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  • Multicenter evaluation of neurofilaments in early symptom onset amyotrophic lateral sclerosis.

    7 May 2018

    OBJECTIVE: To examine neurofilament (Nf) concentrations according to symptom onset and clinical diagnostic certainty categories of amyotrophic lateral sclerosis (ALS). METHODS: We measured Nf light chain (NfL) and phosphorylated Nf heavy chain (pNfH) CSF and NfL serum levels in patients with ALS with first symptom onset ≤6 months (n = 54) or >6 months (n = 135) from sampling, and patients with other neurologic diseases, differential diagnoses of a motor neuron disease (MND mimics), and other MND variants to determine the diagnostic accuracy in patients with ALS with early symptom onset. Samples were received multicentric and analyzed by ELISA and Simoa platform and related to other clinical measures. RESULTS: NfL and pNfH in CSF and NfL in serum were increased in early and later symptomatic phase ALS (p < 0.0001). CSF and serum NfL and CSF pNfH discriminated patients with ALS with early symptom onset from those with other neurologic diseases and MND mimics with high sensitivity (94%, 88%, 98%, and 89%, 100%, 78%) and specificity (86%, 92%, 91%, and 94%, 90%, 98%) and did not vary between clinical diagnostic categories of ALS in the early symptomatic phase group. Baseline NfL and pNfH levels were not significantly different in patients with ALS with clinical progression to definite or probable ALS at follow-up. CONCLUSION: The measurement of Nf has potential to enhance diagnostic accuracy of ALS in those presenting soon after symptom onset, and is measurable across multiple centers. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that CSF and serum Nf concentrations discriminate ALS with early symptom onset from other neurologic diseases.

  • Functional Strength Training and Movement Performance Therapy for Upper Limb Recovery Early Poststroke-Efficacy, Neural Correlates, Predictive Markers, and Cost-Effectiveness: FAST-INdiCATE Trial.

    7 May 2018

    Background: Variation in physiological deficits underlying upper limb paresis after stroke could influence how people recover and to which physical therapy they best respond. Objectives: To determine whether functional strength training (FST) improves upper limb recovery more than movement performance therapy (MPT). To identify: (a) neural correlates of response and (b) whether pre-intervention neural characteristics predict response. Design: Explanatory investigations within a randomised, controlled, observer-blind, and multicentre trial. Randomisation was computer-generated and concealed by an independent facility until baseline measures were completed. Primary time point was outcome, after the 6-week intervention phase. Follow-up was at 6 months after stroke. Participants: With some voluntary muscle contraction in the paretic upper limb, not full dexterity, when recruited up to 60 days after an anterior cerebral circulation territory stroke. Interventions: Conventional physical therapy (CPT) plus either MPT or FST for up to 90 min-a-day, 5 days-a-week for 6 weeks. FST was "hands-off" progressive resistive exercise cemented into functional task training. MPT was "hands-on" sensory/facilitation techniques for smooth and accurate movement. Outcomes: The primary efficacy measure was the Action Research Arm Test (ARAT). Neural measures: fractional anisotropy (FA) corpus callosum midline; asymmetry of corticospinal tracts FA; and resting motor threshold (RMT) of motor-evoked potentials. Analysis: Covariance models tested ARAT change from baseline. At outcome: correlation coefficients assessed relationship between change in ARAT and neural measures; an interaction term assessed whether baseline neural characteristics predicted response. Results: 288 Participants had: mean age of 72.2 (SD 12.5) years and mean ARAT 25.5 (18.2). For 240 participants with ARAT at baseline and outcome the mean change was 9.70 (11.72) for FST + CPT and 7.90 (9.18) for MPT + CPT, which did not differ statistically (p = 0.298). Correlations between ARAT change scores and baseline neural values were between 0.199, p = 0.320 for MPT + CPT RMT (n = 27) and -0.147, p = 0.385 for asymmetry of corticospinal tracts FA (n = 37). Interaction effects between neural values and ARAT change between baseline and outcome were not statistically significant. Conclusions: There was no significant difference in upper limb improvement between FST and MPT. Baseline neural measures did not correlate with upper limb recovery or predict therapy response. Trial registration: Current Controlled Trials: ISRCT 19090862,

  • Dual regression physiological modeling of resting-state EPI power spectra: Effects of healthy aging.

    6 March 2018

    Aging and disease-related changes in the arteriovasculature have been linked to elevated levels of cardiac cycle-induced pulsatility in the cerebral microcirculation. Functional magnetic resonance imaging (fMRI), acquired fast enough to unalias the cardiac frequency contributions, can be used to study these physiological signals in the brain. Here, we propose an iterative dual regression analysis in the frequency domain to model single voxel power spectra of echo planar imaging (EPI) data using external recordings of the cardiac and respiratory cycles as input. We further show that a data-driven variant, without external physiological traces, produces comparable results. We use this framework to map and quantify cardiac and respiratory contributions in healthy aging. We found a significant increase in the spatial extent of cardiac modulated white matter voxels with age, whereas the overall strength of cardiac-related EPI power did not show an age effect.

  • Gas-free calibrated fMRI with a correction for vessel-size sensitivity.

    7 May 2018

    Calibrated functional magnetic resonance imaging (fMRI) is a method to independently measure the metabolic and hemodynamic contributions to the blood oxygenation level dependent (BOLD) signal. This technique typically requires the use of a respiratory challenge, such as hypercapnia or hyperoxia, to estimate the calibration constant, M. There has been a recent push to eliminate the gas challenge from the calibration procedure using asymmetric spin echo (ASE) based techniques. This study uses simulations to better understand spin echo (SE) and ASE signals, analytical modelling to characterize the signal evolution, and in vivo imaging to validate the modelling. Using simulations, it is shown how ASE imaging generally underestimates M and how this depends on several parameters of the acquisition, including echo time and ASE offset, as well as the vessel size. This underestimation is the result of imperfect SE refocusing due to diffusion of water through the extravascular environment surrounding the microvasculature. By empirically characterizing this SE attenuation as an exponential decay that increases with echo time, we have proposed a quadratic ASE biophysical signal model. This model allows for the characterization and compensation of the SE attenuation if SE and ASE signals are acquired at multiple echo times. This was tested in healthy subjects and was found to significantly increase the estimates of M across grey matter. These findings show promise for improved gas-free calibration and can be extended to other relaxation-based imaging studies of brain physiology.