Imaging the Cerebral Blood Flow With Enhanced Laser Speckle Contrast Analysis (eLASCA) by Monotonic Point Transformation

Abstract

Laser speckle contrast analysis (LASCA) has been demonstrated as a full-field method for imaging the cerebral blood flow (CBF). However, conventional LASCA is limited to extremely low dynamic range because of the ambient background field, dark current, and other anomalies in the circuits of a charge-coupled device camera, which makes it difficult to analyze the spatiotemporal variabilities in CBF. In this study, we proposed an enhanced LASCA (eLASCA) method to improve the dynamic range of LASCA based on monotonic point transformation. In investigating the influence of moderate hypothermia (32+/-0.5 degrees C) on capillary CBF change, eLASCA presented much more significant decrease of relative CBF than LASCA (hypothermia: 189% versus 137%, postrewarming: 151% versus 119%). Statistically, eLASCA resulted in a higher confidence degree (p=0.009) of CBF change after the rewarming than LASCA (p=0.013). In addition, eLASCA greatly improves the CBF visualization, which is very helpful in demonstrating the details of CBF change.

Retooling Laser Speckle Contrast Analysis Algorithm to Enhance Non-Invasive High Resolution Laser Speckle Functional Imaging of Cutaneous Microcirculation

“…Motion-free imaging, albeit desirable, is rarely achievable in a non-invasive setting to study human functional outcomes333435. Advancements in laser optics have improved signal strength, resolution, and the frame rates333637.…”

“…Such higher resolution enabled improved visualization of microcirculation. During computation of the K maps, there is an inherent decrease in the spatial resolution35. To compensate, a 5 × 5 sized sliding window was used depending on the quality of acquired perfusion data.…”

“…In deciding the size of sliding window, there is a mathematical tradeoff where a smaller window (3 × 3) limits the statistical analysis, and a larger window (7 × 7) limits spatial resolution5051. The resolution difference in the K maps generated using spatial versus temporal statistics predisposes the need to use a sliding window operator to compute K35. Using Matlab programming platform, we report a powerful image processing tool to visualize and quantitatively assess peripheral microvascular function31.…”

“…When coherent light reflects off a surface, the rebounded speckle pattern is inherently random in both space and time, creating a Gaussian distribution of speckle intensity, with a standard deviation equal to the average intensity55. However, when reflecting off a moving surface, such as moving red blood cells in the vasculature, the light is reflected more heavily away from that region in space in the direction of flow, creating a blur3556. This blur is characterized by a lower standard deviation with respect to the intensity at that point.…”

Random process estimator for laser speckle imaging of cerebral blood flow

“…Both spatial [7] and temporal [8] laser speckle contrast analysis methods, i.e. spatial LASCA and temporal LASCA respectively, have been used to estimate the contrast values ( $K^2$) which is inversely proportional to the relative velocity ( v ) [9]. However, spatial LASCA decreases the spatial resolution while temporal LASCA is under the cost of temporal resolution.…”