytime Sleepiness

INTRODUCTION

Excessive daytime sleepiness (EDS) is one of the common and burdensome non-motor symptoms of Parkinson's disease (PD). However, the underlying neuropathology mechanism in PD patients with EDS (PD-EDS) remains unclear. The present study aims to delineate potential locations of structural alteration of subcortical regions in early stage and drug-naïve PD-EDS.

METHODS

The study had 252 patients with PD and 92 matched healthy controls (HC). EDS was estimated with the Epworth Sleepiness Scale, with a cutoff of 10. Ultimately, 59 patients were considered as PD-EDS. The remaining 193 were PD patients without EDS (PD-nEDS). FMRIB's Integrated Registration and Segmentation Tool (FIRST) was employed to assess the volumetric and surface alterations of subcortical nuclei in PD and PD-EDS.

RESULTS

Volumetric analyses found no difference in the subcortical nucleus volume between PD and HC, or PD-EDS and PD-nEDS groups. The shape analyses revealed the local atrophic changes in bilateral caudate and right putamen in patients with PD. In addition, the hypertrophic changes were located in the right putamen and left pallidum in PD-EDS than in PD-nEDS.

CONCLUSION

Our findings revealed the regional hypertrophy of the striatum in PD-EDS. Our results indicate that local hypertrophic striatum would be a valuable early biomarker for detecting the alteration in PD-EDS. The shape analysis contributes valuable information when investigating PD-EDS.

Differentiation of multiple system atrophy from Parkinson's disease by structural connectivity derived from probabilistic tractography

Recent studies combining diffusion tensor-derived metrics and machine learning have shown promising results in the discrimination of multiple system atrophy (MSA) and Parkinson’s disease (PD) patients. This approach has not been tested using more complex methodologies such as probabilistic tractography. The aim of this work is assessing whether the strength of structural connectivity between subcortical structures, measured as the number of streamlines (NOS) derived from tractography, can be used to classify MSA and PD patients at the single-patient level. The classification performance of subcortical FA and MD was also evaluated to compare the discriminant ability between diffusion tensor-derived metrics and NOS. Using diffusion-weighted images acquired in a 3 T MRI scanner and probabilistic tractography, we reconstructed the white matter tracts between 18 subcortical structures from a sample of 54 healthy controls, 31 MSA patients and 65 PD patients. NOS between subcortical structures were compared between groups and entered as features into a machine learning algorithm. Reduced NOS in MSA compared with controls and PD were found in connections between the putamen, pallidum, ventral diencephalon, thalamus, and cerebellum, in both right and left hemispheres. The classification procedure achieved an overall accuracy of 78%, with 71% of the MSA subjects and 86% of the PD patients correctly classified. NOS features outperformed the discrimination performance obtained with FA and MD. Our findings suggest that structural connectivity derived from tractography has the potential to correctly distinguish between MSA and PD patients. Furthermore, NOS measures obtained from tractography might be more useful than diffusion tensor-derived metrics for the detection of MSA.

Effects of Alzheimer's disease and Lewy body disease on subcortical atrophy

BACKGROUND AND PURPOSE

Subcortical structures are affected by neurodegeneration in Alzheimer's disease (AD) and Lewy body disease (LBD). Although the co-occurrence of AD and LBD pathologies and their possible interaction have been reported, the effect of AD and LBD on subcortical structures remains unknown. The effects of AD and LBD on subcortical atrophy and their relationship with cognitive dysfunction were investigated.

METHODS

The cross-sectional study recruited 42 patients with pure AD related cognitive impairment (ADCI), 30 patients with pure LBD related cognitive impairment (LBCI), 58 patients with mixed ADCI and LBCI, and 29 normal subjects. A general linear model was used to compare subcortical volume and shape amongst the groups, to investigate the independent and interaction effects of ADCI and LBCI on subcortical shape and volume, and to analyze the relationship between subcortical volume and cognitive dysfunction in each group.

RESULTS

Alzheimer's disease related cognitive impairment and LBCI were independently associated with subcortical atrophies in the hippocampus and amygdala and in the hippocampus and putamen respectively, but their interaction effect was not significant. Compared to the control group, the pure LBCI group exhibited additional local atrophies in the amygdala, caudate and thalamus. Subcortical atrophies correlated differently with cognitive dysfunction according to the underlying causes of cognitive dysfunction.

