Modeling of Cerebral Oxygen Transport Based on In vivo Microscopic Imaging of Microvascular Network Structure, Blood Flow, and Oxygenation

Depth-Dependent Contributions of Various Vascular Zones to Cerebral Autoregulation and Functional Hyperemia: An In-Silico Analysis

Autoregulation and neurogliavascular coupling are key mechanisms that modulate myogenic tone (MT) in vessels to regulate cerebral blood flow (CBF) during resting state and periods of increased neural activity, respectively. To determine relative contributions of distinct vascular zones across different cortical depths in CBF regulation, we developed a simplified yet detailed and computationally efficient model of the mouse cerebrovasculature. The model integrates multiple simplifications and generalizations regarding vascular morphology, the hierarchical organization of mural cells, and potentiation/inhibition of MT in vessels. Our analysis showed that autoregulation is the result of the synergy between these factors, but achieving an optimal balance across all cortical depths and throughout the autoregulation range is a complex task. This complexity explains the non-uniformity observed experimentally in capillary blood flow at different cortical depths. In silico simulations of cerebral autoregulation support the idea that the cerebral vasculature does not maintain a plateau of blood flow throughout the autoregulatory range and consists of both flat and sloped phases. We learned that small-diameter vessels with large contractility, such as penetrating arterioles and precapillary arterioles, have major control over intravascular pressure at the entry points of capillaries and play a significant role in CBF regulation. However, temporal alterations in capillary diameter contribute moderately to cerebral autoregulation and minimally to functional hyperemia. In addition, hemodynamic analysis shows that while hemodynamics within capillaries remain relatively stable across all cortical depths throughout the entire autoregulation range, significant variability in hemodynamics can be observed within the first few branch orders of precapillary arterioles or transitional zone vessels. The computationally efficient cerebrovasculature model, proposed in this study, provides a novel framework for analyzing dynamics of the CBF regulation where hemodynamic and vasodynamic interactions are the foundation on which more sophisticated models can be developed.

Modeling hypoxia-induced radiation resistance and the impact of radiation sources

Hypoxia contributes significantly to resistance in radiotherapy. Our research rigorously examines the influence of microvascular morphology on radiotherapy outcome, specifically focusing on how microvasculature shapes hypoxia within the microenvironment and affects resistance to a standard treatment regimen (30×2GyRBE). Our computational modeling extends to the effects of different radiation sources. For photons and protons, our analysis establishes a clear correlation between hypoxic volume distribution and treatment effectiveness, with vascular density and regularity playing a crucial role in treatment success. On the contrary, carbon ions exhibit distinct effectiveness, even in areas of intense hypoxia and poor vascularization. This finding points to the potential of carbon-based hadron therapy in overcoming hypoxia-induced resistance to RT. Considering that the spatial scale analyzed in this study is closely aligned with that of imaging data voxels, we also address the implications of these findings in a clinical context envisioning the possibility of detecting subvoxel hypoxia.

Revisiting hemodynamics and blood oxygenation in a microfluidic microvasculature replica

The complexity of microvascular circulation has led to the development of advanced imaging techniques and biomimetic models. This study developed a multifaceted microfluidic-based microdevice as an in vitro model of microvasculature to replicate important geometric and functional features of in vivo perfusion in mice. The microfluidic device consisted of a microchannel for blood perfusion, mirroring the natural hierarchical branching vascular structures found in mice. Additionally, the device incorporated a steady gradient of oxygen (O2) which diffused through the polydimethylsiloxane (PDMS) layer, allowing for dynamic blood oxygenation. The assembled multi-layered microdevice was accompanied by a dual-modal imaging system that combined laser speckle contrast imaging (LSCI) and intrinsic signal optical imaging (ISOI) to visualize full-field blood flow distributions and blood O2 profiles. By closely reproducing in vivo blood perfusion and oxygenation conditions, this microvasculature model, in conjunction with numerical simulation results, can provide quantitative information on physiologically relevant hemodynamics and key O2 transport parameters that are not directly measurable in traditional animal studies.

Simulating photodynamic therapy for the treatment of glioblastoma using Monte Carlo radiative transport

Significance

Glioblastoma (GBM) is a rare but deadly form of brain tumor with a low median survival rate of 14.6 months, due to its resistance to treatment. An independent simulation of the INtraoperative photoDYnamic therapy for GliOblastoma (INDYGO) trial, a clinical trial aiming to treat the GBM resection cavity with photodynamic therapy (PDT) via a laser coupled balloon device, is demonstrated.

