Qualitative versus quantitative assessment of electroencephalography in cognitive decline: Comparison in a clinical population.

This study aimed to compare the diagnostic performance of visual assessment of electroencephalography (EEG) using the Grand Total EEG (GTE) score and quantitative EEG (QEEG) using spectral analysis in the context of cognitive impairment. This was a retrospective study of patients with mild cognitive impairment, with (MCI+V) or without (MCI) vascular dysfunction, and patients with dementia including Alzheimer's disease, Lewy Body Dementia and vascular dementia. The results showed that the GTE is a simple scoring system with some potential applications, but limited ability to distinguish between dementia subtypes, while spectral analysis appeared to be a powerful tool, but its clinical development requires the use of artificial intelligence tools.

Tri-axial rubidium and helium optically pumped magnetometers for on-scalp magnetoencephalography recording of interictal epileptiform discharges: a case study.

Cryogenic magnetoencephalography (MEG) enhances the presurgical assessment of refractory focal epilepsy (RFE). Optically pumped magnetometers (OPMs) are cryogen-free sensors that enable on-scalp MEG recordings. Here, we investigate the application of tri-axial OPMs [87Rb (Rb-OPM) and 4He gas (He-OPM)] for the detection of interictal epileptiform discharges (IEDs). IEDs were recorded simultaneously with 4 tri-axial Rb- and 4 tri-axial He-OPMs in a child with RFE. IEDs were identified visually, isolated from magnetic background noise using independent component analysis (ICA) and were studied following their optimal magnetic field orientation thanks to virtual sensors. Most IEDs (>1,000) were detectable by both He- and Rb-OPM recordings. IEDs were isolated by ICA and the resulting magnetic field oriented mostly tangential to the scalp in Rb-OPMs and radial in He-OPMs. Likely due to differences in sensor locations, the IED amplitude was higher with Rb-OPMs. This case study shows comparable ability of Rb-OPMs and He-OPMs to detect IEDs and the substantial benefits of triaxial OPMs to detect IEDs from different sensor locations. Tri-axial OPMs allow to maximize spatial brain sampling for IEDs detection with a limited number of sensors.

Multi-approach comparative study of EEG patterns associated with the most common forms of dementia.

Electroencephalography's (EEG) sensitivity in discriminating dementia syndromes remains unclear. This study aimed to investigate EEG markers in patients with major cognitive disorders. The studied population included 4 groups of patients: Alzheimer's disease with associated vascular lesions, Alzheimer's disease without vascular lesions (AD-V), Lewy body disease and vascular dementia (VaD); and completed by a control group composed by cognitively unimpaired patients. EEGs were analysed quantitatively using spectral analysis, functional connectivity and micro-states. By comparison to the controls, expected slowing and alterations of functional connectivity were detected in patients with dementia. Among these patients, an overall increase in power in the alpha band was observed in the VaD group, mainly when compared to the 2 AD groups, while the Alzheimer's disease without vascular lesions group exhibited increased power in the beta-2 band and higher functional connectivity in the same frequency band. Micro-state analyses revealed differences in temporal dynamics for the VaD group. A number of EEG modifications reported as markers of some syndromes were found, but others were not reproduced.

The contribution of executive control dysfunction to freezing of gait in Parkinson's disease.

OBJECTIVE: An executive dysfunction is supposed to contribute to freezing of gait (FoG) in Parkinson's disease. We aimed to investigate at a behavioral and cortical levels whether an attentional load (particularly, a conflicting situation) can specifically impact preparation and execution phases of step initiation in parkinsonian patients with FoG. METHODS: Fifteen patients with FoG, 16 without and 15 controls performed an adapted version of the Attention Network Test, with step initiation as response instead of the standard manual keypress. Kinetic and kinematic features of gait initiation as well as high-resolution electroencephalography were recorded during the task. RESULTS: Patients with FoG presented an impaired executive control. Step execution time was longer in parkinsonian patients. However, the executive control effect on step execution time was not different between all groups. Compared to patients, controls showed a shorter step initiation-locked alpha desynchronization, and an earlier, more intense and shorter beta desynchronization over the sensorimotor cortex. Even though controls were faster, the induced alpha and beta activity associated with the effect of executive control didn't differ between patients and controls. CONCLUSIONS: Tasks of conflict resolution lead to a comparable alteration of step initiation and its underlying brain activity in all groups. Links between executive control, gait initiation and FoG seem more complex than expected. SIGNIFICANCE: This study questions the cognitive hypothesis in the pathophysiology of freezing of gait. Executive dysfunction is associated with FoG but is not the main causal mechanism since the interaction between attention and motor preparation didn't provoke FoG.

