Improved spatial speckle contrast model for tissue blood flow imaging: effects of spatial correlation among neighboring camera pixels.

Significance: Speckle contrast analysis is the basis of laser speckle imaging (LSI), a simple, inexpensive, noninvasive technique used in various fields of medicine and engineering. A common application of LSI is the measurement of tissue blood flow. Accurate measurement of speckle contrast is essential to correctly measure blood flow. Variables, such as speckle grain size and camera pixel size, affect the speckle pattern and thus the speckle contrast. Aim: We studied the effects of spatial correlation among adjacent camera pixels on the resulting speckle contrast values. Approach: We derived a model that accounts for the potential correlation of intensity values in the common experimental situation where the speckle grain size is larger than the camera pixel size. In vitro phantom experiments were performed to test the model. Results: Our spatial correlation model predicts that speckle contrast first increases, then decreases as the speckle grain size increases relative to the pixel size. This decreasing trend opposes what is observed with a standard speckle contrast model that does not consider spatial correlation. Experimental data are in good agreement with the predictions of our spatial correlation model. Conclusions: We present a spatial correlation model that provides a more accurate measurement of speckle contrast, which should lead to improved accuracy in tissue blood flow measurements. The associated correlation factors only need to be calculated once, and open-source software is provided to assist with the calculation.

Spatial versus temporal laser speckle contrast analyses in the presence of static optical scatterers.

Previously published data demonstrate that the temporal processing algorithm for laser speckle contrast imaging (LSCI) can improve the visibility of deep blood vessels and is less susceptible to static speckle artifacts when compared with the spatial algorithm. To the best of our knowledge, the extent to which the temporal algorithm can accurately predict the speckle contrast associated with flow in deep blood vessels has not been quantified. Here, we employed two phantom systems and imaging setups (epi-illumination and transillumination) to study the contrast predicted by the spatial and temporal algorithms in subsurface capillary tubes as a function of the camera exposure time and the actual flow speed. Our data with both imaging setups suggest that the contrast predicted by the temporal algorithm, and therefore the relative flow speed, is nearly independent of the degree of static optical scattering that contributes to the overall measured speckle pattern. Collectively, these results strongly suggest the potential of temporal LSCI at a single-exposure time to assess accurately the changes in blood flow even in the presence of substantial static optical scattering.