Aim

To develop a framework providing increased understanding for the PDT treatment, its parameters, and their impact on the clinical outcome.

Approach

We use Monte Carlo radiative transport techniques within a computational brain model containing a GBM to simulate light path and PDT effects. Treatment parameters (laser power, photosensitizer concentration, and irradiation time) are considered, as well as PDT's impact on brain tissue temperature.

Results

The simulation suggests that 39% of post-resection GBM cells are killed at the end of treatment when using the standard INDYGO trial protocol (light fluence = 200    J / cm 2 at balloon wall) and assuming an initial photosensitizer concentration of 5    μ M . Increases in treatment time and light power (light fluence = 400    J / cm 2 at balloon wall) result in further cell kill but increase brain cell temperature, which potentially affects treatment safety. Increasing the p hotosensitizer concentration produces the most significant increase in cell kill, with 61% of GBM cells killed when doubling concentration to 10    μ M and keeping the treatment time and power the same. According to these simulations, the standard trial protocol is reasonably well optimized with improvements in cell kill difficult to achieve without potentially dangerous increases in temperature. To improve treatment outcome, focus should be placed on improving the photosensitizer.

Conclusions

With further development and optimization, the simulation could have potential clinical benefit and be used to help plan and optimize intraoperative PDT treatment for GBM.

Cortical microvascular blood flow velocity mapping by combining dynamic light scattering optical coherence tomography and two-photon microscopy

Significance

The accurate large-scale mapping of cerebral microvascular blood flow velocity is crucial for a better understanding of cerebral blood flow (CBF) regulation. Although optical imaging techniques enable both high-resolution microvascular angiography and fast absolute CBF velocity measurements in the mouse cortex, they usually require different imaging techniques with independent system configurations to maximize their performances. Consequently, it is still a challenge to accurately combine functional and morphological measurements to co-register CBF speed distribution from hundreds of microvessels with high-resolution microvascular angiograms.

Aim

We propose a data acquisition and processing framework to co-register a large set of microvascular blood flow velocity measurements from dynamic light scattering optical coherence tomography (DLS-OCT) with the corresponding microvascular angiogram obtained using two-photon microscopy (2PM).

Approach

We used DLS-OCT to first rapidly acquire a large set of microvascular velocities through a sealed cranial window in mice and then to acquire high-resolution microvascular angiograms using 2PM. The acquired data were processed in three steps: (i) 2PM angiogram coregistration with the DLS-OCT angiogram, (ii) 2PM angiogram segmentation and graphing, and (iii) mapping of the CBF velocities to the graph representation of the 2PM angiogram.

Results

We implemented the developed framework on the three datasets acquired from the mice cortices to facilitate the coregistration of the large sets of DLS-OCT flow velocity measurements with 2PM angiograms. We retrieved the distributions of red blood cell velocities in arterioles, venules, and capillaries as a function of the branching order from precapillary arterioles and postcapillary venules from more than 1000 microvascular segments.

Conclusions

The proposed framework may serve as a useful tool for quantitative analysis of large microvascular datasets obtained by OCT and 2PM in studies involving normal brain functioning, progression of various diseases, and numerical modeling of the oxygen advection and diffusion in the realistic microvascular networks.

HIV-1 Tat-mediated microglial ferroptosis involves the miR-204–ACSL4 signaling axis

