A Specific Pattern of Routine Cerebrospinal Fluid Parameters Might Help to Identify Cases of West Nile Virus Neuroinvasive Disease.

BACKGROUND: Viral meningitis/encephalitis (ME) is a rare but potentially harmful disease. The prompt identification of the respective virus is important to guide not only treatment but also potential public health countermeasures. However, in about 40% of cases, no virus is identified despite an extensive diagnostic workup. The aim of the present study was to analyze demographic, seasonal, and routine cerebrospinal fluid (CSF) parameters in cases of viral ME and assess their utility for the prediction of the causative virus. METHODS: Demographic data, season, and routine CSF parameters (total leucocytes, CSF cell differentiation, age-adjusted CSF/serum albumin ratio, and total immunoglobulin ratios) were retrospectively assessed in cases of viral ME. RESULTS: In total, 156 cases of acute viral ME (74 female, median age 40.0 years) were treated at a tertiary-care hospital in Germany. Specific viral infections were detected in 93 (59.6%) cases. Of these, 14 (9.0%) cases were caused by herpes simplex virus (HSV), 36 (23.1%) by varicella-zoster virus (VZV), 27 (17.3%) by enteroviruses, 9 (5.8%) by West Nile virus (WNV), and 7 (4.5%) by other specific viruses. Additionally, 64 (41.0%) cases of ME of unknown viral etiology were diagnosed. Cases of WNV ME were older, predominantly male, showed a severe disruption of the blood-CSF-barrier, a high proportion of neutrophils in CSF, and an intrathecal total immunoglobulin M synthesis in the first CSF sample. In a multinominal logistic regression analysis, the accuracy of these CSF parameters together with age and seasonality was best for the prediction of WNV (87.5%), followed by unknown viral etiology (66.7%), VZV (61.8%), and enteroviruses (51.9%). CONCLUSIONS: Cases with WNV ME showed a specific pattern of routine CSF parameters and demographic data that allowed for their identification with good accuracy. These findings might help to guide the diagnostic workup in cases with viral ME, in particular allowing the timely identification of cases with ME due to WNV.

Measuring the iron content of dopaminergic neurons in substantia nigra with MRI relaxometry.

In Parkinson's disease, the depletion of iron-rich dopaminergic neurons in nigrosome 1 of the substantia nigra precedes motor symptoms by two decades. Methods capable of monitoring this neuronal depletion, at an early disease stage, are needed for early diagnosis and treatment monitoring. Magnetic resonance imaging (MRI) is particularly suitable for this task due to its sensitivity to tissue microstructure and in particular, to iron. However, the exact mechanisms of MRI contrast in the substantia nigra are not well understood, hindering the development of powerful biomarkers. In the present report, we illuminate the contrast mechanisms in gradient and spin echo MR images in human nigrosome 1 by combining quantitative 3D iron histology and biophysical modeling with quantitative MRI on post mortem human brain tissue. We show that the dominant contribution to the effective transverse relaxation rate (R2*) in nigrosome 1 originates from iron accumulated in the neuromelanin of dopaminergic neurons. This contribution is appropriately described by a static dephasing approximation of the MRI signal. We demonstrate that the R2* contribution from dopaminergic neurons reflects the product of cell density and cellular iron concentration. These results demonstrate that the in vivo monitoring of neuronal density and iron in nigrosome 1 may be feasible with MRI and provide directions for the development of biomarkers for an early detection of dopaminergic neuron depletion in Parkinson's disease.