Survival prediction models in motor neuron disease.

BACKGROUND AND PURPOSE: This study aimed to assess the predictive value of multimodal brain magnetic resonance imaging (MRI) on survival in a large cohort of patients with motor neuron disease (MND), in combination with clinical and cognitive features. METHODS: Two hundred MND patients were followed up prospectively for a median of 4.13 years. At baseline, subjects underwent neurological examination, cognitive assessment and brain MRI. Grey matter volumes of cortical and subcortical structures and diffusion tensor MRI metrics of white matter tracts were obtained. A multivariable Royston-Parmar survival model was created using clinical and cognitive variables. The increase of survival prediction accuracy provided by MRI variables was assessed. RESULTS: The multivariable clinical model included predominant upper or lower motor neuron presentations and diagnostic delay as significant prognostic predictors, reaching an area under the receiver operating characteristic curve (AUC) of a 4-year survival prediction of 0.79. The combined clinical and MRI model including selected grey matter fronto-temporal volumes and diffusion tensor MRI metrics of the corticospinal and extra-motor tracts reached an AUC of 0.89. Considering amyotrophic lateral sclerosis patients only, the clinical model including diagnostic delay and semantic fluency scores provided an AUC of 0.62, whereas the combined clinical and MRI model reached an AUC of 0.77. CONCLUSION: Our study demonstrated that brain MRI measures of motor and extra-motor structural damage, when combined with clinical and cognitive features, are useful predictors of survival in patients with MND, particularly when a diagnosis of amyotrophic lateral sclerosis is made.

Brain structural and functional signatures of impulsive-compulsive behaviours in Parkinson's disease.

This study assessed brain structural and functional alterations in patients with Parkinson's disease and impulsive-compulsive behaviours (PD-ICB) compared with controls and PD no-ICB cases. Eighty-five PD patients (35 PD-ICB) and 50 controls were recruited. All subjects underwent three-dimensional T1-weighted, diffusion tensor (DT), and resting state functional magnetic resonance imaging (RS fMRI). We assessed cortical thickness with surface-based morphometry, subcortical volumes using FIRST, DT MRI metrics using region of interest and tractography approaches, and RS fMRI using a model free approach. Compared with controls, both PD groups showed a pattern of brain structural alterations in the basal ganglia (more evident in PD no-ICB patients), sensorimotor and associative systems. Compared with PD no-ICB, PD-ICB cases showed left precentral and superior frontal cortical thinning, and motor and extramotor white matter tract damage. Compared with controls, all patients had an increased functional connectivity within the visual network. Additionally, PD no-ICB showed increased functional connectivity of bilateral precentral and postcentral gyri within the sensorimotor network compared with controls and PD-ICB. Severity and duration of PD-ICB modulated the functional connectivity between sensorimotor, visual and cognitive networks. Relative to PD no-ICB, PD-ICB patients were characterised by a more severe involvement of frontal, meso-limbic and motor circuits. These data suggest ICB in PD as the result of a disconnection between sensorimotor, associative and cognitive networks with increasing motor impairment, psychiatric symptoms, and ICB duration. These findings may have important implications in understanding the neural substrates underlying ICB in PD.