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•We thoroughly derive and compare different layered analytical models used in continuous-wave (CW), time-domain (TD), and frequency-domain (FD)-DCS, highlighting their strengths and applications.•We discuss novel artificial intelligence (AI)-enhanced DCS analysis strategies, addressing their effectiveness and potential.•We conclude new applications of CMOS SPAD cameras and compare them with existing sensors used in DCS.•We compare TD-DCS and CW-DCS systems and emphasize the benefits of TD-DCS and its potential for future development.•The authors are leading scientists in DCS and SPAD sensors.•Discussion and outlooks are also provided. Diffuse correlation spectroscopy (DCS) is a powerful tool for assessing microvascular hemodynamic in deep tissues. Recent advances in sensors, lasers, and deep learning have further boosted the development of new DCS methods. However, newcomers might feel overwhelmed, not only by the already-complex DCS theoretical framework but also by the broad range of component options and system architectures. To facilitate new entry to this exciting field, we present a comprehensive review of DCS hardware architectures (continuous-wave, frequency-domain, and time-domain) and summarize corresponding theoretical models. Further, we discuss new applications of highly integrated silicon single-photon avalanche diode (SPAD) sensors in DCS, compare SPADs with existing sensors, and review other components (lasers, sensors, and correlators), as well as data analysis tools, including deep learning. Potential applications in medical diagnosis are discussed and an outlook for the future directions is provided, to offer effective guidance to embark on DCS research.

Value of neuron-specific enolase (NSE) factor combined with ultrasound hemodynamic parameters in the diagnosis of cervical lymph node metastasis of lung cancer was explored. The clinical data of 85 patients with lung cancer, admitted to Qingdao Municipal Hospital (Group) from January 2015 to December 2016, were retrospectively analyzed. According to the results of pathological examination, 47 patients with cervical lymph node metastasis were enrolled in the metastatic group and 38 patients without lymph node metastasis were enrolled in the non-metastatic group. The expression level of NSE in serum and the hemodynamic indicators of blood flow resistance index (RI) and pulsatility index (PI) were compared between the two groups. ROC curve analysis was used to analyze the diagnostic efficacy of NSE, RI, PI, and their combination in lymph node metastasis of lung cancer. The NSE, RI and PI indexes in the metastatic group were significantly higher than those in the non-metastatic group (P<0.05). The sensitivity and specificity of NSE in the diagnosis of cervical lymph node metastasis of lung cancer were 73.68 and 72.34%, respectively; the sensitivity and specificity of RI were 78.95 and 80.85%, respectively; the sensitivity and specificity of PI were 81.58 and 68.09%, respectively. Also, the sensitivity and specificity of NSE combined with RI were 89.47 and 61.70%, respectively, and the diagnostic AUC was 0.881. The sensitivity and specificity of NSE combined with PI were 92.11 and 74.47%, respectively, and the diagnostic AUC was 0.905. NSE, RI, and PI have certain diagnostic value for cervical lymph node metastasis of lung cancer, however, the combined diagnosis is more valuable, and can be used as the auxiliary diagnosis of cervical lymph node metastasis of lung cancer.

The field of diffuse optics has provided a rich set of neurophotonic tools to measure the human brain noninvasively. Interferometric detection is a recent, exciting methodological development in this field. The approach is especially promising for the measurement of diffuse fluctuation signals related to blood flow. Benefitting from inexpensive sensor arrays, the interferometric approach has already dramatically improved throughput, enabling the measurement of brain blood flow faster and deeper. The interferometric approach can also achieve time-of-flight resolution, improving the accuracy of acquired signals. We provide a historical perspective and summary of recent work in the nascent area of interferometric diffuse optics. We predict that the convergence of interferometric technology with existing economies of scale will propel many advances in the years to come.

