Jörn Peuser, Andreas Völker, Pavel Zakharov, Frank Scheffold, Abderraouf Belhaj-Saif, Adjia Hamadjida, Eric Schmidlin, Anne-Dominique Gindrat, Eric Rouiller, Henri-Macel Hoogewoud
The nonhuman primate model is suitable to study mechanisms of functional recovery following lesion of the cerebral cortex (motor cortex), on which therapeutic strategies can be tested. To interpret behavioral data (time course and extent of functional recovery), it is crucial to monitor the properties of the experimental cortical lesion, induced by infusion of the excitotoxin ibotenic acid. In two adult macaque monkeys, ibotenic acid infusions produced a restricted, permanent lesion of the motor cortex. In one monkey, the lesion was monitored over 3.5 weeks, combining laser speckle imaging (LSI) as metabolic readout (cerebral blood flow) and anatomical assessment with magnetic resonance imaging (T2-weighted MRI). The cerebral blood flow, measured online during subsequent injections of the ibotenic acid in the motor cortex, exhibited a dramatic increase, still present after one week, in parallel to a MRI hypersignal. After 3.5 weeks, the cerebral blood flow was strongly reduced (below reference level) and the hypersignal disappeared from the MRI scan, although the lesion was permanent as histologically assessed post-mortem. The MRI data were similar in the second monkey. Our experiments suggest that LSI and MRI, although they reflect different features, vary in parallel during a few weeks following an excitotoxic cortical lesion.
We discuss a new approach to laser speckle biomedical imaging with the goal to establish a quantitative link between the
measured signal and the local dynamic properties of Brownian motion or blood flow. We demonstrate that the presence of a
static component in laser speckle imaging signal can significantly complicate the quantitative interpretation of the imaging
data. With Monte-Carlo simulations and model experiments we show that the error in the mean particles velocity extracted
using traditional approaches can reach several orders of magnitude. With a proper data treatment on the other side the error
can be substantially reduced. We suggest a simple data processing scheme that properly accounts for a static component in
the scattered light intensity.
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