Normal aging is associated with significant alterations in brain's vascular structure and function, which can lead to compromised cerebral circulation and increased risk of neurodegeneration. The in vivo examination of cerebral blood flow (CBF), including capillary beds, in aging brains with sufficient spatial detail remains challenging with current imaging modalities. In the present study, we use 3-dimensional (3-D) quantitative optical coherence tomography angiography (OCTA) to examine characteristic differences of the cerebral vasculatures and hemodynamics at the somatosensory cortex between old (16 months old) and young mice (2 months old) in vivo. The quantitative metrics include cortical vascular morphology, CBF, and capillary flow velocity. We show that compared with young mice, the pial arterial tortuosity increases by 14%, the capillary vessel density decreases by 15%, and the CBF reduces by 33% in the old mice. Most importantly, changes in capillary velocity and heterogeneity with aging are quantified for the first time with sufficiently high statistical power between young and old populations, with a 21% (p < 0.05) increase in capillary mean velocity and 19% (p ≤ 0.05) increase in velocity heterogeneity in the latter. Our findings through noninvasive imaging are in line with previous studies of vascular structure modification with aging, with additional quantitative assessment in capillary velocity enabled by advanced OCTA algorithms on a single imaging platform. The results offer OCTA as a promising neuroimaging tool to study vascular aging, which may shed new light on the investigations of vascular factors contributing to the pathophysiology of age-related neurodegenerative disorders.

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The cerebral vascular system provides a means to meet the constant metabolic needs of neuronal activities in the brain. Within the cerebral capillary bed, the interactions of spatial and temporal hemodynamics play a deterministic role in oxygen diffusion, however, the progression of which remains unclear. Taking the advantages of high spatiotemporal resolution of optical coherence tomography (OCT) capillary velocimetry designed with the eigen-decomposition (ED) statistical analysis, we investigated intrinsic red blood cell (RBC) velocities and their spatiotemporal adjustment within the capillaries permeating mouse cerebral cortex during electrical stimulation of contralateral hind-paw. We found that mean capillary transit velocity (mCTV) is increased and its temporal fluctuation band-width (TFB) is broadened within hind-paw somatosensory cortex. Additionally, the degree to which mCTV is increased negatively correlates with resting state mCTV, and the degree to which TFB is increased negatively correlates with both resting state mCTV and TFB. In order to confirm the changes are due to hemodynamic regulation, we performed angiographic analyses and found that the vessel density remains almost constant, suggesting the observed functional activation does not involve recruitment of reserved capillaries. To further differentiate the contributions of mCTV and TFB to the spatiotemporally-coupled hemodynamics, changes in the mCTV and TBF of capillary flow were modeled and investigated through a Monte Carlo simulation. The results suggest that neural activation evokes the spatial transit time homogenization within the capillary bed, which is regulated via both the heterogeneous acceleration of RBC flow and the heterogeneous increase of temporal RBC fluctuation, ensuring sufficient oxygenation during functional hyperemia.

Optical coherence tomography angiography (OCTA) is capable of noninvasively imaging the vascular networks within circulatory tissue

We present a significant step toward ultrahigh-resolution, motion-insensitive characterization of vascular dynamics. Optical coherence tomography angiography (OCTA) is an invaluable diagnostic technology for non-invasive, label-free vascular imaging in vivo. However, since it relies on detecting moving cells from consecutive scans, high-resolution OCTA is susceptible to tissue motion, which imposes challenges in resolving and quantifying small vessels. We developed a novel OCTA technique named ultrahigh-resolution factor angiography (URFA) by modeling repeated scans as generative latent variables, with a common variance representing shared features and a unique variance representing motion. By iteratively maximizing the combined log-likelihood probability of these variances, the unique variance is largely separated. Meanwhile, features in the common variance are decoupled, in which vessels with dynamic flow are extracted from tissue structure by integrating high-order factors. Combined with Gabor-domain optical coherence microscopy, URFA successfully extracted high-resolution cutaneous vasculature despite severe involuntary tissue motion and scanner oscillation, significantly improving the visualization and characterization of micro-capillaries in vivo. Compared with the conventional approach, URFA reduces motion artifacts by nearly 50% on average, evaluated on local differences.

The dynamic properties of subcellular organism are important biomarkers of the health. Imaging subcellular level dynamics provides effective solutions for evaluating cell metabolism and testing the responses of cells to pathogens and drugs in pharmaceutical engineering. In this paper, we demonstrate an innovative approach to contrast the subcellular motion by using eigen decomposition (ED)‐based variance analysis of time‐dependent complex optical coherence tomography signals. This method reveals a superior advantage of contrast to noise ratio when compared with the approach that employs intensity decorrelation. Furthermore, the eigen values derived from ED processing are calculated and applied to assess the power ratios of complex signal invariance that decreases exponentially along time dimension. The validation experiments are performed on the patterned samples of yeast powder mixed with gelatin/TiO2 water solution. Additionally, the proposed method is used to image mouse cerebral cortex in normal and pathological conditions, suggesting the practicality of variance power mapping in analyzing cortical neural activities. The technique promises efficient measurement of subcellular motions with high sensitivity and high throughput for in vivo and in situ applications.