Ross Keenan

The MoCA Well-suited screen for cognitive impairment in Parkinson disease

Objective: To establish the diagnostic accuracy of the Montreal Cognitive Assessment (MoCA) when screening externally validated cognition in Parkinson disease (PD), by comparison with a PD-focused test (Scales for Outcomes in Parkinson disease–Cognition [SCOPA-COG]) and the standardized Mini-Mental State Examination (S-MMSE) as benchmarks. Methods: A convenience sample of 114 patients with idiopathic PD and 47 healthy controls was examined in a movement disorders center. The 21 patients with dementia (PD-D) were diagnosed using Movement Disorders Society criteria, externally validated by detailed independent functional and neuropsychological tests. The 21 patients with mild cognitive impairment (PD-MCI) scored 1.5 SD or more below normative data in at least 2 measures in 1 of 4 cognitive domains. Other patients had normal cognition (PD-N). Results: Primary outcomes using receiver operating characteristic (ROC) curve analyses showed that all 3 mental status tests produced excellent discrimination of PD-D from patients without dementia (area under the curve [AUC], 87%–91%) and PD-MCI from PD-N patients (AUC, 78%–90%), but the MoCA was generally better suited across both assessments. The optimal MoCA screening cutoffs were <21/30 for PD-D (sensitivity 81%; specificity 95%; negative predictive value [NPV] 92%) and <26/30 for PD-MCI (sensitivity 90%; specificity 75%; NPV 95%). Further support that the MoCA is at least equivalent to the SCOPA-COG, and superior to the S-MMSE, came from the simultaneous classification of the 3 PD patient groups (volumes under a 3-dimensional ROC surface, chance = 17%: MoCA 79%, confidence interval [CI] 70%–89%; SCOPA-COG 74%, CI 62%–86%; MMSE-Sevens item 56%, CI 44%–68%; MMSE-World item 62%, CI 50%–73%). Conclusions: The MoCA is a suitably accurate, brief test when screening all levels of cognition in PD.

Arterial spin labelling reveals an abnormal cerebral perfusion pattern in Parkinson’s disease

There is a need for objective imaging markers of Parkinsons disease status and progression. Positron emission tomography and single photon emission computed tomography studies have suggested patterns of abnormal cerebral perfusion in Parkinsons disease as potential functional biomarkers. This study aimed to identify an arterial spin labelling magnetic resonance-derived perfusion network as an accessible, non-invasive alternative. We used pseudo-continuous arterial spin labelling to measure cerebral grey matter perfusion in 61 subjects with Parkinsons disease with a range of motor and cognitive impairment, including patients with dementia and 29 age- and sex-matched controls. Principal component analysis was used to derive a Parkinsons disease-related perfusion network via logistic regression. Region of interest analysis of absolute perfusion values revealed that the Parkinsons disease pattern was characterized by decreased perfusion in posterior parieto-occipital cortex, precuneus and cuneus, and middle frontal gyri compared with healthy controls. Perfusion was preserved in globus pallidus, putamen, anterior cingulate and post- and pre-central gyri. Both motor and cognitive statuses were significant factors related to network score. A network approach, supported by arterial spin labelling-derived absolute perfusion values may provide a readily accessible neuroimaging method to characterize and track progression of both motor and cognitive status in Parkinsons disease.

White matter microstructure deteriorates across cognitive stages in Parkinson disease