Diffuse correlation tomography (DCT) is an emerging technique for detecting diseases associated with localized abnormal perfusion from near-infrared light intensity temporal autocorrelation functions (g2(τ)). However, a critical drawback of traditional reconstruction methods is the imbalance between optical measurements and the voxels to be reconstructed. To address this issue, this paper proposes Conv-TransNet, a convolutional neural network (CNN)–Transformer hybrid model that directly maps g2(τ) data to blood flow index (BFI) images. For model training and testing, we constructed a dataset of 18,000 pairs of noise-free and noisy g2(τ) data with their corresponding BFI images. In simulation validation, the root mean squared error (RMSE) for the five types of anomalies with noisy data are 2.13%, 4.43%, 2.15%, 4.05%, and 4.39%, respectively. The MJR (misjudgment ratio)of them are close to zero. In the phantom experiments, the CONTRAST of the quasi-solid cross-shaped anomaly reached 0.59, with an MJR of 2.21%. Compared with the traditional Nth-order linearization (NL) algorithm, the average CONTRAST of the speed-varied liquid tubular anomaly increased by 0.55. These metrics also demonstrate the superior performance of our method over traditional CNN-based approaches. The experimental results indicate that the Conv-TransNet model would achieve more accurate and robust reconstruction, suggesting its potential as an alternative for blood flow imaging.

This paper describes and tests a method for automatically determining the envelope of the blood flow velocity curve in ultrasonic Doppler imaging, which was implemented in a prototype of the 128-channel mobile ultrasound B-mode scanner. On the basis of the determined envelopes, algorithms were also developed for the automatic determination of the most important characteristic points of the Doppler blood flow spectrum in pulse wave Doppler imaging mode and the most relevant blood flow parameters. Sufficiently good repeatability and precision were obtained with low computational complexity.

Near-infrared spectroscopy (NIRS) measurements of tissue oxygen saturation (StO2) are frequently used during vascular and cardiac surgeries as a non-invasive means of assessing brain health; however, signal contamination from extracerebral tissues remains a concern. As an alternative, hyperspectral (hs)NIRS can be used to measure changes in the oxidation state of cytochrome c oxidase (ΔoxCCO), which provides greater sensitivity to the brain given its higher mitochondrial concentration versus the scalp. The purpose of this study was to evaluate the depth sensitivity of the oxCCO signal to changes occurring in the brain and extracerebral tissue components. The oxCCO assessment was conducted using multi-distance hsNIRS (source-detector separations = 1 and 3 cm), and metabolic changes were compared to changes in StO2. Ten participants were monitored using an in-house system combining hsNIRS and diffuse correlation spectroscopy (DCS). Data were acquired during carotid compression (CC) to reduce blood flow and hypercapnia to increase flow. Reducing blood flow by CC resulted in a significant decrease in oxCCO measured at rSD = 3 cm but not at 1 cm. In contrast, significant changes in StO2 were found at both distances. Hypercapnia caused significant increases in StO2 and oxCCO at rSD = 3 cm, but not at 1 cm. Extracerebral contamination resulted in elevated StO2 but not oxCCO after hypercapnia, which was significantly reduced by applying regression analysis. This study demonstrated that oxCCO was less sensitive to extracerebral signals than StO2.