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.

Texture Features of Magnetic Resonance Images Predict Poststroke Cognitive Impairment: Validation in a Multicenter Study.

BACKGROUND: Imaging features derived from T1-weighted (T1w) images texture analysis were shown to be potential markers of poststroke cognitive impairment, with better sensitivity than atrophy measurement. However, in magnetic resonance images, the signal distribution is subject to variations and can limit transferability of the method between centers. This study examined the reliability of texture features against imaging settings using data from different centers. METHODS: Data were collected from 327 patients within the Stroke and Cognition Consortium from centers in France, Germany, Australia, and the United Kingdom. T1w images were preprocessed to normalize the signal intensities and then texture features, including first- and second-order statistics, were measured in the hippocampus and the entorhinal cortex. Differences between the data led to the use of 2 methods of analysis. First, a machine learning modeling, using random forest, was used to build a poststroke cognitive impairment prediction model using one dataset and this was validated on another dataset as external unseen data. Second, the predictive ability of the texture features was examined in the 2 remaining datasets by ANCOVA with false discovery rate correction for multiple comparisons. RESULTS: The prediction model had a mean accuracy of 90% for individual classification of patients in the learning base while for the validation base it was ≈ 77%. ANCOVA showed significant differences, in all datasets, for the kurtosis and inverse difference moment texture features when measured in patients with cognitive impairment and those without. CONCLUSIONS: These results suggest that texture features obtained from routine clinical MR images are robust early predictors of poststroke cognitive impairment and can be combined with other demographic and clinical predictors to build an accurate prediction model.

The frontostriatal subtype of mild cognitive impairment in Parkinson's disease, but not the posterior cortical one, is associated with specific EEG alterations.

BACKGROUND: The 'dual syndrome' hypothesis states that two cognitive subtypes can be distinguished in mild cognitive impairment in Parkinson's disease (PD-MCI): a frontostriatal one, characterized by attentional and/or executive deficits, and a posterior cortical one, characterized by visuospatial, memory and/or language deficits. The latter type has been associated with a higher risk of earlier development of PD dementia. The functional bases of these subtypes remain partly unknown. OBJECTIVE: To identify EEG modifications associated with PD-MCI subtypes. METHODS: 75 non-demented PD patients underwent a comprehensive neuropsychological assessment and a high-density EEG. They were classified as having normal cognition (PD-NC; n = 37), PD-MCI with a frontostriatal subtype (PD-FS; n = 11) or PD-MCI with a posterior cortical subtype (PD-PC; n = 27). Two EEG analyses were performed: (a) spectral powers quantification and (b) functional connectivity analysis. RESULTS: PD-FS patients displayed spectral and functional EEG alterations, namely (a) higher powers in the theta and delta bands, (b) lower powers in the beta2 band and (c) lower functional connectivity in the beta2 band compared to PD-NC and PD-PC patients. These alterations were mainly located in the frontal, limbic and parietal regions. There were no significant differences between PD-NC and PD-PC. CONCLUSION: EEG alterations previously reported in PD-MCI may only concern the frontostriatal subtype, and not the posterior-cortical subtype. This provides evidence for the dual syndrome hypothesis and emphasizes the importance of identifying PD-MCI subtypes. It also shows the promising potential of EEG to discriminate between PD-MCI subtypes.

Heterogeneity of PD-MCI in Candidates to Subthalamic Deep Brain Stimulation: Associated Cortical and Subcortical Modifications.

