Correcting sampling bias in speckle contrast imaging

Dynamic light scattering and laser speckle contrast imaging of the brain: theory of the spatial and temporal statistics of speckle pattern evolution

Dynamic light scattering (DLS) and laser speckle contrast imaging (LSCI) are closely related techniques that exploit the statistics of speckle patterns, which can be utilized to measure cerebral blood flow (CBF). Conventionally, the temporal speckle intensity auto-correlation function g 2 t ( τ ) is calculated in DLS, while the spatial speckle contrast Ks is calculated in LSCI measurements. Due to the rapid development of CMOS detection technology with increased camera frame rates while still maintaining a large number of pixels, the ensemble or spatial average of g 2 s ( τ ) as well as the temporal contrast Kt can be easily calculated and utilized to quantify CBF. Although many models have been established, a proper summary is still lacking to fully characterize DLS and LSCI measurements for spatial and temporal statistics, laser coherence properties, various motion types, etc. As a result, there are many instances where theoretical models are misused. For instance, mathematical formulas derived in the diffusive regime or for ergodic systems are sometimes applied to small animal brain measurements, e.g., mice brains, where the assumptions are not valid. Therefore, we aim to provide a review of the speckle theory for both DLS and LSCI measurements with detailed derivations from first principles, taking into account non-ergodicity, spatial and temporal statistics of speckles, scatterer motion types, and laser coherence properties. From these calculations, we elaborate on the differences between spatial and temporal averaging for DLS and LSCI measurements that are typically ignored but can result in inaccurate measurements of blood flow, particularly the spatially varying nature of the static component in g 2 t ( τ ) and Kt. We also obtained g 2 s ( τ ) maps in in vivo mouse brain measurements using high frame rate CMOS cameras which have not been demonstrated before, and compared with g 2 t ( τ ) and Ks,t. This work provides a useful guide for choosing the correct model to analyze spatial and temporal speckle statistics in in-vivo DLS and LSCI measurements.

Choosing a polarisation configuration for dynamic light scattering and laser speckle contrast imaging

Laser speckle contrast imaging (LSCI) is applied in various biomedical applications for full-field characterization of blood flow and tissue perfusion. The accuracy of the contrast interpretation and its conversion to the blood flow index depends on specific parameters of the optical system and scattering media. One such parameter is the polarisation of detected light, which is often adjusted to minimize specular reflections and image artefacts. The polarisation's effect on the detected light scattering dynamics and, therefore, the accuracy of LSCI data interpretation requires more detailed investigation. In this study, we used LSCI and Dynamic Light Scattering Imaging to evaluate the effects of the detected light polarisation when imaging perfusion in the mouse cortex. We found that cross-polarisation results in a shorter decorrelation time constant, a higher coherence degree and stronger dynamic scattering compared to the parallel-polarisation or no-polariser configurations. These results support the cross-polarisation configuration as the most optimal for brain cortex imaging and suggest against direct or calibrated comparisons between the contrast recordings made with different polarisation configurations.

Optimizing the precision of laser speckle contrast imaging

Laser speckle contrast imaging (LSCI) is a rapidly developing technology broadly applied for the full-field characterization of tissue perfusion. Over the recent years, significant advancements have been made in interpreting LSCI measurements and improving the technique's accuracy. On the other hand, the method's precision has yet to be studied in detail, despite being as important as accuracy for many biomedical applications. Here we combine simulation, theory and animal experiments to systematically evaluate and re-analyze the role of key factors defining LSCI precision-speckle-to-pixel size ratio, polarisation, exposure time and camera-related noise. We show that contrary to the established assumptions, smaller speckle size and shorter exposure time can improve the precision, while the camera choice is less critical and does not affect the signal-to-noise ratio significantly.

Interferometric speckle visibility spectroscopy (iSVS) for measuring decorrelation time and dynamics of moving samples with enhanced signal-to-noise ratio and relaxed reference requirements

Diffusing wave spectroscopy (DWS) is a group of techniques used to measure the dynamics of a scattering medium in a non-invasive manner. DWS methods rely on detecting the speckle light field from the moving scattering medium and measuring the speckle decorrelation time to quantify the scattering medium's dynamics. For DWS, the signal-to-noise (SNR) is determined by the ratio between measured decorrelation time to the standard error of the measurement. This SNR is often low in certain applications because of high noise variances and low signal intensity, especially in biological applications with restricted exposure and emission levels. To address this photon-limited signal-to-noise ratio problem, we investigated, theoretically and experimentally, the SNR of an interferometric speckle visibility spectroscopy (iSVS) compared to more traditional DWS methods. We found that iSVS can provide excellent SNR performance through its ability to overcome camera noise. We also proved an iSVS system has more relaxed constraints on the reference beam properties. For an iSVS system to function properly, we only require the reference beam to exhibit local temporal stability, while incident angle, reference phase and intensity uniformity do not need to be constrained. This flexibility can potentially enable more unconventional iSVS implementation schemes.

Lossless temporal contrast analysis of laser speckle images from periodic signals

Laser speckle contrast imaging is a technique that provides valuable physiological information about vascular topology and blood flow dynamics. When using contrast analysis, it is possible to obtain detailed spatial information at the cost of sacrificing temporal resolution and vice versa. Such a trade-off becomes problematic when assessing blood dynamics in narrow vessels. This study presents a new contrast calculation method that preserves fine temporal dynamics and structural features when applied to periodic blood flow changes, such as cardiac pulsatility. We use simulations and in vivo experiments to compare our method with the standard spatial and temporal contrast calculations and demonstrate that the proposed method retains the spatial and temporal resolutions, resulting in the improved estimation of the blood flow dynamics.