The combination of diffuse correlation spectroscopy (DCS) and frequency-domain diffuse optical spectroscopy (FD-DOS) techniques is a promising approach for continuous and noninvasive measurement of cerebral blood flow (CBF), blood oxygenation, and oxygen metabolism at the bedside.^{1 – 3} The approach has been validated in pediatric patient populations and swine models.^{4 – 9} These validation studies approximated the head as a homogeneous medium [i.e., semi-infinite (SI) head model] to derive cerebral hemodynamics from the FD-DOS/DCS signals. A well-known drawback of the homogeneous head model, however, is the significant extracerebral tissue (scalp and skull) contributions to the measured signals.^{10 – 15} Neglecting extracerebral contributions can result in large errors, especially for adult populations.^15,16 Herein, we investigate the accuracy of CBF and cerebral tissue absorption coefficient measurements derived from applying a constrained two-layer (2L) head model algorithm to (a) hybrid FD-DOS and DCS simulated data in adults and (b) hybrid FD-DOS and DCS in vitro data in a 2L liquid phantom.

Carotid artery stenosis (CAS) is a common vascular disease with long-term consequences for the brain. Although CAS is strongly associated with impaired cerebral hemodynamics and neurodegeneration, the mechanisms underlying hemodynamic impairment in the microvasculature remain unknown. In this work, we employed functional near-infrared spectroscopy (fNIRS) to introduce a methodological approach for quantifying the temporal delay of the evoked hemodynamic response. The method was validated during a vasodilatory task (breath-holding) in 50 CAS patients and 20 controls. Our results suggest that the hemodynamic response to breath-holding can be delayed by up to 6 s in the most severe patients, a significant increase from the median 4 s measured for the control group (p = 0.01). In addition, the fraction of brain regions that responded to the task decreased as the CAS severity increased, from a median of 90% in controls to 73% in the most severe CAS group (p = 0.04). The presence of collateral circulation increases the response to breath-holding and decreases the average time delays across the brain, although the number of communicating arteries alone cannot predict these fNIRS-based hemodynamic variables (p > 0.09). Overall, this work proposes a method to quantitatively assess impaired cerebral hemodynamics in CAS patients.

Diffuse optical spectroscopies are promising non-invasive optical techniques that may provide a point-of-care tool to evaluate cerebral hemometabolic stress. This study quantifies the intra- and inter-operator reliability of a battery of cerebral hemometabolic parameters quantified with diffuse correlation spectroscopy (DCS) and frequency-domain near-infrared spectroscopy (FDNIRS) in children with sickle cell anemia. For measures of cerebral blood flow, oxygen extraction fraction, metabolic rate of oxygen, and cerebral blood volume, we found inter-operator concordance correlation coefficients (CCC) ranging from 0.45 to 0.97, intra-operator CCCs ranging from 0.81 to 0.98, and a median coefficient of variation < 16%.

Sickle cell disease causes alterations in cerebral blood flow (CBF) and a high risk of stroke. Monitoring CBF in these patients may provide valuable information about neurovascular compromise. Diffuse correlation spectroscopy (DCS) is a promising approach for non-invasively estimating an index of regional CBF; however, foundational studies are needed to validate DCS against clinical standards for estimating CBF in this clinical population. Here, we demonstrate that DCS significantly correlates with transcranial Doppler ultrasound-measured blood flow velocity in the anterior cerebral artery in 16 children with sickle cell disease (r = 0.82, p < 0.001). Correction for the influence of hematocrit on BFI did not significantly change this correction.

Accurate estimation of optical properties and hemodynamic parameters is critical for advancing frequency-domain diffuse optical spectroscopy (FD-DOS) techniques in clinical neuroscience. However, conventional FD-DOS models often assume planar air–tissue interfaces, introducing errors in anatomically curved regions such as the forehead or infant heads. This study evaluates the impact of incorporating tissue curvature into forward models for FD-DOS analysis. Using simulations and optical phantoms, we demonstrate that curved models reduce errors in absorption coefficient estimation from 20% to less than 10% in high-curvature scenarios. Within the curvatures tested, even minor curvature mismatches resulted in errors significantly lower than those observed from planar approximations (p < 0.001). In low-curvature regions, curved models yielded errors comparable to planar models (<5% in both cases). When applied to human data, our proposed curved model increased absorption and hemoglobin concentration estimates by 10–15% compared to standard semi-infinite models, closer to physiological expectations. Overall, these results quantitatively demonstrate that accounting for tissue curvature in FD-DOS forward models significantly improves the accuracy of optical property estimation. We propose a numerical framework that achieves this in a fast and reliable manner, advancing FD-DOS as a robust tool for clinical and research applications in anatomically complex regions.