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OBJECTIVE: Diffuse correlation spectroscopy (DCS) is an optical technique that allows for the non-invasive measurement of blood flow. Recent work has shown that utilizing longer wavelengths beyond the traditional NIR range provides a significant improvement to signal-to-noise ratio (SNR). However, current detectors both sensitive to longer wavelengths and suitable for clinical applications (InGaAs/InP SPADs) suffer from suboptimal afterpulsing and dark noise characteristics. To overcome these barriers, we introduce a cross correlation method to more accurately recover blood flow information using InGaAs/InP SPADs. METHODS: Two InGaAs/InP SPAD detectors were used for during in vitro and in vivo DCS measurements. Cross correlation of the photon streams from each detector was performed to calculate the correlation function. Detector operating parameters were varied to determine parameters which maximized measurement SNR. State-space modeling was performed to determine the detector characteristics at each operating point. RESULTS: Evaluation of detector characteristics was performed across the range of operating conditions. Modeling the effects of the detector noise on the correlation function provided a method to correct the distortion of the correlation curve, yielding accurate recovery of flow information as confirmed by a reference detector. CONCLUSION: Through a combination of cross-correlation of the signals from two detectors, model-based characterization of detector response, and optimization of detector operating parameters, the method allows for the accurate estimation of the true blood flow index. Significance: This work presents a method by which DCS can be performed at longer NIR wavelengths with existing detector technology, taking advantage of the increased SNR.

Traumatic injury resulting in hemorrhage is a prevalent cause of death worldwide. The current standard of care for trauma patients is to restore hemostasis by controlling bleeding and administering intravenous volume resuscitation. Adequate resuscitation to restore tissue blood flow and oxygenation is critical within the first hours following admission to assess severity and avoid complications. However, current clinical methods for guiding resuscitation are not sensitive or specific enough to adequately understand the patient condition. To better address the shortcomings of the current methods, an approach to monitor intestinal perfusion and oxygenation using a multiwavelength (470, 560, and 630 nm) optical sensor has been developed based on photoplethysmography and reflectance spectroscopy. Specifically, two sensors were developed using three wavelengths to measure relative changes in the small intestine. Using vessel occlusion, systemic changes in oxygenation input, and induction of hemorrhagic shock, the capabilities and sensitivity of the sensor were explored in vivo. Pulsatile and nonpulsatile components of the red, blue, and green wavelength signals were analyzed for all three protocols (occlusion, systemic oxygenation changes, and shock) and were shown to differentiate perfusion and oxygenation changes in the jejunum. The blue and green signals produced better correlation to perfusion changes during occlusion and shock, while the red and blue signals, using a new correlation algorithm, produced better data for assessing changes in oxygenation induced both systemically and locally during shock. The conventional modulation ratio method was found to be an ineffective measure of oxygenation in the intestine due to noise and an algorithm was developed based on the Pearson correlation coefficient. The method utilized the difference in phase between two different wavelength signals to assess oxygen content. A combination of measures from the three wavelengths provided verification of oxygenation and perfusion states, and showed promise for the development of a clinical monitor.