ArticleJournal of biomedical optics2023
Comparison of diffuse correlation spectroscopy analytical models for measuring cerebral blood flow in adults.
Article in Journal of biomedical optics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 11 citations in OpenAlex.
- Compact FPGA-based software correlator for real-time blood flow measurement with diffuse correlation spectroscopy.Biomedical optics express · 2026Article
- Toward comprehensive multimodal neuromonitoring of surrogates of cerebral autoregulation in traumatic brain injury: insights from a hyperventilation protocol.Neurophotonics · 2026Article
- Monte Carlo simulations of time-resolved blood flow index: times-of-flight beyond ∼1 ns are necessary for brain-dominated measurements.Neurophotonics · 2026Article
- CoMind R1: a time-resolved interferometric optical neuromonitoring system for pulsatile cerebral blood flow measurement at late times-of-flight.Neurophotonics · 2026Article
- Depth-sensitive cerebral blood flow and low-frequency oscillations for consciousness assessment using time-domain diffuse correlation spectroscopy.Neurophotonics · 2026Article
- Highly parallel, 1060 nm interferometric diffusing wave spectroscopy with a time-of-flight filter.Biomedical optics express · 2026Article
- Correlation between diffuse correlation spectroscopy and transcranial Doppler ultrasound in pediatric sickle cell disease.Biomedical optics express · 2026Article
- Noninvasive estimation of superficial layer thickness using multi-channel diffuse correlation spectroscopy.Biomedical optics express · 2025Article
- Comparison of diffuse correlation spectroscopy analytical models for cerebral blood flow measurements.Journal of biomedical optics · 2025Article
- Cerebral blood flow monitoring using a deep learning implementation of the two-layer diffuse correlation spectroscopy analytical model with a 512 × 512 SPAD array.Neurophotonics · 2025Article
- Beneath the surface: revealing deep-tissue blood flow in human subjects with massively parallelized diffuse correlation spectroscopy.Neurophotonics · 2025Article
- All-optics technique for monitoring absolute cerebral blood flow: validation against magnetic resonance imaging perfusion.Neurophotonics · 2024Article
- Modified Beer-Lambert algorithm to measure pulsatile blood flow, critical closing pressure, and intracranial hypertension.Biomedical optics express · 2024Article
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Authors and funding
11 authors at 3 institutions in 1 country.
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Abstract
Significance: Although multilayer analytical models have been proposed to enhance brain sensitivity of diffuse correlation spectroscopy (DCS) measurements of cerebral blood flow, the traditional homogeneous model remains dominant in clinical applications. Rigorous Aim: We compare the performance of different analytical models to estimate a cerebral blood flow index (CBFi) with DCS in adults. Approach: Resting-state data were obtained on a cohort of 20 adult patients with subarachnoid hemorrhage. Data at 1 and 2.5 cm source-detector separations were analyzed with the homogenous, two-layer, and three-layer models to estimate scalp blood flow index and CBFi. The performance of each model was quantified via fitting convergence, fit stability, brain-to-scalp flow ratio (BSR), and correlation with transcranial Doppler ultrasound (TCD) measurements of cerebral blood flow velocity in the middle cerebral artery (MCA). Results: The homogeneous model has the highest pass rate (100%), lowest coefficient of variation (CV) at rest (median [IQR] at 1 Hz of 0.18 [0.13, 0.22]), and most significant correlation with MCA blood flow velocities ( Conclusions: We found that the homogeneous model has the highest pass rate, lowest CV at rest, and most significant correlation with MCA blood flow velocities. Results from the multilayer models should be taken with caution because they suffer from lower pass rates and higher coefficients of variation at rest and can converge to non-physiological values for CBFi. Future work is needed to validate these models
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.