Faculty Bibliography

OBJECTIVE: To determine whether post Lyme syndrome (PLS) is antibiotic responsive. METHODS: The authors conducted a single-center randomized double-masked placebo-controlled trial on 55 patients with Lyme disease with persistent severe fatigue at least 6 or more months after antibiotic therapy. Patients were randomly assigned to receive 28 days of IV ceftriaxone or placebo. The primary clinical outcomes were improvement in fatigue, defined by a change of 0.7 points or more on an 11-item fatigue questionnaire, and improvement in cognitive function (mental speed), defined by a change of 25% or more on a test of reaction time. The primary laboratory outcome was an experimental measure of CSF infection, outer surface protein A (OspA). Outcome data were collected at the 6-month visit. RESULTS: Patients assigned to ceftriaxone showed improvement in disabling fatigue compared to the placebo group (rate ratio, 3.5; 95% CI, 1.50 to 8.03; p = 0.001). No beneficial treatment effect was observed for cognitive function or the laboratory measure of persistent infection. Four patients, three of whom were on placebo, had adverse events associated with treatment, which required hospitalization. CONCLUSIONS: Ceftriaxone therapy in patients with PLS with severe fatigue was associated with an improvement in fatigue but not with cognitive function or an experimental laboratory measure of infection in this study. Because fatigue (a nonspecific symptom) was the only outcome that improved and because treatment was associated with adverse events, this study does not support the use of additional antibiotic therapy with parenteral ceftriaxone in post-treatment, persistently fatigued patients with PLS.

OBJECTIVE: To relate neuropsychological performance to measures of cerebral injury in persons with MS selected for cognitive impairment. METHODS: Participants were 37 individuals with relapsing-remitting (59.5%) and secondary progressive (40.5%) MS. They were tested at baseline as part of a clinical trial to enhance cognition with an acetylcholinesterase inhibitor. Eligibility criteria included at least mild cognitive impairment on a verbal learning and memory task. A modified Brief Repeatable Battery of Neuropsychological Tests formed the core of the behavioral protocol. Neuroimaging measures were central (ventricular) cerebral atrophy, lesion volume, and ratios of N-acetyl aspartate (NAA) to both creatine and choline. RESULTS: A clear, consistent relation was found between cognitive and MR measures. Among neuroimaging measures, central atrophy displayed the highest correlations with cognition, accounting for approximately half the variance in overall cognitive performance. NAA ratios in right hemisphere sites displayed larger correlations than those on the left. Multiple regression models combining the MR measures accounted for well over half the variance in overall cognitive performance. The Symbol Digit Modalities Test was the neuropsychological task most strongly associated with the neuroimaging variables. CONCLUSIONS: If a strong and stable association can be firmly established between cognitive and MR variables in appropriate subsets of MS patients, it might aid in the investigation of interventions to enhance cognition and modify the course of the disease

The objective of this study was to determine the clinical characteristics of multiple sclerosis (MS) in African American (AA) patients in the New York State Multiple Sclerosis Consortium (NYSMSC) patient registry. The NYSMSC is a group of 18 MS centers throughout New York State organized to prospectively assess clinical characteristics of MS patients. AAs comprise 6% (329) of the total NYSMSC registrants (5602). Demographics, disease course, therapy, and socioeconomic status were compared in AA registrants versus nonAfrican Americans (NAA). There was an increased female preponderance and a significantly younger age at diagnosis in the AA group. AA patients were more likely to have greater disability with increased disease duration. No differences were seen in types of MS and use of disease modifying therapies. Our findings suggest a racial influence in MS. Further genetic studies that consider race differences are warranted to elucidate mechanisms of disease susceptibility

Fatigue is a common disabling symptom of multiple sclerosis (MS). It is often considered a state of exhaustion distinct from depressed mood or physical weakness. Fatigue can be assessed by either self-report scales or performance-based measures; however, neither method captures all features of fatigue. Fatigue in MS frequently leads to unemployment. It is associated with a sense of loss of control over one's environment, low positive affect, psychological distress and neurological impairment. To date there is no reproducible neuroimaging marker or biological correlate that has been identified. Proposed pathological mechanisms of fatigue in MS include neuronal factors such as dysfunction of premotor, limbic, basal ganglia or hypothalamic areas; disruption of the neuroendrocrine axis leading to low arousal; alteration in serotoninergic pathways; changes in neurotransmitter levels; and altered CNS functioning caused by a disruption of the immune response. Treatment of fatigue is best approached in a multidisciplinary fashion that incorporates nonpharmacological interventions as well as medication. Amantadine and modafinil are among the most commonly used medications for fatigue associated with MS. Both medications have been studied with positive results in controlled clinical trials. Additional research towards measurement and pathogenesis of fatigue will hopefully lead to improved therapies.

We present an automatic mixture-based algorithm for segmentation of brain tissues (white and gray matters-WM and GM), cerebral spinal fluid (CSF), and brain lesions to quantitatively analyze multiple sclerosis. The method performs intensity-based tissue classification using multispectral magnetic resonance (MR) images based on a stochastic model. With the existence of white Gaussian noise and spatially invariant blurring in acquired MR images, a Karhunen-Loeve (K-L) domain Wiener filter is applied for accurate noise reduction and resolution restoration on blurred and noisy images to minimize the partial volume effect (PVE), which is a major limiting factor for the quantitative analysis. Following that, we utilize a Markov random field Gibbs model to integrate the local spatial information into the well-established expectation-maximization model-fitting algorithm. Each voxel is then classified by a maximum a posterior (MAP) criterion, indicating its probabilities of belonging to each class, i.e., each voxel is labeled as a mixel with different tissue percentages, leading to further minimization of the PVE. The volumes of WM, GM, CSF, and brain lesions are extracted from the mixture-based segmentation and the corresponding brain atrophies are computed. In this study, we have investigated the accuracy and repeatability of the algorithm with inclusion of noise analysis and point spread function for image resolution enhancement. Experimental results on phantom, healthy volunteer, and patient studies are presented.