Objectives: To characterize different stages of Parkinson disease (PD)-related cognitive decline using diffusion tensor imaging (DTI) and investigate potential relationships between cognition and microstructural integrity of primary white matter tracts. Methods: Movement Disorder Society criteria were used to classify 109 patients with PD as having normal cognition (PD-N, n = 63), mild cognitive impairment (PD-MCI, n = 28), or dementia (PD-D, n = 18), and were compared with 32 matched controls. DTI indices were assessed across groups using tract-based spatial statistics, and multiple regression was used to assess association with cognitive and clinical measures. Results: Relative to controls, PD-N showed some increased mean diffusivity (MD) in corpus callosum, but no significantly decreased fractional anisotropy (FA). Decreased FA and increased MD were identified in PD-MCI and PD-D relative to controls. Only small areas of difference were observed in PD-MCI and PD-D compared with PD-N, while DTI metrics did not differ significantly between PD-MCI and PD-D. Executive function, attention, memory, and a composite measure of global cognition were associated with MD, primarily in anterior white matter tracts; only attention was associated with FA. These differences were independent of white matter hyperintensity load, which was also associated with cognition in PD. Conclusions: PD is associated with spatially restricted loss of microstructural white matter integrity in patients with relatively normal cognition, and these alterations increase with cognitive dysfunction. Functional impairment in executive function, attention, and learning and memory appears associated with microstructural changes, suggesting that tract-based spatial statistics provides an early marker for clinically relevant cognitive impairment in PD.

Reduced striatal volumes in Parkinson’s disease: a magnetic resonance imaging study

BackgroundThe presence and extent of structural changes in the brain as a consequence of Parkinson’s disease (PD) is still poorly understood.MethodsHigh-resolution 3-tesla T1-weighted structural magnetic resonance images in sixty-five PD and 27 age-matched healthy control participants were examined. Putamen, caudate, and intracranial volumes were manually traced in the axial plane of 3D reconstructed images. Striatal nuclei volumes were normalized to intracranial volume for statistical comparison. Disease status was assessed using the Unified Parkinson’s Disease Rating Scale and Hoehn and Yahr scale. Cognitive status was assessed using global status tests and detailed neuropsychological testing.ResultsBoth caudate and putamen volumes were smaller in PD brains compared to controls after adjusting for age and gender. Caudate volumes were reduced by 11% (p = 0.001) and putamen volumes by 8.1% (p = 0.025). PD striatal volumes were not found to be significantly correlated with cognitive or motor decline.ConclusionSmall, but significant reductions in the volume of both the caudate and putamen occur in PD brains. These reductions are independent of the effects of age and gender, however the relation of these reductions to the functional loss of dopamine, which is characteristic of PD, remains unclear.

Comparing cerebral perfusion in Alzheimer's disease and Parkinson's disease dementia: an ASL-MRI study

Emerging evidence suggests that Alzheimers disease (AD) and Parkinsons disease dementia (PDD) share neurodegenerative mechanisms. We sought to directly compare cerebral perfusion in these two conditions using arterial spin labeling magnetic resonance imaging (ASL-MRI). In total, 17 AD, 20 PDD, and 37 matched healthy controls completed ASL and structural MRI, and comprehensive neuropsychological testing. Alzheimers disease and PDD perfusion was analyzed by whole-brain voxel-based analysis (to assess absolute blood flow), a priori specified region of interest analysis, and principal component analysis (to generate a network differentiating the two groups). Corrections were made for cerebral atrophy, age, sex, education, and MRI scanner software version. Analysis of absolute blood flow showed no significant differences between AD and PDD. Comparing each group with controls revealed an overlapping, posterior pattern of hypoperfusion, including posterior cingulate gyrus, precuneus, and occipital regions. The perfusion network that differentiated AD and PDD groups identified relative differences in medial temporal lobes (AD < PDD) and right frontal cortex (PDD < AD). In conclusion, the pattern of cerebral hypoperfusion is very similar in AD and PDD. This suggests closely linked mechanisms of neurodegeneration mediating the evolution of dementia in both conditions.