CONCLUSIONS

The patterns of subcortical atrophies and their correlation with cognitive dysfunction differ according to the underlying AD, LBD or concomitant AD and LBD.

Increased functional connectivity of thalamic subdivisions in patients with Parkinson's disease

Parkinson’s disease (PD) affects 2–3% of the population over the age of 65 with loss of dopaminergic neurons in the substantia nigra impacting the functioning of basal ganglia-thalamocortical circuits. The precise role played by the thalamus is unknown, despite its critical role in the functioning of the cerebral cortex, and the abnormal neuronal activity of the structure in PD. Our objective was to more clearly elucidate how functional connectivity and morphology of the thalamus are impacted in PD (n = 32) compared to Controls (n = 20). To investigate functional connectivity of the thalamus we subdivided the structure into two important regions-of-interest, the first with putative connections to the motor cortices and the second with putative connections to prefrontal cortices. We then investigated potential differences in the size and shape of the thalamus in PD, and how morphology and functional connectivity relate to clinical variables. Our data demonstrate that PD is associated with increases in functional connectivity between motor subdivisions of the thalamus and the supplementary motor area, and between prefrontal thalamic subdivisions and nuclei of the basal ganglia, anterior and dorsolateral prefrontal cortices, as well as the anterior and paracingulate gyri. These results suggest that PD is associated with increased functional connectivity of subdivisions of the thalamus which may be indicative alterations to basal ganglia-thalamocortical circuitry.

Combined Assessment of Diffusion Parameters and Cerebral Blood Flow Within Basal Ganglia in Early Parkinson's Disease

Diffusion tensor imaging (DTI) is a sensitive tool for detecting brain tissue microstructural alterations in Parkinson’s disease (PD). Abnormal cerebral perfusion patterns have also been reported in PD patients using arterial spin labeling (ASL) MRI. In this study we aimed to perform a combined DTI and ASL assessment in PD patients within the basal ganglia, in order to test the relationship between microstructural and perfusion alterations. Fifty-two subjects participated in this study. Specifically, 26 PD patients [mean age (SD) = 66.7 (8.9) years, 21 males, median (IQR) Modified Hoehn and Yahr = 1.5 (1–1.6)] and twenty-six healthy controls [HC, mean age (SD) = 65.2 (7.5), 15 males] were scanned with 1.5T MRI. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD) maps were derived from diffusion-weighted images, while cerebral blood flow (CBF) maps were computed from ASL data. After registration to Montreal Neurological Institute standard space, FA, MD, AD, RD and CBF median values were extracted within specific regions of interest: substantia nigra, caudate, putamen, globus pallidus, thalamus, red nucleus and subthalamic nucleus. DTI measures and CBF were compared between the two groups. The relationship between diffusion parameters and CBF was tested with Spearman’s correlations. False discovery rate (FDR)-corrected p-values lower than 0.05 were considered significant, while uncorrected p-values <0.05 were considered a trend. No significant FA, MD and RD differences were observed. AD was significantly increased in PD patients compared with HC in the putamen (p = 0.005, p_FDR = 0.035). No significant CBF differences were found between PD patients and HC. Diffusion parameters were not significantly correlated with CBF in the HC group, while a significant correlation emerged for PD patients in the caudate nucleus, for all DTI measures (with FA: r = 0.543, p_FDR = 0.028; with MD: r = −0.661, p_FDR = 0.002; with AD: r = −0.628, p_FDR = 0.007; with RD: r = −0.635, p_FDR = 0.003). This study showed that DTI is a more sensitive technique than ASL to detect alterations in the basal ganglia in the early phase of PD. Our results suggest that, although DTI and ASL convey different information, a relationship between microstructural integrity and perfusion changes in the caudate may be present.

