A new way of rapidly screening for depression in multiple sclerosis using Emotional Thermometers.

OBJECTIVE: Depression is a common, serious, but under-recognised problem in multiple sclerosis (MS). The primary objective of this study was to assess whether a rapid visual analogue screening tool for depression could operate as a quick and reliable screening method for depression, in patients with MS. METHOD: Patients attending a regional MS outpatient clinic completed the Emotional Thermometer 7 tool (ET7), the Hospital Anxiety and Depression Scale - Depression Subscale (HADS-D) and the Major Depression Inventory (MDI) to establish a Diagnostic and Statistical Manual, 4th edition (DSM-IV) diagnosis of Major Depression. Full ET7, briefer subset ET4 version and depression and distress thermometers alone were compared with HADS-D and MDI. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and receiver operating characteristic (ROC) curve were calculated to compare the performance of all the screening tools. RESULTS: In total, 190 patients were included. ET4 performed well as a 'rule-out' screening step (sensitivity 0.91, specificity 0.72, NPV 0.98, PPV 0.32). ET4 performance was comparable to HADS-D (sensitivity 0.96, specificity 0.77, NPV 0.99, PPV 0.37) without need for clinician scoring. The briefer ET4 performed as well as the full ET7. CONCLUSION: ET are quick, sensitive and useful screening tools for depression in this MS population, to be complemented by further questioning or more detailed psychiatric assessment where indicated. Given that ET4 and ET7 perform equally well, we recommend the use of ET4 as it is briefer. It has the potential to be widely implemented across busy neurology clinics to assist in depression screening in this under diagnosed group.

Automated, high accuracy classification of Parkinsonian disorders: a pattern recognition approach.

Progressive supranuclear palsy (PSP), multiple system atrophy (MSA) and idiopathic Parkinson's disease (IPD) can be clinically indistinguishable, especially in the early stages, despite distinct patterns of molecular pathology. Structural neuroimaging holds promise for providing objective biomarkers for discriminating these diseases at the single subject level but all studies to date have reported incomplete separation of disease groups. In this study, we employed multi-class pattern recognition to assess the value of anatomical patterns derived from a widely available structural neuroimaging sequence for automated classification of these disorders. To achieve this, 17 patients with PSP, 14 with IPD and 19 with MSA were scanned using structural MRI along with 19 healthy controls (HCs). An advanced probabilistic pattern recognition approach was employed to evaluate the diagnostic value of several pre-defined anatomical patterns for discriminating the disorders, including: (i) a subcortical motor network; (ii) each of its component regions and (iii) the whole brain. All disease groups could be discriminated simultaneously with high accuracy using the subcortical motor network. The region providing the most accurate predictions overall was the midbrain/brainstem, which discriminated all disease groups from one another and from HCs. The subcortical network also produced more accurate predictions than the whole brain and all of its constituent regions. PSP was accurately predicted from the midbrain/brainstem, cerebellum and all basal ganglia compartments; MSA from the midbrain/brainstem and cerebellum and IPD from the midbrain/brainstem only. This study demonstrates that automated analysis of structural MRI can accurately predict diagnosis in individual patients with Parkinsonian disorders, and identifies distinct patterns of regional atrophy particularly useful for this process.

Diffusion tensor imaging in sporadic and familial (D90A SOD1) forms of amyotrophic lateral sclerosis.

BACKGROUND: The basis of heterogeneity in the clinical presentation and rate of progression of amyotrophic lateral sclerosis (ALS) is poorly understood. OBJECTIVES: To use diffusion tensor imaging as a measure of axonal pathologic features in vivo in ALS and to compare a homogeneous form of familial ALS (homozygous D90A SOD1 [superoxide dismutase 1]) with sporadic ALS. DESIGN: Cross-sectional diffusion tensor imaging study. SETTING: Tertiary referral neurology clinic. PATIENTS: Twenty patients with sporadic ALS, 6 patients with homozygous D90A SOD1 ALS, and 21 healthy control subjects. MAIN OUTCOME MEASURE: Fractional anisotropy in cerebral white matter. RESULTS: Patients with homozygous D90A SOD1 ALS showed less extensive pathologic white matter in motor and extramotor pathways compared with patients with sporadic ALS, despite similar disease severity assessed clinically using a standard functional rating scale. Fractional anisotropy correlated with clinical measures of severity and upper motor neuron involvement. CONCLUSION: In vivo diffusion tensor imaging measures demonstrate differences in white matter degeneration between sporadic ALS and a unique familial form of the disease, indicating that genotype influences the distribution of cerebral pathologic features in ALS.

A longitudinal study of diffusion tensor MRI in ALS.

In this study, we investigated whether diffusion tensor MRI (DTI) could detect progressive corticospinal tract degeneration in amyotrophic lateral sclerosis (ALS) and whether changes in diffusion variables reflected clinical deterioration. Twenty-three ALS patients and 25 healthy volunteers underwent whole brain DTI. Patients and a subset (n = 12) of controls returned for a second scan. Clinical measures of disease severity were assessed in the ALS group. Changes in fractional anisotropy (FA) and mean diffusivity (MD) were measured along the corticospinal tract using a region of interest approach. Adequate DTI data were available in 11 ALS patients and 11 controls at two time points. FA and MD differed significantly between ALS patients and controls at both time points, but neither changed significantly over time, while global measures of disease severity in patients increased with time. Although we confirmed that DTI detects corticospinal tract damage in ALS, there were no significant changes in diffusion measures over time. The sensitivity of DTI may be improved by advanced data analysis techniques, although the high dropout rate suggests that use of MRI as a biomarker in ALS may be restricted to earlier stages of disease.

Cortical activation during motor imagery is reduced in Amyotrophic Lateral Sclerosis.

The neural correlates of motor execution in Amyotrophic Lateral Sclerosis (ALS) are challenging to investigate due to muscle weakness. Alternatives to traditional motor execution paradigms are therefore of great interest. This study tested the hypothesis that patients with Amyotrophic Lateral Sclerosis (ALS) would show increased cortical activation during motor imagery compared to healthy controls, as seen in studies of motor execution. Functional MRI was used to measure activation during a block design paradigm contrasting imagery of right hand movements against rest in 16 patients with ALS and 17 age-matched healthy controls. Patients with ALS showed reduced activation during motor imagery in the left inferior parietal lobule, and in the anterior cingulate gyrus and medial pre-frontal cortex. This reduction in cortical activation during motor imagery contrasts with the pattern seen during motor execution. This may represent the disruption of normal motor imagery networks by ALS pathology outside the primary motor cortex.