Random process estimator for laser speckle imaging of cerebral blood flow

Abstract

In this paper, we develop a random process theory to explain the laser speckle phenomena. The relation between the probability distribution of speckle’s integrated intensity random process Y(t) and the relative velocity v(t) is derived. Based on the random process theory, traditional spatial or temporal laser speckle contrast analysis (i.e. spatial or temporal LASCA) can be derived as the spatial or temporal estimators respectively. Both spatial LASCA and temporal LASCA suffer from noise due to insufficient statistics and nonstationarity in either spatial or temporal domain. Furthermore, either LASCA results in a reduction of spatial or temporal resolution. A new random process estimator is proposed and able to overcome these drawbacks. In an in-vitro study, random process estimator outperforms either spatial LASCA or temporal LASCA by providing much higher SNR (random process estimator vs. spatial LASCA vs. temporal LASCA: 33.64±6.87 ( mean±s.t.d.) vs. 9.08±2.85 vs. 3.83±1.05). In an in-vivo structural imaging study, random process estimator efficiently suppresses the noise in contrast image and thus improves the distinguishability of small vessels. In a functional imaging study of cerebral blood flow change in the somatosensory cortex induced by rat’s hind paw stimulation, random process estimator provides much lower estimation errors in single trial data (random process estimator vs. temporal LASCA: 0.31±0.03 vs. 1.36±0.09) and finally leads to higher resolution spatiotemporal patterns of cerebral blood flow.

Rescue of cortical neurovascular functions during the hyperacute phase of ischemia by peripheral sensory stimulation

“…Compared with DOI, LSI demonstrates a higher spatial resolution of blood flow responses but limited penetration (0.5-0.8 mm only) (Liao et al, 2013). Thus, the perfusion-and metabolism-related data can only be evaluated in the superficial layers of the cortex, which is insufficient for assessing the progressive changes in the ischemic region during the entire hyperacute phase of ischemia Liao et al, 2013;Luckl et al, 2010;Miao et al, 2010;Zhang et al, 2006). Functional magnetic resonance imaging (fMRI) provides noninvasive large-scale measurements of neural functions and can precisely distinguish both stroke mimics and small lesions in cerebral ischemia (Tatlisumak, 2002;Vymazal et al, 2012).…”

Review of near-infrared methods for wound assessment

“…[76][77][78] Red blood cells are efficient light scattering centers within tissue so the resulting speckle patterns from perfused tissue contain information about blood flow in the form of speckle variance or blur. However, as discussed above, to extract blood flow measurements from the speckle statistics requires knowledge of the underlying velocity distribution, the fraction of moving scattering centers, and the degree of multiple scattering.…”

The Adipose-Derived Lineage-Negative Cells Are Enriched Mesenchymal Stem Cells and Promote Limb Ischemia Recovery in Mice

“…The principle of laser speckle imaging (LSI) has been previously described [25][26][27]. The LSCI-2 is a 21 · 18 · 21-cm portable instrument and is connected to a computer equipped with real-time data acquisition software (LSCI data processing system).…”