Metabolite ratios in the posterior cingulate cortex do not track cognitive decline in Parkinson's disease in a clinical setting

INTRODUCTION Parkinsons Disease (PD) is classified as a motor disorder, but most patients develop cognitive impairment, and eventual dementia (PDD). Predictive neurobiomarkers may be useful in the identification of those patients at imminent risk of PDD. Given the compromised cerebral integrity in PDD, we investigated whether brain metabolites track disease progression over time. METHODS Proton Magnetic Resonance Spectroscopy (MRS) was used to identify brain metabolic changes associated with cognitive impairment and dementia in PD. Forty-nine healthy participants and 130 PD patients underwent serial single voxel proton MRS and neuropsychological testing. At baseline patients were classified as either having normal cognitive status (PDN, n = 77), mild cognitive impairment (PDMCI, n = 33), or dementia (PDD, n = 20). Posterior cingulate cortex (PCC) was examined to quantify N-acetylaspartate (NAA), choline (Cho), creatine (Cr), and myo-inositol (mI). A hierarchical Bayesian model was used to assess whether cognitive ability and other covariates were related to baseline MRS values and changes in MRS over time. RESULTS At baseline, relative to controls, PDD had significantly decreased NAA/Cr and increased Cho/Cr. However, these differences did not remain significant after accounting for age, sex, and MDS-UPDRS III. At follow-up, no significant changes in MRS metabolite ratios were detected, with no relationship found between MRS measures and change in cognitive status. CONCLUSIONS Unlike Alzheimers disease, single voxel MR spectroscopy of the PCC failed to show any significant association with cognitive status at baseline or over time. This suggests that MRS of PCC is not a clinically useful biomarker for tracking or predicting cognitive impairment in Parkinsons disease.

Tracking Parkinson's Disease Over One Year with Multimodal Magnetic Resonance Imaging in a Group of Older Patients with Moderate Disease

Background & Objectives Cross-sectional magnetic resonance imaging (MRI) suggests that Parkinson’s disease (PD) is associated with changes in cerebral tissue volume, diffusion tensor imaging metrics, and perfusion values. Here, we performed a longitudinal multimodal MRI study—including structural, diffusion tensor imaging (DTI), and perfusion MRI—to investigate progressive brain changes over one year in a group of older PD patients at a moderate stage of disease. Methods Twenty-three non-demented PD (mean age (SD) = 69.5 (6.4) years, disease duration (SD) = 5.6 (4.3) years) and 23 matched control participants (mean age: 70.6 (6.8)) completed extensive neuropsychological and clinical assessment, and multimodal 3T MRI scanning at baseline and one year later. We used a voxel-based approach to assess change over time and group-by-time interactions for cerebral structural and perfusion metrics. Results Compared to controls, in PD participants there was localized grey matter atrophy over time in bilateral inferior and right middle temporal, and left orbito-frontal cortices. Using a voxel-based approach that focused on the centers of principal white matter tracts, the PD and control cohorts exhibited similar levels of change in DTI metrics. There was no significant change in perfusion, cognitive, or motor severity measures. Conclusions In a cohort of older, non-demented PD participants, macrostructural MRI detected atrophy in the PD group compared with the control group in temporal and orbito-frontal cortices. Changes in diffusion MRI along principal white matter tracts over one year were found, but this was not differentially affected by PD.

General Functional Connectivity: shared features of resting-state and task fMRI drive reliable individual differences in functional brain networks

Intrinsic connectivity, commonly measured using resting-state fMRI, has emerged as a fundamental feature of the brain. However, largely due to practical limitations, many studies do not collect enough resting-state data to generate reliable measures of intrinsic connectivity necessary for studying individual differences. Here we present general functional connectivity (GFC) as a method for leveraging shared features across resting-state and task fMRI and demonstrate that GFC is substantially more reliable than intrinsic connectivity estimated from typically available resting-state data alone (i.e., 5-10 minutes). We further demonstrate that the increase in reliability gained through GFC boosts predictive utility by accounting for upwards of 200% more variance in the domain of intelligence. Our work suggests that GFC represents an opportunity to improve the reliability and predictive utility of fMRI for mapping individual differences, and that collection of resting-state and task scans need not be a zero-sum competition when designing future studies.