This study was focused on exploring the role of the HIV-1 Tat protein in mediating microglial ferroptosis. Exposure of mouse primary microglial cells (mPMs) to HIV-1 Tat protein resulted in induction of ferroptosis, which was characterized by increased expression of Acyl-CoA synthetase long-chain family member 4 (ACSL4), in turn, leading to increased generation of oxidized phosphatidylethanolamine, elevated levels of lipid peroxidation, upregulated labile iron pool (LIP) and ferritin heavy chain-1 (FTH1), decreased glutathione peroxidase-4 and mitochondrial outer membrane rupture. Also, inhibition of ferroptosis by ferrostatin-1 (Fer-1) or deferoxamine (DFO) treatment suppressed ferroptosis-related changes in mPMs. Similarly, the knockdown of ACSL4 by gene silencing also inhibited ferroptosis induced by HIV-1 Tat. Furthermore, increased lipid peroxidation resulted in increased release of proinflammatory cytokines, such as TNFα, IL6, and IL1β and microglial activation. Pretreatment of mPMs with Fer-1 or DFO further blocked HIV-1 Tat-mediated microglial activation in vitro and reduced the expression and release of proinflammatory cytokines. We identified miR-204 as an upstream modulator of ACSL4, which was downregulated in mPMs exposed to HIV-1 Tat. Transient transfection of mPMs with miR-204 mimics reduced the expression of ACSL4 while inhibiting HIV-1 Tat-mediated ferroptosis and the release of proinflammatory cytokines. These in vitro findings were further validated in HIV-1 transgenic rats as well as HIV + ve human brain samples. Overall, this study underscores a novel mechanism(s) underlying HIV-1 Tat-mediated ferroptosis and microglial activation involving miR-204-ACSL4 signaling.

Computational cardiac physiology for new modelers: Origins, foundations, and future

Mathematical models of the cardiovascular system have come a long way since they were first introduced in the early 19th century. Driven by a rapid development of experimental techniques, numerical methods, and computer hardware, detailed models that describe physical scales from the molecular level up to organs and organ systems have been derived and used for physiological research. Mathematical and computational models can be seen as condensed and quantitative formulations of extensive physiological knowledge and are used for formulating and testing hypotheses, interpreting and directing experimental research, and have contributed substantially to our understanding of cardiovascular physiology. However, in spite of the strengths of mathematics to precisely describe complex relationships and the obvious need for the mathematical and computational models to be informed by experimental data, there still exist considerable barriers between experimental and computational physiological research. In this review, we present a historical overview of the development of mathematical and computational models in cardiovascular physiology, including the current state of the art. We further argue why a tighter integration is needed between experimental and computational scientists in physiology, and point out important obstacles and challenges that must be overcome in order to fully realize the synergy of experimental and computational physiological research.

Hybrid fiber optic-fMRI for multimodal cell-specific recording and manipulation of neural activity in rodents

Significance: Multiscale imaging holds particular relevance to neuroscience, where it helps integrate the cellular and molecular biological scale, which is most accessible to interventions, with holistic organ-level evaluations, most relevant with respect to function. Being inextricably interdisciplinary, multiscale imaging benefits substantially from incremental technology adoption, and a detailed overview of the state-of-the-art is vital to an informed application of imaging methods. Aim: In this article, we lay out the background and methodological aspects of multimodal approaches combining functional magnetic resonance imaging (fMRI) with simultaneous optical measurement or stimulation. Approach: We focus on optical techniques as these allow, in conjunction with genetically encoded proteins (e.g. calcium indicators or optical signal transducers), unprecedented read-out and control specificity for individual cell-types during fMRI experiments, while leveraging non-interfering modalities. Results: A variety of different solutions for optical/fMRI methods has been reported ranging from bulk fluorescence recordings via fiber photometry to high resolution microscopy. In particular, the plethora of optogenetic tools has enabled the transformation of stimulus-evoked fMRI into a cell biological interrogation method. We discuss the capabilities and limitations of these genetically encoded molecular tools in the study of brain phenomena of great methodological and neuropsychiatric interest-such as neurovascular coupling (NVC) and neuronal network mapping. We provide a methodological description of this interdisciplinary field of study, and focus in particular on the limitations of the widely used blood oxygen level dependent (BOLD) signal and how multimodal readouts can shed light on the contributions arising from neurons, astrocytes, or the vasculature. Conclusion: We conclude that information from multiple signaling pathways must be incorporated in future forward models of the BOLD response to prevent erroneous conclusions when using fMRI as a surrogate measure for neural activity. Further, we highlight the potential of direct neuronal stimulation via genetically defined brain networks towards advancing neurophysiological understanding and better estimating effective connectivity.

Hyperspectral Wide-Field-Of-View Imaging to Study Dynamic Microcirculatory Changes During Hypoxia

OBJECTIVE

Hyperspectral imaging (HSI) provides a fast, reliable, and non-invasive way the study vascular microcirculation in animal models. Rapid hyperspectral imaging of large portions of the microcirculatory preparation is critical for understanding the function and regulation of vascular microcirculatory networks.

