Faculty Bibliography

PURPOSE/OBJECTIVE:The purpose of this study is to demonstrate three-dimensional (3D) graphing based on optical coherence tomography (OCT) angiography for characterization of the inner retinal vascular architecture and determination of its topologic principles. METHODS:Rat eyes (N = 3) were imaged with a 1300-nm spectral/Fourier domain OCT microscope. A topologic model of the inner retinal vascular network was obtained from OCT angiography data using a combination of automated and manually-guided image processing techniques. Using a resistive network model, with experimentally-quantified flow in major retinal vessels near the optic nerve head as boundary conditions, theoretical changes in the distribution of flow induced by vessel dilations were inferred. RESULTS:A topologically-representative 3D vectorized graph of the inner retinal vasculature, derived from OCT angiography data, is presented. The laminar and compartmental connectivity of the vasculature are characterized. In contrast to sparse connectivity between the superficial vitreal vasculature and capillary plexuses of the inner retina, connectivity between the two capillary plexus layers is dense. Simulated dilation of single arterioles is shown to produce both localized and lamina-specific changes in blood flow, while dilation of capillaries in a given retinal vascular layer is shown to lead to increased total flow in that layer. CONCLUSIONS:Our graphing and modeling data suggest that vascular architecture enables both local and lamina-specific control of blood flow in the inner retina. The imaging, graph analysis, and modeling approach presented here will help provide a detailed characterization of vascular changes in a variety of retinal diseases, both in experimental preclinical models and human subjects.

Quantification of chromophore concentrations in reflectance mode remains a major challenge for biomedical optics. Spectroscopic Optical Coherence Tomography (SOCT) provides depth-resolved spectroscopic information necessary for quantitative analysis of chromophores, like hemoglobin, but conventional SOCT analysis methods are applicable only to well-defined specular reflections, which may be absent in highly scattering biological tissue. Here, by fitting of the dynamic scattering signal spectrum in the OCT angiogram using a forward model of light propagation, we quantitatively determine hemoglobin concentrations directly. Importantly, this methodology enables mapping of both oxygen saturation and total hemoglobin concentration, or alternatively, oxyhemoglobin and deoxyhemoglobin concentration, simultaneously. Quantification was verified by ex vivo blood measurements at various pO2 and hematocrit levels. Imaging results from the rodent brain and retina are presented. Confounds including noise and scattering, as well as potential clinical applications, are discussed.

What is the organization of cerebral microvascular oxygenation and morphology that allows adequate tissue oxygenation at different activity levels? We address this question in the mouse cerebral cortex using microscopic imaging of intravascular O2 partial pressure and blood flow combined with numerical modelling. Here we show that parenchymal arterioles are responsible for 50% of the extracted O2 at baseline activity, and the majority of the remaining O2 exchange takes place within the first few capillary branches. Most capillaries release little O2 at baseline acting as an O2 reserve that is recruited during increased neuronal activity or decreased blood flow. Our results challenge the common perception that capillaries are the major site of O2 delivery to cerebral tissue. The understanding of oxygenation distribution along arterio-capillary paths may have profound implications for the interpretation of blood-oxygen-level dependent (BOLD) contrast in functional magnetic resonance imaging and for evaluating microvascular O2 delivery capacity to support cerebral tissue in disease.

The BOLD (blood-oxygen-level dependent) fMRI (functional Magnetic Resonance Imaging) signal is shaped, in part, by changes in red blood cell (RBC) content and flow across vascular compartments over time. These complex dynamics have been challenging to characterize directly due to a lack of appropriate imaging modalities. In this study, making use of infrared light scattering from RBCs, depth-resolved Optical Coherence Tomography (OCT) angiography was applied to image laminar functional hyperemia in the rat somatosensory cortex. After defining and validating depth-specific metrics for changes in RBC content and speed, laminar hemodynamic responses in microvasculature up to cortical depths of >1mm were measured during a forepaw stimulus. The results provide a comprehensive picture of when and where changes in RBC content and speed occur during and immediately following cortical activation. In summary, the earliest and largest microvascular RBC content changes occurred in the middle cortical layers, while post-stimulus undershoots were most prominent superficially. These laminar variations in positive and negative responses paralleled known distributions of excitatory and inhibitory synapses, suggesting neuronal underpinnings. Additionally, the RBC speed response consistently returned to baseline more promptly than RBC content after the stimulus across cortical layers, supporting a "flow-volume mismatch" of hemodynamic origin.

Recent hardware advances in optical coherence tomography (OCT) have led to ever higher A-scan rates. However, the estimation of blood flow axial velocities is limited by the presence and type of noise. Higher acquisition rates alone do not necessarily enable precise quantification of Doppler velocities, particularly if the estimator is suboptimal. In previous work, we have shown that the Kasai autocorrelation estimator is statistically suboptimal under conditions of additive white Gaussian noise. In addition, for practical OCT measurements of flow, decorrelation noise affects Doppler frequency estimation by broadening the signal spectrum. Here, we derive a general maximum likelihood estimator (MLE) for Doppler frequency estimation that takes into account additive white noise as well as signal decorrelation. We compare the decorrelation MLE with existing techniques using simulated and flow phantom data and find that it has better performance, achieving the Cramer-Rao lower bound. By making an approximation, we also provide an interpretation of this method in the Fourier domain. We anticipate that this estimator will be particularly suited for estimating blood flow in in vivo scenarios.

The hemodynamic response to neuronal activation is a well-studied phenomenon in the brain, due to the prevalence of functional magnetic resonance imaging. The retina represents an optically accessible platform for studying lamina-specific neurovascular coupling in the central nervous system; however, due to methodological limitations, this has been challenging to date. We demonstrate techniques for the imaging of visual stimulus-evoked hyperemia in the rat inner retina using Doppler optical coherence tomography (OCT) and OCT angiography. Volumetric imaging with three-dimensional motion correction, en face flow calculation, and normalization of dynamic signal to static signal are techniques that reduce spurious changes caused by motion. We anticipate that OCT imaging of retinal functional hyperemia may yield viable biomarkers in diseases, such as diabetic retinopathy, where the neurovascular unit may be impaired.