Choosing a camera and optimizing system parameters for speckle contrast optical spectroscopy.

Speckle contrast optical spectroscopy (SCOS) is an emerging camera-based technique that can measure human cerebral blood flow (CBF) with high signal-to-noise ratio (SNR). At low photon flux levels typically encountered in human CBF measurements, camera noise and nonidealities could significantly impact SCOS measurement SNR and accuracy. Thus, a guide for characterizing, selecting, and optimizing a camera for SCOS measurements is crucial for the development of next-generation optical devices for monitoring human CBF and brain function. Here, we provide such a guide and illustrate it by evaluating three commercially available complementary metal-oxide-semiconductor cameras, considering a variety of factors including linearity, read noise, and quantization distortion. We show that some cameras that are well-suited for general intensity imaging could be challenged in accurately quantifying spatial contrast for SCOS. We then determine the optimal operating parameters for the preferred camera among the three and demonstrate measurement of human CBF with this selected low-cost camera. This work establishes a guideline for characterizing and selecting cameras as well as for determining optimal parameters for SCOS systems.

Comparing the performance potential of speckle contrast optical spectroscopy and diffuse correlation spectroscopy for cerebral blood flow monitoring using Monte Carlo simulations in realistic head geometries.

Significance: The non-invasive measurement of cerebral blood flow based on diffuse optical techniques has seen increased interest as a research tool for cerebral perfusion monitoring in critical care and functional brain imaging. Diffuse correlation spectroscopy (DCS) and speckle contrast optical spectroscopy (SCOS) are two such techniques that measure complementary aspects of the fluctuating intensity signal, with DCS quantifying the temporal fluctuations of the signal and SCOS quantifying the spatial blurring of a speckle pattern. With the increasing interest in the use of these techniques, a thorough comparison would inform new adopters of the benefits of each technique. Aim: We systematically evaluate the performance of DCS and SCOS for the measurement of cerebral blood flow. Approach: Monte Carlo simulations of dynamic light scattering in an MRI-derived head model were performed. For both DCS and SCOS, estimates of sensitivity to cerebral blood flow changes, coefficient of variation of the measured blood flow, and the contrast-to-noise ratio of the measurement to the cerebral perfusion signal were calculated. By varying complementary aspects of data collection between the two methods, we investigated the performance benefits of different measurement strategies, including altering the number of modes per optical detector, the integration time/fitting time of the speckle measurement, and the laser source delivery strategy. Results: Through comparison across these metrics with simulated detectors having realistic noise properties, we determine several guiding principles for the optimization of these techniques and report the performance comparison between the two over a range of measurement properties and tissue geometries. We find that SCOS outperforms DCS in terms of contrast-to-noise ratio for the cerebral blood flow signal in the ideal case simulated here but note that SCOS requires careful experimental calibrations to ensure accurate measurements of cerebral blood flow. Conclusion: We provide design principles by which to evaluate the development of DCS and SCOS systems for their use in the measurement of cerebral blood flow.