Biology subjects

Jafari, C. Z.

Publications and source records attributed to Jafari, C. Z..

3 recordsLinked to original sources

bioRxiv2023

Microvascular plasticity in stroke recovery: Longitudinal snapshots, network statistical analysis, and dynamics

This research article quantitatively investigates neuro-microvascular network remodeling dynamics following stroke using a novel in vivo two-photon angiography (cubic millimeter volume, weekly snapshots) and high throughput (thousands of connected capillaries) vascular vectorization method. The results suggest distinct temporal patterns of cere-brovascular plasticity, with acute remodeling peaking at one week post-stroke. The network architecture then gradually stabilizes, returning to a new steady state after four weeks. These findings align with previous literature on neuronal plasticity, highlighting the correlation between neuronal and neurovascular remodeling. Quantitative analysis of neurovascular networks using length- and strand-based statistical measures reveals intri-cate changes in network anatomy and topology. The distance and strand-length statistics show significant alterations, with a peak of plasticity observed at one week post-stroke, followed by a gradual return to baseline. The orientation statistic plasticity peaks at two weeks, gradually approaching the (conserved across subjects) stroke signature. The underlying mechanism of the vascular response (angiogenesis vs. tissue deformation), however, is yet unelucidated, requiring network registration advancements. Overall, the combination of two-photon angiography, vectorization, reconstruction/visualization, and statistical analysis enables both qualitative and quantitative assessments of neu-rovascular remodeling dynamics, demonstrating an impactful method for investigating neuro-microvascular network disorders and the therapeutic modes of action thereof. Understanding the timing and nature of neurovascular remodeling allows for optimized interventions, including personalized medicine for stroke rehabilitation. Additionally, the evaluation of pharmaceutical interventions using these tools may facilitate targeted drug development. Furthermore, neurovascular coupling dynamics have implications for neurodegenerative diseases, brain aging, and the field of brain-computer interfaces.

neuroscience↗

bioRxiv2022

Interpreting ICT: from Blood Flow to Vascular Network

The inverse correlation time (ICT) is a key quantity in laser speckle contrast imaging (LSCI) measurements. Traditionally, ICT is regarded as a metric of blood flow, such as speed or perfusion. However, we highlight that ICT not only contains important information about blood flow, but also reflects the underlying structure of the vascular network. In the past, ICT has been found to be correlated with vessel diameter. Here, we further report that ICT exhibits a different sensitivity to blood flow depending on vessel orientation. Specifically, ICT is more sensitive to blood flow speed changes in vessels descending from or arising to the tissue surface, compared with those laying parallel to the surface. Those findings shift our understanding of ICT from purely blood flow to a combination of blood flow and vascular network structure. We also develop theories to facilitate the study of vascular networks impact on ICT.

bioengineering↗

bioRxiv2020

Establishing the Effect of Vascular Structure on Laser Speckle Contrast Imagining

Laser Speckle Contrast Imaging (LSCI) is a powerful tool for non-invasive, real-time imaging of blood flow in tissue. However, the effect of tissue geometry on the form of the electric field autocorrelation function and speckle contrast values is yet to be investigated. In this paper, we present an ultrafast forward model for simulating a speckle contrast image with the ability to rapidly update the image for a desired illumination pattern and flow perturbation. We demonstrate the first simulated speckle contrast image and compare it against experimental results. We simulate three mouse-specific cerebral cortex decorrelation time images and implement three different schemes for analyzing the effects of homogenization of vascular structure on correlation decay times. Our results indicate that dissolving structure and assuming homogeneous geometry creates up to ∼ 10x shift in the correlation function decay times and alters its form compared with the case for which the exact geometry is simulated. These effects are more pronounced for point illumination and detection imaging schemes. Further analysis indicates that correlated multiple scattering events, on average, account for 50% of all dynamic scattering events for a detector over a vessel region and 31% that of a detector over parenchyma region, highlighting the significance of accurate modeling of the three-dimensional vascular geometry for accurate blood flow estimates.Competing Interest StatementThe authors have declared no competing interest.View Full Text

bioengineering↗