BACKGROUND: Parkinson's disease mild cognitive impairment (PD-MCI) is frequent and heterogenous. There is no consensus about its influence on subthalamic deep brain stimulation (STN-DBS) outcomes. OBJECTIVE: To determine the prevalence of PD-MCI and its subtypes in candidates to STN-DBS. Secondarily, we sought to identify MRI structural markers associated with cognitive impairment in these subgroups. METHODS: Baseline data from the French multicentric PREDISTIM cohort were used. Candidates to STN-DBS were classified according to their cognitive performance in normal cognition (PD-NC) or PD-MCI. The latter included frontostriatal (PD-FS) and posterior cortical (PD-PC) subtypes. Between-group comparisons were performed on demographical and clinical variables as well as on T1-weighted MRI sequences at the cortical and subcortical levels. RESULTS: 320 patients were included: 167 (52%) PD-NC and 153 (48%) PD-MCI patients. The latter group included 123 (80%) PD-FS and 30 (20%) PD-PC patients. There was no between-group difference regarding demographic and clinical variables. PD-PC patients had significantly lower global efficiency than PD-FS patients and significantly worse performance on visuospatial functions, episodic memory, and language. Compared to PD-NC, PD-MCI patients had cortical thinning and radiomic-based changes in the left caudate nucleus and hippocampus. There were no significant differences between the PD-MCI subtypes. CONCLUSION: Among the candidates to STN-DBS, a significant proportion has PD-MCI which is associated with cortical and subcortical alterations. Some PD-MCI patients have posterior cortical deficits, a subtype known to be at higher risk of dementia.

Performance Analysis of Optically Pumped 4He Magnetometers vs. Conventional SQUIDs: From Adult to Infant Head Models.

Optically pumped magnetometers (OPMs) are new, room-temperature alternatives to superconducting quantum interference devices (SQUIDs) for measuring the brain's magnetic fields. The most used OPM in MagnetoEncephaloGraphy (MEG) are based on alkali atoms operating in the spin-exchange relaxation-free (SERF) regime. These sensors do not require cooling but have to be heated. Another kind of OPM, based on the parametric resonance of 4He atoms are operated at room temperature, suppressing the heat dissipation issue. They also have an advantageous bandwidth and dynamic range more suitable for MEG recordings. We quantitatively assessed the improvement (relative to a SQUID magnetometers array) in recording the magnetic field with a wearable 4He OPM-MEG system through data simulations. The OPM array and magnetoencephalography forward models were based on anatomical MRI data from an adult, a nine-year-old child, and 10 infants aged between one month and two years. Our simulations showed that a 4He OPMs array offers markedly better spatial specificity than a SQUID magnetometers array in various key performance areas (e.g., signal power, information content, and spatial resolution). Our results are also discussed regarding previous simulation results obtained for alkali OPM.

Functional networks underlying freezing of gait: a resting-state electroencephalographic study.

INTRODUCTION: The pathophysiology of freezing of gait in people with Parkinson's disease (PD) remains unclear, despite its association with motor, cognitive, limbic and sensory-perceptual impairments. Resting-state electroencephalography (EEG) may provide functional information for a better understanding of freezing of gait by studying spectral power and connectivity between brain regions in different frequency bands. METHODS: High-resolution EEG was recorded in 36 patients with PD (18 freezers, 18 non-freezers), and 18 healthy controls during a 5-min resting-state protocol with eyes open, followed by a basic spectral analysis in the sensor space and a more advanced analysis of functional connectivity at the source level. RESULTS: Freezers showed a diffusely higher theta-band relative spectral power than controls. This increased power was correlated with a deficit in executive control. Concerning resting-state functional connectivity, connectivity strength within a left fronto-parietal network appeared to be higher in freezers than in controls in the theta band, and to be correlated with freezing severity and a history of falls. CONCLUSION: We have shown that spectral power and connectivity analyses of resting-state EEG provide useful and complementary information to better understand freezing of gait in PD. The higher connectivity strength seen within the left ventral attention network in freezers is in keeping with an excessive guidance of behavior by external cues, due to executive dysfunction, and spectral analysis also found changes in freezers that was closely correlated with executive control deficits. This exaggerated influence of the external environment might result in behavioral consequences that contribute to freezing of gait episodes. These findings should be further investigated with a longitudinal study.

EEG-based functional connectivity and executive control in patients with Parkinson's disease and freezing of gait.