A totally data-driven whole-brain multimodal pipeline for the discrimination of Parkinson's disease, multiple system atrophy and healthy control

Parkinson's Disease (PD) and Multiple System Atrophy (MSA) are two parkinsonian syndromes that share many symptoms, albeit having very different prognosis. Although previous studies have proposed multimodal MRI protocols combined with multivariate analysis to discriminate between these two populations and healthy controls, studies combining all MRI indexes relevant for these disorders (i.e. grey matter volume, fractional anisotropy, mean diffusivity, iron deposition, brain activity at rest and brain connectivity) with a completely data-driven voxelwise analysis for discrimination are still lacking. In this study, we used such a complete MRI protocol and adapted a fully-data driven analysis pipeline to discriminate between these populations and a healthy controls (HC) group. The pipeline combined several feature selection and reduction steps to obtain interpretable models with a low number of discriminant features that can shed light onto the brain pathology of PD and MSA. Using this pipeline, we could discriminate between PD and HC (best accuracy = 0.78), MSA and HC (best accuracy = 0.94) and PD and MSA (best accuracy = 0.88). Moreover, we showed that indexes derived from resting-state fMRI alone could discriminate between PD and HC, while mean diffusivity in the cerebellum and the putamen alone could discriminate between MSA and HC. On the other hand, a more diverse set of indexes derived by multiple modalities was needed to discriminate between the two disorders. We showed that our pipeline was able to discriminate between distinct pathological populations while delivering sparse model that could be used to better understand the neural underpinning of the pathologies.

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Structuro-functional MRI can discriminate between parkinsonian syndromes

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Discriminant MRI modalities vary as a function of the discrimination task

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fMRI is crucial in discriminating between Parkinson's disease patients and controls

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Structural MRI discriminate between Multiple System Atrophy patients and controls

Subcortical Shape Abnormalities in Bulimia Nervosa

BACKGROUND

Bulimia nervosa (BN) is associated with functional abnormalities in frontostriatal and frontolimbic circuits. Although structural alterations in the frontal portions of these circuits have been observed, this is the first study of subcortical surface morphometry and the largest study of subcortical volume in BN.

METHODS

Anatomical magnetic resonance scans were acquired from 62 female participants with full and subthreshold BN (mean age ± SD, 18.7 ± 4.0 years) and 65 group-matched healthy control participants (mean age ± SD, 19.3 ± 5.7 years). General linear models were used to compare groups and assess the significance of group-by-age interactions on the shape and total volume of 15 subcortical structures (p < .05, familywise error corrected). Associations with illness severity and duration were assessed in the BN group.

RESULTS

Subcortical volumes did not differ across groups, but vertexwise analyses revealed inward shape deformations on the anterior surface of the pallidum in BN relative to control participants that were associated with binge-eating frequency and illness duration. Inward deformations on the ventrolateral thalamus and dorsal amygdala were more pronounced with advancing age in the BN group, and inward deformations on the caudate, putamen, and amygdala were associated with self-induced vomiting frequency.

CONCLUSIONS

Our findings point to localized deformations on the surface of subcortical structures in areas that comprise both reward and cognitive control circuits. These deformations were more pronounced among older BN participants and among those with the most severe symptoms. Such precise localization of alterations in subcortical morphometry may ultimately aid in efforts to identify markers of risk and BN persistence.

Thalamic shape and volume abnormalities in female patients with panic disorder

The thalamus is believed to play crucial role in processing viscero-sensory information, and regulating the activity of amygdala in patients with panic disorder (PD). Previous functional neuroimaging studies have detected abnormal activation in the thalamus in patients with PD compared with healthy control subjects (HC). Very few studies, however, have investigated for volumetric abnormalities in the thalamus in patients with PD. Furthermore, to the best of our knowledge, no previous study has investigated for shape abnormalities in the thalamus in patients with PD. Twenty-five patients with PD and 25 HC participants (all female) were recruited for the study. A voxel-wise volume comparison analysis and a vertex-wise shape analysis were conducted to evaluate structural abnormalities in the PD patients compared to HC. The patients with PD demonstrated significant gray matter volume reductions in the thalamus bilaterally, relative to the HC. The shape analysis detected significant inward deformation in some thalamic regions in the PD patients, including the anterior nucleus, mediodorsal nucleus, and pulvinar nucleus. PD patients showed shape deformations in key thalamic regions that are believed to play a role in regulating emotional and cognitive functions.