METHODS

This report presents the application of an off-the-shelf, benchtop, HSI linear scanning system to acquire larger field-of-view images of microcirculatory preparations. The HSI line detector was displaced perpendicular to the scanning direction to map larger areas, with a rate of displacement determined by the scanning rate and the exposure time. The collected image was analyzed to determine dynamic changes in the microcirculation.

RESULTS

The system records dynamic changes in microvascular hemoglobin (Hb) oxygen (O₂) saturation and vascular morphology during hypoxia and reoxygenation and has similar acquisition speeds to commonly referenced spectral-scanning HSI systems. Additionally, the HbO₂ saturations collected via HSI closely correlate with those collected by phosphorescence quenching microscopy.

CONCLUSION

The reported system enables dynamic functional microcirculation imaging for broad experimental and clinical applications.

Challenges and opportunities of integrating imaging and mathematical modelling to interrogate biological processes

Advances in biological imaging have accelerated our understanding of human physiology in both health and disease. As these advances have developed, the opportunities gained by integrating with cutting-edge mathematical models have become apparent yet remain challenging. Combined imaging-modelling approaches provide unprecedented opportunity to correlate data on tissue architecture and function, across length and time scales, to better understand the mechanisms that underpin fundamental biology and also to inform clinical decisions. Here we discuss the opportunities and challenges of such approaches, providing literature examples across a range of organ systems. Given the breadth of the field we focus on the intersection of continuum modelling and in vivo imaging applied to the vasculature and blood flow, though our rationale and conclusions extend widely. We propose three key research pillars (image acquisition, image processing, mathematical modelling) and present their respective advances as well as future opportunity via better integration. Multidisciplinary efforts that develop imaging and modelling tools concurrently, and share them open-source with the research community, provide exciting opportunity for advancing these fields.

Network-driven anomalous transport is a fundamental component of brain microvascular dysfunction

Blood microcirculation supplies neurons with oxygen and nutrients, and contributes to clearing their neurotoxic waste, through a dense capillary network connected to larger tree-like vessels. This complex microvascular architecture results in highly heterogeneous blood flow and travel time distributions, whose origin and consequences on brain pathophysiology are poorly understood. Here, we analyze highly-resolved intracortical blood flow and transport simulations to establish the physical laws governing the macroscopic transport properties in the brain micro-circulation. We show that network-driven anomalous transport leads to the emergence of critical regions, whether hypoxic or with high concentrations of amyloid-β, a waste product centrally involved in Alzheimer's Disease. We develop a Continuous-Time Random Walk theory capturing these dynamics and predicting that such critical regions appear much earlier than anticipated by current empirical models under mild hypoperfusion. These findings provide a framework for understanding and modelling the impact of microvascular dysfunction in brain diseases, including Alzheimer's Disease.

Imaging faster neural dynamics with fast fMRI: A need for updated models of the hemodynamic response

Fast fMRI enables the detection of neural dynamics over timescales of hundreds of milliseconds, suggesting it may provide a new avenue for studying subsecond neural processes in the human brain. The magnitudes of these fast fMRI dynamics are far greater than predicted by canonical models of the hemodynamic response. Several studies have established nonlinear properties of the hemodynamic response that have significant implications for fast fMRI. We first review nonlinear properties of the hemodynamic response function that may underlie fast fMRI signals. We then illustrate the breakdown of canonical hemodynamic response models in the context of fast neural dynamics. We will then argue that the canonical hemodynamic response function is not likely to reflect the BOLD response to neuronal activity driven by sparse or naturalistic stimuli or perhaps to spontaneous neuronal fluctuations in the resting state. These properties suggest that fast fMRI is capable of tracking surprisingly fast neuronal dynamics, and we discuss the neuroscientific questions that could be addressed using this approach.

Parallel generation of extensive vascular networks with application to an archetypal human kidney model

Given the relevance of the inextricable coupling between microcirculation and physiology, and the relation to organ function and disease progression, the construction of synthetic vascular networks for mathematical modelling and computer simulation is becoming an increasingly broad field of research. Building vascular networks that mimic in vivo morphometry is feasible through algorithms such as constrained constructive optimization (CCO) and variations. Nevertheless, these methods are limited by the maximum number of vessels to be generated due to the whole network update required at each vessel addition. In this work, we propose a CCO-based approach endowed with a domain decomposition strategy to concurrently create vascular networks. The performance of this approach is evaluated by analysing the agreement with the sequentially generated networks and studying the scalability when building vascular networks up to 200 000 vascular segments. Finally, we apply our method to vascularize a highly complex geometry corresponding to the cortex of a prototypical human kidney. The technique presented in this work enables the automatic generation of extensive vascular networks, removing the limitation from previous works. Thus, we can extend vascular networks (e.g. obtained from medical images) to pre-arteriolar level, yielding patient-specific whole-organ vascular models with an unprecedented level of detail.