OBJECTIVE: To explore changes over time in the network specificities underpinning a visual attentional task in patients with Parkinson's disease and freezing of gait (the PD + FoG group), patients with Parkinson's disease but no FoG (PD-FoG), and healthy controls (HCs). METHODS: High-resolution electroencephalography (EEG) data were acquired for 15 PD + FoG patients, 14 PD-FoG patients, and 18 HCs performing the Attention Network Test. After source localization, functional connectivity was assessed and compared by applying the dynamic phase-locking value method. RESULTS: The PD + FoG patients showed an impairment in executive control. Furthermore, the PD + FoG patients showed abnormally high theta band connectivity (relative to HCs, and 400 to 600 ms after target presentation) in a network connecting the orbitofrontal and occipitotemporal regions. CONCLUSIONS: In PD + FoG, the greater functional connectivity between the visual network and the regions to which executive function has been attributed might indicate greater reliance on environmental features when seeking to overcome the impairment in executive control. SIGNIFICANCE: FoG in PD involves cognitive, attentional and executive dysfunctions. Our observation of abnormally high connectivity in PD + FoG patients argues in favor of the interference model of FoG.

Anxiety in Parkinson's disease: A resting-state high density EEG study.

OBJECTIVE: To identify markers of Parkinson's disease (PD) related anxiety, using high density electroencephalography (hd-EEG). METHODS: 108 patients participated in the study. They were divided into two groups: with and without clinically relevant anxiety, according to their score on the Parkinson Anxiety Scale. Resting-state hd-EEG was recorded. Spectral and functional connectivity characteristics were compared between the two groups. RESULTS: Thirty-three patients (31%) had significant anxiety symptoms. In the spectral analysis, relative power in the alpha1 frequency band in the right prefrontal cortex was lower in patients with anxiety than without. Functional connectivity analysis showed a stronger connectivity between the left insula and several regions of the right prefrontal cortex in patients with anxiety than in those without. CONCLUSION: This study shows the pivotal role of the insula and frontal cortex in the pathophysiology of anxiety in PD and extends the results of previous studies using magnetic resonance imaging or positron emission tomography imaging.

Neurophysiological recordings improve the accuracy of the evaluation of the outcome in perinatal hypoxic ischemic encephalopathy.

OBJECTIVES: Our objective was to evaluate the potential additional value of electroencephalogram (EEG) and evoked potentials in neonates with hypoxic-ischemic encephalopathy to predict their disability at 1 and 2 years old. METHODS: 30 full-term infants after perinatal asphyxia who underwent therapeutic hypothermia were evaluated at 1 year and 2 years for disability using International Classification of Functioning, Disability and Health classification. Scores for EEG, sensory evoked potentials and brainstem auditory evoked potentials were evaluated after withdrawal of therapeutic hypothermia that lasted 72 h. A regression approach was investigated to build models allowing to distinguish neonates according to their disability at 1 and 2 years. Two models were built, the first by considering the clinical data and EEG before and after therapeutic hypothermia and the second by incorporating evoked potentials recording. RESULTS: Adding EEG and evoked potentials data after rewarming improved dramatically the accuracy of the model considering outcome at 1 and 2 years. INTERPRETATION: We propose to record systematically EEG and evoked potentials following rewarming to predict the outcome of neonates with hypoxic ischemic encephalopathy. Combination of altered evoked potentials with no improvement of EEG after rewarming appeared to be a robust criterion for a poor outcome.

Posterior Cortical Cognitive Deficits Are Associated With Structural Brain Alterations in Mild Cognitive Impairment in Parkinson's Disease.