Background Alterations in perfusion to the brain during the transition from mechanical ventilation (MV) to a spontaneous breathing trial (SBT) remain poorly understood. The aim of the study was to determine whether changes in cerebral cortex perfusion, oxygen delivery (DO 2 ), and oxygen saturation (%StiO 2 ) during the transition from MV to an SBT differ between patients who succeed or fail an SBT. Methods This was a single-center prospective observational study conducted in a 16-bed medical intensive care unit of the University Hospital Leuven, Belgium. Measurements were performed in 24 patients receiving MV immediately before and at the end of a 30-min SBT. Blood flow index (BFI), DO 2 , and %StiO 2 in the prefrontal cortex, scalene, rectus abdominis, and thenar muscle were simultaneously assessed by near-infrared spectroscopy using the tracer indocyanine green dye. Cardiac output, arterial blood gases, and systemic oxygenation were also recorded. Results During the SBT, prefrontal cortex BFI and DO 2 responses did not differ between SBT-failure and SBT-success groups ( p  > 0.05). However, prefrontal cortex %StiO 2 decreased in six of eight patients (75%) in the SBT-failure group (median [interquartile range 25–75%]: MV = 57.2% [49.1–61.7] vs. SBT = 51.0% [41.5–62.5]) compared to 3 of 16 patients (19%) in the SBT-success group (median [interquartile range 25–75%]: MV = 65.0% [58.6–68.5] vs. SBT = 65.1% [59.5–71.1]), resulting in a significant differential %StiO 2 response between groups ( p  = 0.031). Similarly, a significant differential response in thenar muscle %StiO 2 ( p  = 0.018) was observed between groups. A receiver operating characteristic analysis identified a decrease in prefrontal cortex %StiO 2  > 1.6% during the SBT as an optimal cutoff, with a sensitivity of 94% and a specificity of 75% to predict SBT failure and an area under the curve of 0.79 (95% CI: 0.55–1.00). Cardiac output, systemic oxygenation, scalene, and rectus abdominis BFI, DO 2 , and %StiO 2 responses did not differ between groups ( p  > 0.05); however, during the SBT, a significant positive association in prefrontal cortex BFI and partial pressure of arterial carbon dioxide was observed only in the SBT-success group (SBT success: Spearman’s ρ  = 0.728, p  = 0.002 vs. SBT failure: ρ  = 0.048, p  = 0.934). Conclusions This study demonstrated a reduced differential response in prefrontal cortex %StiO 2 in the SBT-failure group compared with the SBT-success group possibly due to the insufficient increase in prefrontal cortex perfusion in SBT-failure patients. A  > 1.6% drop in prefrontal cortex %StiO 2 during SBT was sensitive in predicting SBT failure. Further research is needed to validate these findings in a larger population and to evaluate whether cerebral cortex %StiO 2 measurements by near-infrared spectroscopy can assist in the decision-making process on liberation from MV.

Background Microcirculatory dysfunction is a poor prognostic indicator for the management of critically ill patients, highlighting the need for the development of appropriate assessment methods. Current microcirculatory parameters are often indirect, invasive, or lack immediacy and continuity, with no standardised markers for critical care. Diffuse correlation spectroscopy (DCS), a near-infrared optical technique, facilitates the non-invasive real-time monitoring of microvascular dynamics via the blood flow index (BFI). However, the relationship between BFI and conventional microcirculatory parameters in hypovolemic shock remains unclear. This study examined the utility of DCS in assessing the microcirculation during hypovolemic shock in a canine model. Methods Six male beagle dogs underwent controlled blood withdrawal to induce hypovolemic shock, defined as a ≥ 30% decrease in cardiac output (CO) and mean arterial pressure (MAP) < 60 mmHg or systolic arterial pressure (SAP) < 90 mmHg. BFI was measured using a DCS device attached to the skin of the forelimb. From baseline to blood withdrawals followed by transfusions, changes in BFI were compared with microcirculatory parameters, mixed venous oxygen saturation (S v O₂), core-to-skin temperature gradient (ΔT), veno-arterial difference in partial pressure of carbon dioxide (PCO₂ gap), and serum lactate. Correlation and receiver operating characteristic (ROC) analyses were performed to determine the cut-off value of relative BFI for predicting whether lactate levels exceeded 22.5 mg/dL. Results Blood withdrawal resulted in significant reductions in BFI, CO, and radial artery blood flow, with the corresponding deteriorations in the ΔT, S v O₂, and PCO 2 gap and lactate levels. BFI showed significant correlations with ΔT (correlation coefficient [CC] = − 0.48, 95% confidence interval [CI] − 0.69 to − 0.18, p  < 0.01), SvO₂ (CC = 0.67, 95% CI 0.43 to 0.81, p  < 0.01), and PCO2 gap (CC = − 0.63, 95% CI − 0.79 to − 0.39, p  < 0.01). ROC analysis identified a relative BFI threshold of 35.5% of the baseline for predicting elevated lactate levels, with 62% sensitivity and 100% specificity (AUC = 0.75). Conclusions Blood flow index measured by DCS reflects peripheral perfusion changes and is significantly correlated with clinical parameters during blood withdrawal and transfusion, highlighting its potential for non-invasive, continuous microcirculation monitoring in hypovolemic shock.