Control of low flow regions in the cortical vasculature determines optimal arterio-venous ratios

The energy demands of neurons are met by a constant supply of glucose and oxygen via the cerebral vasculature. The cerebral cortex is perfused by dense, parallel arterioles and venules, consistently in imbalanced ratios. Whether and how arteriole-venule arrangement and ratio affect the efficiency of energy delivery to the cortex has remained an unanswered question. Here, we show by mathematical modeling and analysis of the mapped mouse sensory cortex that the perfusive efficiency of the network is predicted to be limited by low-flow regions produced between pairs of arterioles or pairs of venules. Increasing either arteriole or venule density decreases the size of these low-flow regions, but increases their number, setting an optimal ratio between arterioles and venules that matches closely that observed across mammalian cortical vasculature. Low-flow regions are reshaped in complex ways by changes in vascular conductance, creating geometric challenges for matching cortical perfusion with neuronal activity.

Theranostic applications of optical coherence tomography in neurosurgery?

In light of our own experiences, we value the existing literature to critically point out possible “near” future applications of optical coherence tomography (OCT) as an intraoperative neurosurgical guidance tool. “Pub Med”, “Cochrane Library”, “Crossref Metadata Search”, and “IEEE Xplore” databases as well as the search engine “Google Scholar” were screened for “optical coherence tomography + neurosurgery”, “optical coherence tomography + intraoperative imaging + neurosurgery”, and “microscope integrated optical coherence tomography + neurosurgery”. n = 51 articles related to the use of OCT as an imaging technique in the field of neurosurgery or neurosurgical research. n = 7 articles documented the intraoperative use of OCT in patients. n = 4 articles documented the use of microscope-integrated optical coherence tomography as a neurosurgical guidance tool. The Results demonstrate that OCT is the first imaging technique to study microanatomy in vivo. Postoperative analysis of intraoperative scans holds promise to enrich our physiological and pathophysiological understanding of the human brain. No data exists to prove that OCT-guided surgery minimizes perioperative morbidity or extends tumor resection. But results suggest that regular use of microscope-integrated OCT could increase security during certain critical microsurgical steps like, e.g., dural dissection at cavernous sinus, transtentorial approaches, or aneurysm clip placement. Endoscopy integration could aid surgery in regions which are not yet accessible to real-time imaging modalities like the ventricles or hypophysis. Theranostic instruments which combine OCT with laser ablation might gain importance in the emerging field of minimal invasive tumor surgery. OCT depicts vessel wall layers and its pathologies uniquely. Doppler OCT could further visualize blood flow in parallel. These abilities shed light on promising future applications in the field of vascular neurosurgery.

Location Matters: Navigating Regional Heterogeneity of the Neurovascular Unit

The neurovascular unit (NVU) of the brain is composed of multiple cell types that act synergistically to modify blood flow to locally match the energy demand of neural activity, as well as to maintain the integrity of the blood-brain barrier (BBB). It is becoming increasingly recognized that the functional specialization, as well as the cellular composition of the NVU varies spatially. This heterogeneity is encountered as variations in vascular and perivascular cells along the arteriole-capillary-venule axis, as well as through differences in NVU composition throughout anatomical regions of the brain. Given the wide variations in metabolic demands between brain regions, especially those of gray vs. white matter, the spatial heterogeneity of the NVU is critical to brain function. Here we review recent evidence demonstrating regional specialization of the NVU between brain regions, by focusing on the heterogeneity of its individual cellular components and briefly discussing novel approaches to investigate NVU diversity.

A Mesoscale Computational Model for Microvascular Oxygen Transfer

We address a mathematical model for oxygen transfer in the microcirculation. The model includes blood flow and hematocrit transport coupled with the interstitial flow, oxygen transport in the blood and the tissue, including capillary-tissue exchange effects. Moreover, the model is suited to handle arbitrarily complex vascular geometries. The purpose of this study is the validation of the model with respect to classical solutions and the further demonstration of its adequacy to describe the heterogeneity of oxygenation in the tissue microenvironment. Finally, we discuss the importance of these effects in the treatment of cancer using radiotherapy.