Structural Imaging in Atypical Parkinsonism

Qualitative and quantitative structural magnetic resonance imaging offer objective measures of the underlying neurodegeneration in atypical parkinsonism. Regional changes in tissue volume, signal changes and increased deposition of iron as assessed with different structural MRI techniques are surrogate markers of underlying neurodegeneration and may reflect cell loss, microglial proliferation and astroglial activation. Structural MRI has been explored as a tool to enhance diagnostic accuracy in differentiating atypical parkinsonian disorders (APDs). Moreover, the longitudinal assessment of serial structural MRI-derived parameters offers the opportunity for robust inferences regarding the progression of APDs. This review summarizes recent research findings as (1) a diagnostic tool for APDs as well as (2) as a tool to assess longitudinal changes of serial MRI-derived parameters in the different APDs.

Selection Processing in Noun and Verb Production in Left- and Right-Sided Parkinson's Disease Patients

Verbs are more difficult to produce than nouns. Thus, if executive resources are reduced as in Parkinson's disease (PD), verbs are penalized compared to nouns. However, in an experimental condition in which it is the noun that must be selected from a larger number of alternatives compared to the verb, it is the noun production that becomes slower and more prone to errors. Indeed, patients are slower and less accurate than normal subjects when required to produce nouns from verbs (VN) in a morphology derivation tasks (e.g., "osservazione" from "osservare") ["observation" from "observe"] than verbs from nouns in a morphology generation task, in which only a verb can be generated from the noun (NV) (e.g., "fallire" from "fallimento") ["to fail" from "failure"]. In the Italian language morphology, in fact, generation and derivation tasks differ in the number of lexical entries among which the response must be selected. The left Inferior Frontal Gyrus (IFG) has been demonstrated to be involved in selection processes. In the present study, we explored if the ability to select words is related to the cortical thickness of the left IFG. Twelve right-sided PD with nigrostriatal hypofunctionality in the left hemisphere (RPD-LH), 9 left-sided PD with nigrostriatal hypofunctionality in the right hemisphere (LPD-RH) and 19 healthy controls (HC) took part in the study. NV and VN production tasks were administered; accuracy and reaction times (RTs) were collected. All 40 subjects received a structural MRI examination. Cortical thickness of the IFG and volumetric measurements for subcortical regions, thought to support selection processes, were computed using FreeSurfer. In VN derivation tasks RPD-LH patients were less accurate than LPD-RH patients (accuracy: 66% vs. 77%). No difference emerged among the three groups in RTs. Task accuracy/RTs and IFG thickness showed a significant correlation only in RPD-LH. Not only nouns (as expected) but also verbs were correlated with cortical thickness. This suggests that the linguistic nature of the stimuli along with executive resources are both relevant during word selection processes. Our data confirm that executive resources and language interact in the left IFG in word production tasks.

Striatal changes in Parkinson disease: An investigation of morphology, functional connectivity and their relationship to clinical symptoms

We sought to investigate morphological and resting state functional connectivity changes to the striatal nuclei in Parkinson disease (PD) and examine whether changes were associated with measures of clinical function. Striatal nuclei were manually segmented on 3T-T1 weighted MRI scans of 74 PD participants and 27 control subjects, quantitatively analysed for volume, shape and also functional connectivity using functional MRI data. Bilateral caudate nuclei and putamen volumes were significantly reduced in the PD cohort compared to controls. When looking at left and right hemispheres, the PD cohort had significantly smaller left caudate nucleus and right putamen volumes compared to controls. A significant correlation was found between greater atrophy of the caudate nucleus and poorer cognitive function, and between greater atrophy of the putamen and more severe motor symptoms. Resting-state functional MRI analysis revealed altered functional connectivity of the striatal structures in the PD group. This research demonstrates that PD involves atrophic changes to the caudate nucleus and putamen that are linked to clinical dysfunction. Our work reveals important information about a key structure-function relationship in the brain and provides support for caudate nucleus and putamen atrophy as neuroimaging biomeasures in PD.

A Fully-Automated Subcortical and Ventricular Shape Generation Pipeline Preserving Smoothness and Anatomical Topology