Context: Cognitive impairments are common in patients with Parkinson's disease (PD) and are heterogeneous in their presentation. The "dual syndrome hypothesis" suggests the existence of two distinct subtypes of mild cognitive impairment (MCI) in PD: a frontostriatal subtype with predominant attentional and/or executive deficits and a posterior cortical subtype with predominant visuospatial, memory, and/or language deficits. The latter subtype has been associated with a higher risk of developing dementia. Objective: The objective of this study was to identify structural modifications in cortical and subcortical regions associated with each PD-MCI subtype. Methods: One-hundred and fourteen non-demented PD patients underwent a comprehensive neuropsychological assessment as well as a 3T magnetic resonance imaging scan. Patients were categorized as having no cognitive impairment (n = 41) or as having a frontostriatal (n = 16), posterior cortical (n = 25), or a mixed (n = 32) MCI subtype. Cortical regions were analyzed using a surface-based Cortical thickness (CTh) method. In addition, the volumes, shapes, and textures of the caudate nuclei, hippocampi, and thalami were studied. Tractometric analyses were performed on associative and commissural white matter (WM) tracts. Results: There were no between-group differences in volumetric measurements and cortical thickness. Shape analyses revealed more abundant and more extensive deformations fields in the caudate nuclei, hippocampi, and thalami in patients with posterior cortical deficits compared to patients with no cognitive impairment. Decreased fractional anisotropy (FA) and increased mean diffusivity (MD) were also observed in the superior longitudinal fascicle, the inferior fronto-occipital fascicle, the striato-parietal tract, and the anterior and posterior commissural tracts. Texture analyses showed a significant difference in the right hippocampus of patients with a mixed MCI subtype. Conclusion: PD-MCI patients with posterior cortical deficits have more abundant and more extensive structural alterations independently of age, disease duration, and severity, which may explain why they have an increased risk of dementia.

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.

Do kinematic gait parameters help to discriminate between fallers and non-fallers with Parkinson's disease?

OBJECTIVE: Although a number of clinical factors have been linked to falls in Parkinson's disease (PD), the diagnostic value of gait parameters remains subject to debate. The objective of this retrospective study was to determine to what extent the combination of gait parameters with clinical characteristics can distinguish between fallers and non-fallers. METHODS: Using a video motion system, we recorded gait in 174 patients with PD. The patients' clinical characteristics (including motor status, cognitive status, disease duration, dopaminergic treatment and any history of falls or freezing of gait) were noted. The considered kinematic gait parameters included indices of gait bradykinesia and hypokinesia, asymmetry, variability, and foot clearance. After a parameters selection using an ANCOVA analysis, support vector machine algorithm was used to build classification models for distinguishing between fallers and non-fallers. Two models were built, the first included clinical data only while the second incorporated the selected gait parameters. RESULTS: The "clinical-only" model had an accuracy of 94% for distinguishing between fallers and non-fallers. The model incorporating additional gait parameters including stride time and foot clearance performed even better, with an accuracy of up to 97%. CONCLUSION: Although fallers differed significantly from non-fallers with regard to disease duration, motor impairment or dopaminergic treatment, the addition of gait parameters such as foot clearance or stride time to clinical variables increased the model's discriminant power. SIGNIFICANCE: This predictive model now needs to be validated in prospective cohorts.

Quantitative approach to early neonatal EEG visual analysis in hypoxic-ischemic encephalopathy severity: Bridging the gap between eyes and machine.

OBJECTIVES: To identify relevant quantitative parameters for early classification of neonatal hypoxic-ischemic encephalopathy (HIE) severity from conventional EEGs. METHODS: Ninety EEGs, recorded in full-term infants within 6 h of life after perinatal hypoxia, were visually classified according to the French EEG classification into three groups of increasing HIE severity. Physiologically significant EEG features (signal amplitude, continuity and frequency content) were automatically quantified using different parameters. The EEG parameters selection was based on their ability to reproduce the visual EEG classification. Post hoc analysis based on clinical outcome was performed. RESULTS: Six EEG parameters were selected, with overall EEG classification performances between 61% and 70%. All parameters differed significantly between group 3 (severe) and groups 1 (normal-mildly abnormal) and 2 (moderate) EEGs (p < 0.001). Amplitude and discontinuity parameters were different between the 3 groups (p < 0.01) and were also the best predictors of clinical outcome. Conversely, pH and lactate did not differ between groups. DISCUSSION: This study provides quantitative EEG parameters that are complementary to visual analysis as early markers of neonatal HIE severity. These parameters could be combined in a multiparametric algorithm to improve their classification performance. The absence of relationship between pH lactate and HIE severity reinforces the central role of early neonatal EEG.

Anxiety in Parkinson's disease is associated with changes in the brain fear circuit.