Purpose. To evaluate state of the blood flow parameters of the macular region, the optic nerve disc, and the state of the premacular bag after the formation of the corneal lenticle during the correction of myopia using CLEAR technology. Material and methods. From December 2021 to February 2022, 25 patients (44 eyes) aged 18 to 39 years (31.88±1.15, M±m) with myopia (–4.08±0.19, M±m) and myopic astigmatism (–0.47±0.04, M±m), who underwent femtolaser lenticular vision correction using CLEAR technology. As additional examination methods, all patients underwent optical coherence tomography on the Nidek RS-3000 Advance AngioScan device (NIDEK, Japan) in order to evaluate the following parameters: vascular network density and blood flow index in the macular region of the retina and optic disc before surgery and 1 day after the CLEAR correction, as well as to determine the size of the premacular bag before surgery and 1 day later. Results. In patients after performing vision correction using CLEAR technology, there are no statistically significant changes in the vascular network density and blood flow index in the macular region of the retina and in the optic disc, as well as the size of the premacular bag 1 day after surgery. Conclusion. With femtolaser lenticular correction of myopia, a longer vacuum effect on the eye is provided at the stage of corneal lenticular formation. However, this does not affect the condition of the blood flow of the posterior segment of the eye in the first day after surgery. Key words: femtolaser correction, lenticula, myopia, vacuum exposure, vascular network density, blood flow index, macular area of the retina, Optical Nerv, premacular bag

Objective: To detect perfusion reductions in patients with acute cerebral infarcts using near-infrared spectroscopy (NIRS) with indocyanine green (ICG) as tracer. Methods: Kinetics of an intravenous bolus of ICG were monitored by NIRS in 13 patients with acute infarction in the territory of the middle cerebral artery (mean (SD) age, 62.2 (13.0) years) and 12 controls (64.2 (9.1) years) at 2.8 (2.8) days after onset. NIRS optodes were placed bitemporally, with an interoptode distance of 4–5 cm. Absolute concentration changes in ICG were calculated. The following were assessed: time to peak, maximum ICG concentration, time interval between 0% and 100% maximum ICG concentration (interval), rise time (time between 10% and 90% ICG maximum), slope (maximum Δ ICG/interval), and blood flow index (BFI = maximum Δ ICG/rise time) of each hemisphere. Intraindividual differences were calculated between the two hemispheres. Results: Patients with ischaemic stroke had increased time to peak (p<0.01), interval (p<0.01), and rise time (p<0.01), while maximum ICG concentration (p<0.03), slope (p<0.01), and BFI (p<0.01) were diminished at the site of infarction compared with the unaffected hemisphere. In stroke patients, intraindividual differences in time to peak (p<0.001), interval (p<0.001), rise time (p = 0.001), maximum ICG concentration (p<0.02), slope (p<0.001), and BFI (p<0.001) were greater than in the controls, with excellent sensitivity and specificity for Δ time to peak (100% and 100%, respectively) and Δ time interval (100% and 91.7%). Conclusions: Measurement of interhemispheric differences in ICG kinetics by NIRS detects perfusion reductions in patients with acute middle cerebral artery infarction. This non-invasive bedside test is rapid, repeatable, without major side effects, and avoids transportation of critically ill patients.