In this paper, we present a fully-automated subcortical and ventricular shape generation pipeline that acts on structural magnetic resonance images (MRIs) of the human brain. Principally, the proposed pipeline consists of three steps: (1) automated structure segmentation using the diffeomorphic multi-atlas likelihood-fusion algorithm; (2) study-specific shape template creation based on the Delaunay triangulation; (3) deformation-based shape filtering using the large deformation diffeomorphic metric mapping for surfaces. The proposed pipeline is shown to provide high accuracy, sufficient smoothness, and accurate anatomical topology. Two datasets focused upon Huntington's disease (HD) were used for evaluating the performance of the proposed pipeline. The first of these contains a total of 16 MRI scans, each with a gold standard available, on which the proposed pipeline's outputs were observed to be highly accurate and smooth when compared with the gold standard. Visual examinations and outlier analyses on the second dataset, which contains a total of 1,445 MRI scans, revealed 100% success rates for the putamen, the thalamus, the globus pallidus, the amygdala, and the lateral ventricle in both hemispheres and rates no smaller than 97% for the bilateral hippocampus and caudate. Another independent dataset, consisting of 15 atlas images and 20 testing images, was also used to quantitatively evaluate the proposed pipeline, with high accuracy having been obtained. In short, the proposed pipeline is herein demonstrated to be effective, both quantitatively and qualitatively, using a large collection of MRI scans.

Cortical and subcortical gray matter bases of cognitive deficits in REM sleep behavior disorder

OBJECTIVE

To investigate cortical and subcortical gray matter abnormalities underlying cognitive impairment in patients with REM sleep behavior disorder (RBD) with or without mild cognitive impairment (MCI).

METHODS

Fifty-two patients with RBD, including 17 patients with MCI, were recruited and compared to 41 controls. All participants underwent extensive clinical assessments, neuropsychological examination, and 3-tesla MRI acquisition of T1 anatomical images. Vertex-based cortical analyses of volume, thickness, and surface area were performed to investigate cortical abnormalities between groups, whereas vertex-based shape analysis was performed to investigate subcortical structure surfaces. Correlations were performed to investigate associations between cortical and subcortical metrics, cognitive domains, and other markers of neurodegeneration (color discrimination, olfaction, and autonomic measures).

RESULTS

Patients with MCI had cortical thinning in the frontal, cingulate, temporal, and occipital cortices, and abnormal surface contraction in the lenticular nucleus and thalamus. Patients without MCI had cortical thinning restricted to the frontal cortex. Lower patient performance in cognitive domains was associated with cortical and subcortical abnormalities. Moreover, impaired performance on olfaction, color discrimination, and autonomic measures was associated with thinning in the occipital lobe.

CONCLUSIONS

Cortical and subcortical gray matter abnormalities are associated with cognitive status in patients with RBD, with more extensive patterns in patients with MCI. Our results highlight the importance of distinguishing between subgroups of patients with RBD according to cognitive status in order to better understand the neurodegenerative process in this population.

Cognition and connectomes in nondementia idiopathic Parkinson's disease

In this study, we investigate the organization of the structural connectome in cognitively well participants with Parkinson’s disease (PD-Well; n = 31) and a subgroup of participants with Parkinson’s disease who have amnestic disturbances (PD-MI; n = 9). We explore correlations between connectome topology and vulnerable cognitive domains in Parkinson’s disease relative to non-Parkinson’s disease peers (control, n = 40). Diffusion-weighted MRI data and deterministic tractography were used to generate connectomes. Connectome topological indices under study included weighted indices of node strength, path length, clustering coefficient, and small-worldness. Relative to controls, node strength was reduced 4.99% for PD-Well (p = 0.041) and 13.2% for PD-MI (p = 0.004). We found bilateral differences in the node strength between PD-MI and controls for inferior parietal, caudal middle frontal, posterior cingulate, precentral, and rostral middle frontal. Correlations between connectome and cognitive domains of interest showed that topological indices of global connectivity negatively associated with working memory and displayed more and larger negative correlations with neuropsychological indices of memory in PD-MI than in PD-Well and controls. These findings suggest that indices of network connectivity are reduced in PD-MI relative to PD-Well and control participants.

Parkinson’s disease (PD) patients with amnestic mild cognitive impairment (e.g., primary processing-speed impairments or primary memory impairments) are at greater risk of developing dementia. Recent evidence suggests that patients with PD and mild cognitive impairment present an altered connectome connectivity. In this work, we further explore the structural connectome of PD patients to provide clues to identify possible sensitive markers of disease progression, and cognitive impairment, in susceptible PD patients. We employed a weighted network framework that yields more stable topological results than the binary network framework and is robust despite graph density differences, hence it does not require thresholding to analyze the connectomes. As Supplementary Information (Colon-Perez et al., 2017), we include databases sharing the results of the network data.

