A primary focus of neurointensive care is the prevention of secondary brain injury, mainly caused by ischemia. A noninvasive bedside technique for continuous monitoring of cerebral blood flow (CBF) could improve patient management by detecting ischemia before brain injury occurs. A promising technique for this purpose is diffuse correlation spectroscopy (DCS) since it can continuously monitor relative perfusion changes in deep tissue. In this study, DCS was combined with a time-resolved near-infrared technique (TR-NIR) that can directly measure CBF using indocyanine green as a flow tracer. With this combination, the TR-NIR technique can be used to convert DCS data into absolute CBF measurements. The agreement between the two techniques was assessed by concurrent measurements of CBF changes in piglets. A strong correlation between CBF changes measured by TR-NIR and changes in the scaled diffusion coefficient measured by DCS was observed (R2 = 0.93) with a slope of 1.05 ± 0.06 and an intercept of 6.4 ± 4.3% (mean ± standard error).
Diffuse correlation spectroscopy (DCS) is a promising technique for brain monitoring as it can provide a continuous signal that is directly related to cerebral blood flow (CBF); however, signal contamination from extracerebral tissue can cause flow underestimations. The goal of this study was to investigate whether a multi-layered (ML) model that accounts for light propagation through the different tissue layers could successfully separate scalp and brain flow when applied to DCS data acquired at multiple source-detector distances. The method was first validated with phantom experiments. Next, experiments were conducted in a pig model of the adult head with a mean extracerebral tissue thickness of 9.8 ± 0.4 mm. Reductions in CBF were measured by ML DCS and computed tomography perfusion for validation; excellent agreement was observed by a mean difference of 1.2 ± 4.6% (CI 95% : −31.1 and 28.6) between the two modalities, which was not significantly different.
Preterm infants are highly susceptible to ischemic brain injury; consequently, continuous bedside monitoring to detect ischemia before irreversible damage occurs would improve patient outcome. In addition to monitoring cerebral blood flow (CBF), assessing the cerebral metabolic rate of oxygen (CMRO2) would be beneficial considering that metabolic thresholds can be used to evaluate tissue viability. The purpose of this study was to demonstrate that changes in absolute CMRO2 could be measured by combining diffuse correlation spectroscopy (DCS) with time-resolved near-infrared spectroscopy (TR-NIRS). Absolute CBF was determined using bolus-tracking TR-NIRS to calibrate the DCS measurements. Cerebral venous blood oxygenation (SvO2) was determined by multiwavelength TR-NIRS measurements, the accuracy of which was assessed by directly measuring the oxygenation of sagittal sinus blood. In eight newborn piglets, CMRO2 was manipulated by varying the anesthetics and by injecting sodium cyanide. No significant differences were found between the two sets of SvO2 measurements obtained by TR-NIRS or sagittal sinus blood samples and the corresponding CMRO2 measurements. Bland-Altman analysis showed a mean CMRO2 difference of 0.0268 ± 0.8340 mLO2/100 g/min between the two techniques over a range from 0.3 to 4 mL O2/100 g/min.
Dynamic contrast-enhanced (DCE) methods are widely used with magnetic resonance imaging and computed tomography to assess the vascular characteristics of tumours since these properties can affect the response to radiotherapy and chemotherapy. In contrast, there have been far fewer studies using optical-based applications despite the advantages of low cost and safety. This study investigated an appropriate kinetic model for optical applications to characterize tumour haemodynamics (blood flow, F, blood volume, V(b), and vascular heterogeneity) and vascular leakage (permeability surface-area product, PS). DCE data were acquired with two dyes, indocyanine green (ICG) and 800 CW carboxylate (IRD(cbx)), from a human colon tumour xenograph model in rats. Due to the smaller molecular weight of IRD(cbx) (1166 Da) compared to albumin-bound ICG (67 kDa), PS of IRD(cbx) was significantly larger; however, no significant differences in F and V(b) were found between the dyes as expected. Error analysis demonstrated that all parameters could be estimated with an uncertainty less than 5% due to the high temporal resolution and signal-to-noise ratio of the optical measurements. The next step is to adapt this approach to optical imaging to generate haemodynamics and permeability maps, which should enhance the clinical interest in optics for treatment monitoring.
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