This pilot study explores the potential of noninvasive diffuse correlation spectroscopy (DCS) and diffuse reflectance spectroscopy (DRS) for monitoring early relative blood flow $(rBF)$, tissue oxygen saturation $(StO2)$, and total hemoglobin concentration $(THC)$ responses to chemo-radiation therapy in patients with head and neck tumors. $rBF$, $StO2$, and $THC$ in superficial neck tumor nodes of eight patients are measured before and during the chemo-radiation therapy period. The weekly $rBF$, $StO2$, and $THC$ kinetics exhibit different patterns for different individuals, including significant early blood flow changes during the first two weeks. Averaged blood flow increases $(52.7±9.7)%$ in the first week and decreases $(42.4±7.0)%$ in the second week. Averaged $StO2$ increases from $(62.9±3.4)%$ baseline value to $(70.4±3.2)%$ at the end of the second week, and averaged $THC$ exhibits a continuous decrease from pretreatment value of $(80.7±7.0)$$[μM]$ to $(73.3±8.3)$$[μM]$ at the end of the second week and to $(63.0±8.1)$$[μM]$ at the end of the fourth week of therapy. These preliminary results suggest daily diffuse-optics-based therapy monitoring is feasible during the first two weeks and may have clinical promise.

The ability to probe deep tissues with light for biomedical applications has been recognized since the scientific reports published as early as the late 1800s for monitoring brain hemorrhage¹ and early 1900s for imaging breast cancer² and performing tissue oximetry.^3,4 Since then, diffuse optical imaging techniques have greatly benefited numerous biomedical fields. Mainly, the goal of these optical techniques is to characterize optical properties of tissue using light from the ultraviolet to the infrared spectral region. The specific light–tissue interaction enables monitoring of a vast array of tissue characteristics, including structural, physiological, metabolic, and molecular properties.

Recently proposed time-gated diffuse correlation spectroscopy (TG-DCS) has significant advantages compared to conventional continuous wave (CW)-DCS, but it is still in an early stage and clinical capability has yet to be established. The main challenge for TG-DCS is the lower signal-to-noise ratio (SNR) when gating for the deeper traveling late photons. Longer wavelengths, such as 1064 nm have a smaller effective attenuation coefficient and a higher power threshold in humans, which significantly increases the SNR. Here, we demonstrate the clinical utility of TG-DCS at 1064 nm in a case study on a patient with severe traumatic brain injury admitted to the neuro-intensive care unit (neuroICU). We showed a significant correlation between TG-DCS early (ρ = 0.67) and late (ρ = 0.76) gated against invasive thermal diffusion flowmetry. We also analyzed TG-DCS at high temporal resolution (50 Hz) to elucidate pulsatile flow data. Overall, this study demonstrates the first clinical translation capability of the TG-DCS system at 1064 nm using a superconducting nanowire single-photon detector.

A novel approach for time-domain diffuse correlation spectroscopy (TD-DCS) has been recently proposed, which has the unique advantage by simultaneous measurements of optical and dynamical properties in a scattering medium. In this study, analytical models for calculating the time-resolved electric-field autocorrelation function is presented for a multi-layer turbid sample, as well as a semi-infinite medium embedded with a small dynamic heterogeneity. To verify the analytical models, we used Monte Carlo simulations, which demonstrated that the theoretical prediction for the time-resolved autocorrelation function was highly consistent with the Monte Carlo simulation, validating the proposed analytical models. Using these analytical models, we also showed that TD-DCS has a higher sensitivity compared to conventional continuous-wave (CW) DCS for detecting the deeper dynamics. The presented analytical models and simulations can be utilized for quantification of optical and dynamical properties from future TD-DCS experimental data as well as for optimization of the experimental design to achieve maximum contrast for deep tissue dynamics.

Diffuse correlation spectroscopy (DCS) is increasingly used in the optical imaging field to assess blood flow in humans due to its non-invasive, real-time characteristics and its ability to provide label-free, bedside monitoring of blood flow changes. Previous DCS studies have utilized a traditional curve fitting of the analytical or Monte Carlo models to extract the blood flow changes, which are computationally demanding and less accurate when the signal to noise ratio decreases. Here, we present a deep learning model that eliminates this bottleneck by solving the inverse problem more than 2300% faster, with equivalent or improved accuracy compared to the nonlinear fitting with an analytical method. The proposed deep learning inverse model will enable real-time and accurate tissue blood flow quantification with the DCS technique.

Doxorubicin (Dox) is approved for use in liposomal form for the treatment of ovarian cancer. We previously developed a long-circulating Dox formulation in liposomes containing small amounts of porphyrin-phospholipid, which enables on-demand drug release with near-infrared irradiation. In this study, we present and evaluate a dual-modal, dual-channel light endoscope that allows quantitative reflectance and fluorescence imaging for monitoring of local Dox concentrations in target areas. The endoscope consists of two flexible imaging fibers; one to transmit diagnostic and therapeutic light to the target, and the other to detect fluorescent and reflected light. Thus, the endoscope serves for imaging, for light delivery to trigger drug release, and for monitoring drug concentration kinetics during drug release. We characterized the performance of this endoscope in tissue phantoms and in anin vivomodel of ovarian cancer. This study demonstrates the feasibility of non-invasive, quantitative mapping of Dox distributionin vivovia endoscopic imaging.