Reproducibility of Deep Gray Matter Atrophy Rate Measurement in a Large Multicenter Dataset

BACKGROUND AND PURPOSE

Precise in vivo measurement of deep GM volume change is a highly demanded prerequisite for an adequate evaluation of disease progression and new treatments. However, quantitative data on the reproducibility of deep GM structure volumetry are not yet available. In this paper we aim to investigate this reproducibility using a large multicenter dataset.

MATERIALS AND METHODS

We have assessed the reproducibility of 2 automated segmentation software packages (FreeSurfer and the FMRIB Integrated Registration and Segmentation Tool) by quantifying the volume changes of deep GM structures by using back-to-back MR imaging scans from the Alzheimer Disease Neuroimaging Initiative's multicenter dataset. Five hundred sixty-two subjects with scans at baseline and 1 year were included. Reproducibility was investigated in the bilateral caudate nucleus, putamen, amygdala, globus pallidus, and thalamus by carrying out descriptives as well as multilevel and variance component analysis.

RESULTS

Median absolute back-to-back differences varied between GM structures, ranging from 59.6-156.4 μL for volume change, and 1.26%-8.63% for percentage volume change. FreeSurfer had a better performance for the outcome of longitudinal volume change for the bilateral amygdala, putamen, left caudate nucleus (P < .005), and right thalamus (P < .001). For longitudinal percentage volume change, Freesurfer performed better for the left amygdala, bilateral caudate nucleus, and left putamen (P < .001). Smaller limits of agreement were found for FreeSurfer for both outcomes for all GM structures except the globus pallidus. Our results showed that back-to-back differences in 1-year percentage volume change were approximately 1.5-3.5 times larger than the mean measured 1-year volume change of those structures.

CONCLUSIONS

Longitudinal deep GM atrophy measures should be interpreted with caution. Furthermore, deep GM atrophy measurement techniques require substantially improved reproducibility, specifically when aiming for personalized medicine.

Predicting auditory feedback control of speech production from subregional shape of subcortical structures

Although a growing body of research has focused on the cortical sensorimotor mechanisms that support auditory feedback control of speech production, much less is known about the subcortical contributions to this control process. This study examined whether subregional anatomy of subcortical structures assessed by statistical shape analysis is associated with vocal compensations and cortical event-related potentials in response to pitch feedback errors. The results revealed significant negative correlations between the magnitudes of vocal compensations and subregional shape of the right thalamus, between the latencies of vocal compensations and subregional shape of the left caudate and pallidum, and between the latencies of cortical N1 responses and subregional shape of the left putamen. These associations indicate that smaller local volumes of the basal ganglia and thalamus are predictive of slower and larger neurobehavioral responses to vocal pitch errors. Furthermore, increased local volumes of the left hippocampus and right amygdala were predictive of larger vocal compensations, suggesting that there is an interplay between the memory-related subcortical structures and auditory-vocal integration. These results, for the first time, provide evidence for differential associations of subregional morphology of the basal ganglia, thalamus, hippocampus, and amygdala with neurobehavioral processing of vocal pitch errors, suggesting that subregional shape measures of subcortical structures can predict behavioral outcome of auditory-vocal integration and associated neural features. Hum Brain Mapp 39:459-471, 2018. © 2017 Wiley Periodicals, Inc.

Magnetic resonance imaging for the diagnosis of Parkinson's disease

The differential diagnosis of parkinsonian syndromes is considered one of the most challenging in neurology and error rates in the clinical diagnosis can be high even at specialized centres. Despite several limitations, magnetic resonance imaging (MRI) has undoubtedly enhanced the diagnostic accuracy in the differential diagnosis of neurodegenerative parkinsonism over the last three decades. This review aims to summarize research findings regarding the value of the different MRI techniques, including advanced sequences at high- and ultra-high-field MRI and modern image analysis algorithms, in the diagnostic work-up of Parkinson's disease. This includes not only the exclusion of alternative diagnoses for Parkinson's disease such as symptomatic parkinsonism and atypical parkinsonism, but also the diagnosis of early, new onset, and even prodromal Parkinson's disease.

