Automated brainstem volumetry can aid in the diagnostics of parkinsonian disorders.

INTRODUCTION: Separating progressive supranuclear palsy (PSP) from Parkinson's disease (PD) and multiple system atrophy (MSA) is often challenging in early disease but is important for appropriate management. Magnetic resonance imaging (MRI) can aid the diagnostics and manual 2D measurements are often used. However, new fully automatic brainstem volumetry could potentially be more accurate and increase availability of brainstem metrics. METHODS: Clinical 3D T1-weighted MRI were obtained from 196 consecutive patients; 29 PSP, 27 MSA, 140 PD. Midbrain-pons ratio and magnetic resonance parkinsonism index (MRPI) 1.0 and 2.0 were manually calculated, and intra-rater and inter-rater reliability was assessed. FreeSurfer was used to automatically segment brainstem substructures, normalized to the intracranial volume. The robustness of the automated analysis was evaluated in 3 healthy controls. The diagnostic accuracy of the brainstem biomarkers was assessed using receiver operating characteristic curves. RESULTS: Automatic brainstem volumetry had good repeatability/reproducibility with intra-scanner coefficient of variation 0.3-5.5% and inter-scanner coefficient of variation 0.9-8.4% in the different brainstem regions. Midbrain volume performs better than planimetric measurements in separating PSP from PD (Area under the curve (AUC) 0.90 compared with 0.81 for midbrain-pons ratio (p = 0.019), 0.77 for MRPI 1.0 (p = 0.007) and 0.81 for MRPI 2.0 (p = 0.021)). Midbrain volume performed on par with planimetry for separation between PSP and MSA. CONCLUSION: Automatic brainstem segmentation is robust and shows promising diagnostic performance in separating PSP from PD and MSA. If further developed, it could play a role in diagnosing PSP and could potentially be used as an outcome in clinical trials.

An unusual cause of fatal rapid-onset ataxia plus syndrome.

BACKGROUND: Progressive multifocal leukoencephalopathy (PML) is a demyelinating disorder of the central nervous system caused by reactivation of the JC-virus and is in most cases associated with underlying immunosuppression. Acquired immune deficiency syndrome (AIDS) and hematological malignancies are well-known predisposing factors for PML. However, in the past ten years, various pharmacological agents have been associated with increased risk of PML. Based on the phenomenology PML can be divided into the cerebral form and the rare cerebellar form. CASE PRESENTATION: Here we describe a man affected by polycythemia vera (PCV) that was treated with hydroxyurea (HU) and developed PML. The initially PML presentation included ataxia as one of the main features. Brain MRI displayed widespread supratentorial and infratentorial lesions. Immunological analysis revealed absence of reactivity to a wide range of antigens. The course of disease was rapidly progressive with fatal outcome - autopsy ruled out leukemic transformation. CONCLUSION: The occurrence of PML in PCV patients is very rare and has been reported only once. Movement disorders, such as ataxia, are also less frequent. In the present case the PML was likely multifactorial.

Post mTBI fatigue is associated with abnormal brain functional connectivity.

This study set out to investigate the behavioral correlates of changes in resting-state functional connectivity before and after performing a 20 minute continuous psychomotor vigilance task (PVT) for patients with chronic post-concussion syndrome. Ten patients in chronic phase after mild traumatic brain injury (mTBI) with persisting symptoms of fatigue and ten matched healthy controls participated in the study. We assessed the participants' fatigue levels and conducted resting-state fMRI before and after a sustained PVT. We evaluated the changes in brain functional connectivity indices in relation to the subject's fatigue behavior using a quantitative data-driven analysis approach. We found that the PVT invoked significant mental fatigue and specific functional connectivity changes in mTBI patients. Furthermore, we found a significant linear correlation between self-reported fatigue and functional connectivity in the thalamus and middle frontal cortex. Our findings indicate that resting-state fMRI measurements may be a useful indicator of performance potential and a marker of fatigue level in the neural attentional system.