BACKGROUND: Anxiety is frequent in Parkinson's disease (PD) and has a negative impact on disease symptoms and quality of life. The underlying mechanisms remain largely unknown. The aim of this study was to identify anatomical and functional changes associated to PD-related anxiety by comparing the volume, shape and texture of the amygdala, the cortical thickness as well as the functional connectivity (FC) of the fear circuit in patients with and without clinically relevant anxiety. METHODS: Non-demented PD patients were recruited, and anxiety was quantified using the Parkinson Anxiety Scale. Structural MRI was used to compare cortical thickness and amygdala structure and resting-state functional MRI to compare FC patterns of the amygdala and resting-state functional networks in both groups. RESULTS: We included 118 patients: 34 with (A+) and 84 without (A-) clinically relevant anxiety. Clusters of cortical thinning were identified in the bilateral fronto-cingulate and left parietal cortices of the A+ group. The texture and the shape of the left amygdala was different in the A+ group but the overall volume did not differ between groups. FC between the amygdala and the whole brain regions did not differ between groups. The internetwork resting-state FC was higher between the "fear circuit" and salience network in the A+ group. CONCLUSION: Anxiety in PD induces structural modifications of the left amygdala, atrophy of the bilateral fronto-cingulate and the left parietal cortices, and a higher internetwork resting-state FC between the fear circuit and the salience network.

Texture features of magnetic resonance images: A marker of slight cognitive deficits in Parkinson's disease.

BACKGROUND: Cognitive impairment is a frequent nonmotor symptom of Parkinson's disease. Depending on severity, patients are considered to have mild cognitive impairment or dementia. However, among the cognitively intact patients, some may have deficits in a less severe range. The early detection of such subtle symptoms may be important for the initiation of care strategies. OBJECTIVE: To identify imaging markers of early cognitive symptoms, potentially before usual signs, such as atrophy, become manifest. METHODS: A total of 102 patients with Parkinson's disease and 17 age-matched cognitively intact healthy controls underwent extensive neuropsychological assessment and T1-weighted magnetic resonance imaging. Parkinson's disease patients were separated into 3 groups according to their cognitive status: intact, with slight slowing, and with mild deficits in executive functions. Texture features as measured by first-order and second-order statistics were computed in the following 6 brain regions: the hippocampus, thalamus, amygdala, putamen, caudate nucleus, and pallidum. They were tested between the groups, and their correlation with cognition was examined. Volumetric measurements were made for comparison. RESULTS: Texture analysis showed significant between-group differences for 2 features-skewness and entropy in the hippocampus, the thalamus, and the amygdala-and the volume analysis revealed no between-group difference. These features were significantly correlated with cognitive performance. CONCLUSION: These results support the assumption that signal alterations associated with Parkinson's disease-related cognitive decline can be captured very early by texture analysis. As these changes appear to reflect clinical phenomena, texture analysis may be a promising marker for helping cognitive phenotyping in Parkinson's disease. © 2019 International Parkinson and Movement Disorder Society.

Texture Features of Magnetic Resonance Images: an Early Marker of Post-stroke Cognitive Impairment.

Stroke is frequently associated with delayed, long-term cognitive impairment (CI) and dementia. Recent research has focused on identifying early predictive markers of CI occurrence. We carried out a texture analysis of magnetic resonance (MR) images to identify predictive markers of CI occurrence based on a combination of preclinical and clinical data. Seventy-two-hour post-stroke T1W MR images of 160 consecutive patients were examined, including 75 patients with confirmed CI at the 6-month post-stroke neuropsychological examination. Texture features were measured in the hippocampus and entorhinal cortex and compared between patients with CI and those without. A correlation study determined their association with MoCA and MMSE clinical scores. Significant features were then combined with the classical prognostic factors, age and gender, to build a machine learning algorithm as a predictive model for CI occurrence. A middle cerebral artery transient occlusion model was used. Texture features were compared in the hippocampus of sham and lesioned rats and were correlated with histologically assessed neural loss. In clinical studies, two texture features, kurtosis and inverse difference moment, differed significantly between patients with and without CI and were significantly correlated with MoCA and MMSE scores. The prediction model had an accuracy of 88 ± 3%. The preclinical model revealed a significant correlation between texture features and neural density in the hippocampus contralateral to the ischemic area. These preliminary results suggest that texture features of MR images are representative of neural alteration and could be a part of a screening strategy for the early prediction of post-stroke CI.