Putamen Volume is Negatively Correlated with the Ability to Recognize Fearful Facial Expressions

Findings of previous functional magnetic resonance imaging (MRI) and neuropsychological studies have suggested that specific aspects of the basal ganglia, particularly the putamen, are involved in the recognition of emotional facial expressions. However, it remains unknown whether variations in putamen structure reflect individual differences in the ability to recognize facial expressions. Thus, the present study assessed the putamen volumes and shapes of 50 healthy Japanese adults using structural MRI scans and evaluated the ability of participants to recognize facial expressions associated with six basic emotions: anger, disgust, fear, happiness, sadness, and surprise. The volume of the bilateral putamen was negatively associated with the recognition of fearful faces, and the local shapes of both the anterior and posterior subregions of the bilateral putamen, which are thought to support cognitive/affective and motor processing, respectively, exhibited similar negative relationships with the recognition of fearful expressions. These results suggest that individual differences in putamen structure can predict the ability to recognize fearful facial expressions in others. Additionally, these findings indicate that cognitive/affective and motor processing underlie this process.

Probabilistic modeling of anatomical variability using a low dimensional parameterization of diffeomorphisms

We present an efficient probabilistic model of anatomical variability in a linear space of initial velocities of diffeomorphic transformations and demonstrate its benefits in clinical studies of brain anatomy. To overcome the computational challenges of the high dimensional deformation-based descriptors, we develop a latent variable model for principal geodesic analysis (PGA) based on a low dimensional shape descriptor that effectively captures the intrinsic variability in a population. We define a novel shape prior that explicitly represents principal modes as a multivariate complex Gaussian distribution on the initial velocities in a bandlimited space. We demonstrate the performance of our model on a set of 3D brain MRI scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Our model yields a more compact representation of group variation at substantially lower computational cost than the state-of-the-art method such as tangent space PCA (TPCA) and probabilistic principal geodesic analysis (PPGA) that operate in the high dimensional image space.

Striatal and Hippocampal Atrophy in Idiopathic Parkinson's Disease Patients without Dementia: A Morphometric Analysis

Background

Analyses of subcortical gray structure volumes in non-demented idiopathic Parkinson’s disease (PD) often, but not always, show volume loss of the putamen, caudate nucleus, nucleus accumbens, and hippocampus. There is building evidence that structure morphometry might be more sensitive to disease-related processes than volume.

Objective

To assess morphometric differences of subcortical structures (putamen, caudate nucleus, thalamus, globus pallidus, nucleus accumbens, and amygdala) as well as the hippocampus in non-demented individuals with PD relative to age and education matched non-PD peers.

Methods

Prospective recruitment of idiopathic no-dementia PD and non-PD peers as part of a federally funded investigation. T1-weighted isovoxel metrics acquired via 3-T Siemens Verio for all individuals [PD n = 72 (left side onset n = 27, right side onset n = 45); non-PD n = 48]. FIRST (FMRIB Software Library) applications provided volumetric and vertex analyses on group differences for structure size and morphometry.

Results

Group volume differences were observed only for putamen and hippocampi (PD < non-PD) with hippocampal volume significantly associating with disease duration. Group shape differences were observed for bilateral putamen, caudate nucleus, and hippocampus with greater striatal atrophy contralateral to side of motor symptom onset. Hippocampal shape differences disappeared when removing the effects of volume.

Conclusion

The putamen was the primary structure to show both volume and shape differences in PD, indicating that the putamen is the predominant site of basal ganglia atrophy in early- to mid-stage PD. Side of PD symptom onset associates with contralateral striatal atrophy. Left-onset PD might experience more extensive striatal atrophy than right-onset PD. Hippocampus morphometric results suggest possible primary atrophy of CA3/4 and dentate gyrus.

Marked brain asymmetry with intact cognitive functioning in idiopathic Parkinson's disease: a longitudinal analysis

OBJECTIVE

A 71-year-old (MN) with an 11-year history of left onset tremor diagnosed as Parkinson's disease (PD) completed longitudinal brain magnetic resonance imaging (MRI) and neuropsychological testing. MRI scans showed an asymmetric caudate nucleus (right < left volume). We describe this asymmetry at baseline and the progression over time relative to other subcortical gray, frontal white matter, and cortical gray matter regions of interest. Isolated structural changes are compared to MN's cognitive profiles.

