ABSTRACT
BACKGROUND AND PURPOSE: Dementia in Parkinson's disease (PD) is common and disabling. Identification of modifiable risk factors for it is essential. Vascular risk factors (VRFs) may be associated with cognitive decline in early PD. Biomarkers that serve as surrogates of the long-term effect of VRFs on PD are needed. To that end, we aimed to quantitate white matter hyperintensities (WMH) in early PD, measure associations with VRFs and examine relationships between WMH and longitudinal cognition. METHODS: Participants in the Parkinson's Progression Markers Initiative study (141 patients with PD, 63 healthy controls) with adequate baseline structural brain magnetic resonance imaging data were included. Hypertension and diabetes history, and body mass index were combined to create a vascular risk score. WMH were quantitated via automated methods. Cognition was assessed annually with a comprehensive test battery. RESULTS: In the PD group, vascular risk score was associated with WMH for total brain (ß = 0.210; P = 0.021), total white matter (ß = 0.214; P = 0.013), frontal (ß = 0.220; P = 0.002) and temporal (ß = 0.212; P = 0.002) regions. Annual rate of change in global cognition was greater in those with higher vascular risk score (ß = -0.040; P = 0.007) and greater WMH (ß = -0.029; P = 0.049). Higher temporal WMH burden was associated with great decline over time in verbal memory (ß = -0.034; P = 0.031). CONCLUSIONS: In early PD, modifiable VRFs are associated with WMH on brain magnetic resonance imaging. Temporal WMH burden predicts decline in verbal memory. WMH may serve as a surrogate marker for the effect of VRFs on cognitive abilities in PD.
Subject(s)
Brain/pathology , Cognition Disorders/etiology , Cognition/physiology , Cognitive Dysfunction/etiology , Leukoencephalopathies/etiology , Parkinson Disease/complications , White Matter/pathology , Aged , Cognition Disorders/pathology , Cognition Disorders/psychology , Cognitive Dysfunction/pathology , Cognitive Dysfunction/psychology , Disease Progression , Female , Humans , Leukoencephalopathies/pathology , Leukoencephalopathies/psychology , Magnetic Resonance Imaging , Male , Middle Aged , Neuropsychological Tests , Parkinson Disease/pathology , Parkinson Disease/psychology , Risk FactorsABSTRACT
OBJECTIVE: In adulthood, the diagnosis of attention-deficit/hyperactivity disorder (ADHD) has been subject of recent controversy. We searched for a neuroanatomical signature associated with ADHD spectrum symptoms in adults by applying, for the first time, machine learning-based pattern classification methods to structural MRI and diffusion tensor imaging (DTI) data obtained from stimulant-naïve adults with childhood-onset ADHD and healthy controls (HC). METHOD: Sixty-seven ADHD patients and 66 HC underwent high-resolution T1-weighted and DTI acquisitions. A support vector machine (SVM) classifier with a non-linear kernel was applied on multimodal image features extracted on regions of interest placed across the whole brain. RESULTS: The discrimination between a mixed-gender ADHD subgroup and individually matched HC (n = 58 each) yielded area-under-the-curve (AUC) and diagnostic accuracy (DA) values of up to 0.71% and 66% (P = 0.003) respectively. AUC and DA values increased to 0.74% and 74% (P = 0.0001) when analyses were restricted to males (52 ADHD vs. 44 HC). CONCLUSION: Although not at the level of clinically definitive DA, the neuroanatomical signature identified herein may provide additional, objective information that could influence treatment decisions in adults with ADHD spectrum symptoms.
Subject(s)
Attention Deficit Disorder with Hyperactivity/diagnosis , Attention Deficit Disorder with Hyperactivity/physiopathology , Brain/diagnostic imaging , Brain/physiopathology , Magnetic Resonance Imaging/methods , Support Vector Machine , Adult , Diffusion Tensor Imaging/methods , Female , Humans , Male , NeurobiologyABSTRACT
BACKGROUND: Diffusion tensor imaging (DTI) studies have consistently shown white matter (WM) microstructural abnormalities in schizophrenia. Whether or not such alterations could vary depending on clinical status (i.e. acute psychosis v. remission) remains to be investigated. METHODS: Twenty-five treatment-naïve first-episode psychosis (FEP) patients and 51 healthy-controls (HC) underwent MRI scanning at baseline. Twenty-one patients were re-scanned as soon as they achieved sustained remission of symptoms; 36 HC were also scanned twice. Rate-of-change maps of longitudinal DTI changes were calculated for in order to examine WM alterations associated with changes in clinical status. We conducted voxelwise analyses of fractional anisotropy (FA) and trace (TR) maps. RESULTS: At baseline, FEP presented reductions of FA in comparison with HC [p < 0.05, false-discovery rate (FDR)-corrected] affecting fronto-limbic WM and associative, projective and commissural fasciculi. After symptom remission, patients showed FA increase over time (p < 0.001, uncorrected) in some of the above WM tracts, namely the right anterior thalamic radiation, right uncinate fasciculus/inferior fronto-occipital fasciculus, and left inferior fronto-occipital fasciculus/inferior longitudinal fasciculus. We also found significant correlations between reductions in PANSS scores and FA increases over time (p < 0.05, FDR-corrected). CONCLUSIONS: WM changes affecting brain tracts critical to the integration of perceptual information, cognition and emotions are detectable soon after the onset of FEP and may partially reverse in direct relation to the remission of acute psychotic symptoms. Our findings reinforce the view that WM abnormalities in brain tracts are a key neurobiological feature of acute psychotic disorders, and recovery from such WM pathology can lead to amelioration of symptoms.