METHOD

MN completed yearly MRIs and neuropsychological assessments. For comparison, left onset PD (n = 15) and non-PD (n = 43) peers completed the same baseline protocol. All MRI scans were processed with FreeSurfer and the FMRIB Software Library to analyze gray matter structures and frontal fractional anisotropy (FA) metrics. Processing speed, working memory, language, verbal memory, abstract reasoning, visuospatial, and motor functions were examined using reliable change methods.

RESULTS

At baseline, MN had striatal volume and frontal lobe thickness asymmetry relative to peers with mild prefrontal white matter FA asymmetry. Over time only MN's right caudate nucleus showed accelerated atrophy. Cognitively, MN had slowed psychomotor speed and visuospatial-linked deficits with mild visuospatial working memory declines longitudinally.

CONCLUSIONS

This is a unique report using normative neuroimaging and neuropsychology to describe an individual diagnosed with PD who had striking striatal asymmetry followed secondarily by cortical thickness asymmetry and possible frontal white matter asymmetry. His decline and variability in visual working memory could be linked to ongoing atrophy of his right caudate nucleus.

The effects of HIV and aging on subcortical shape alterations: A 3D morphometric study

Standard volumetric neuroimaging studies have demonstrated preferential atrophy of subcortical structures among individuals with HIV. However, to our knowledge, no study has investigated subcortical shape alterations secondary to HIV and whether advancing age impacts that relationship. This study employed 3D morphometry to examine the independent and interactive effects of HIV and age on shape differences in nucleus accumbens, amygdala, caudate, hippocampus, pallidum, putamen, and thalamus in 81 participants ranging in age from 24 to 76 including 59 HIV+ individuals and 22 HIV-seronegative controls. T1-weighted MRI underwent a preprocessing pipeline followed by automated subcortical segmentation. Parametric statistical analyses were used to determine independent effects of HIV infection and age on volume and shape in each region of interest (ROI) and the interaction between age and HIV serostatus in predicting volume/shape in each ROI. Significant main effects for HIV were found in the shape of right caudate and nucleus accumbens, left pallidum, and hippocampus. Age was associated with differences in shape in left pallidum, right nucleus accumbens and putamen, and bilateral caudate, hippocampus, and thalamus. Of greatest interest, an age × HIV interaction effect was found in the shape of bilateral nucleus accumbens, amygdala, caudate, and thalamus as well as right pallidum and putamen such that increasing age in HIV participants was associated with greater shape alterations. Traditional volumemetric analyses revealed main effects for both HIV and age but no age × HIV interaction. These findings may suggest that age and HIV infection conferred additional deleterious effects on subcortical shape abnormalities beyond the independent effects of these factors. Hum Brain Mapp 38:1025-1037, 2017. © 2016 Wiley Periodicals, Inc.

Multimodal Magnetic Resonance Imaging in Alzheimer's Disease Patients at Prodromal Stage

One objective of modern neuroimaging is to identify markers that can aid in diagnosis, monitor disease progression, and impact long-term drug analysis. In this study, physiopathological modifications in seven subcortical structures of patients with mild cognitive impairment (MCI) due to Alzheimer’s disease (AD) were characterized by simultaneously measuring quantitative magnetic resonance parameters that are sensitive to complementary tissue characteristics (e.g., volume atrophy, shape changes, microstructural damage, and iron deposition). Fourteen MCI patients and fourteen matched, healthy subjects underwent 3T-magnetic resonance imaging with whole-brain, T1-weighted, T2^*-weighted, and diffusion-tensor imaging scans. Volume, shape, mean R2^*, mean diffusivity (MD), and mean fractional anisotropy (FA) in the thalamus, hippocampus, putamen, amygdala, caudate nucleus, pallidum, and accumbens were compared between MCI patients and healthy subjects. Comparisons were then performed using voxel-based analyses of R2^*, MD, FA maps, and voxel-based morphometry to determine which subregions showed the greatest difference for each parameter. With respect to the micro- and macro-structural patterns of damage, our results suggest that different and distinct physiopathological processes are present in the prodromal phase of AD. MCI patients had significant atrophy and microstructural changes within their hippocampi and amygdalae, which are known to be affected in the prodromal stage of AD. This suggests that the amygdala is affected in the same, direct physiopathological process as the hippocampus. Conversely, atrophy alone was observed within the thalamus and putamen, which are not directly involved in AD pathogenesis. This latter result may reflect another mechanism, whereby atrophy is linked to indirect physiopathological processes.