A Suite of Neurophotonic Tools to Underpin the Contribution of Internal Brain States in fMRI

Recent developments in optical microscopy, applicable for large-scale and longitudinal imaging of cortical activity in behaving animals, open unprecedented opportunities to gain a deeper understanding of neurovascular and neurometabolic coupling during different brain states. Future studies will leverage these tools to deliver foundational knowledge about brain state-dependent regulation of cerebral blood flow and metabolism as well as regulation as a function of brain maturation and aging. This knowledge is of critical importance to interpret hemodynamic signals observed with functional magnetic resonance imaging (fMRI).

Tissue clearing and imaging methods for cardiovascular development

Tissue imaging in 3D using visible light is limited and various clearing techniques were developed to increase imaging depth, but none provides universal solution for all tissues at all developmental stages. In this review, we focus on different tissue clearing methods for 3D imaging of heart and vasculature, based on chemical composition (solvent-based, simple immersion, hyperhydration, and hydrogel embedding techniques). We discuss in detail compatibility of various tissue clearing techniques with visualization methods: fluorescence preservation, immunohistochemistry, nuclear staining, and fluorescent dyes vascular perfusion. We also discuss myocardium visualization using autofluorescence, tissue shrinking, and expansion. Then we overview imaging methods used to study cardiovascular system and live imaging. We discuss heart and vessels segmentation methods and image analysis. The review covers the whole process of cardiovascular system 3D imaging, starting from tissue clearing and its compatibility with various visualization methods to the types of imaging methods and resulting image analysis.

A multiscale computational model of angiogenesis after traumatic brain injury, investigating the role location plays in volumetric recovery

Vascular endothelial growth factor (VEGF) is a key protein involved in the process of angiogenesis. VEGF is of particular interest after a traumatic brain injury (TBI), as it re-establishes the cerebral vascular network in effort to allow for proper cerebral blood flow and thereby oxygenation of damaged brain tissue. For this reason, angiogenesis is critical in the progression and recovery of TBI patients in the days and weeks post injury. Although well established experimental work has led to advances in our understanding of TBI and the progression of angiogenisis, many constraints still exist with existing methods, especially when considering patient progression in the days following injury. To better understand the healing process on the proposed time scales, we develop a computational model that quickly simulates vessel growth and recovery by coupling VEGF and its interactions with its associated receptors to a physiologically inspired fractal model of the microvascular re-growth. We use this model to clarify the role that diffusivity, receptor kinetics and location of the TBI play in overall blood volume restoration in the weeks post injury and show that proper therapeutic angiogenesis, or vasculogenic therapies, could speed recovery of the patient as a function of the location of injury.

Mathematical synthesis of the cortical circulation for the whole mouse brain-part II: Microcirculatory closure

Recent advancements in multiphoton imaging and vascular reconstruction algorithms have increased the amount of data on cerebrovascular circulation for statistical analysis and hemodynamic simulations. Experimental observations offer fundamental insights into capillary network topology but mainly within a narrow field of view typically spanning a small fraction of the cortical surface (less than 2%). In contrast, larger-resolution imaging modalities, such as computed tomography (CT) or magnetic resonance imaging (MRI), have whole-brain coverage but capture only larger blood vessels, overlooking the microscopic capillary bed. To integrate data acquired at multiple length scales with different neuroimaging modalities and to reconcile brain-wide macroscale information with microscale multiphoton data, we developed a method for synthesizing hemodynamically equivalent vascular networks for the entire cerebral circulation. This computational approach is intended to aid in the quantification of patterns of cerebral blood flow and metabolism for the entire brain. In part I, we described the mathematical framework for image-guided generation of synthetic vascular networks covering the large cerebral arteries from the circle of Willis through the pial surface network leading back to the venous sinuses. Here in part II, we introduce novel procedures for creating microcirculatory closure that mimics a realistic capillary bed. We demonstrate our capability to synthesize synthetic vascular networks whose morphometrics match empirical network graphs from three independent state-of-the-art imaging laboratories using different image acquisition and reconstruction protocols. We also successfully synthesized twelve vascular networks of a complete mouse brain hemisphere suitable for performing whole-brain blood flow simulations. Synthetic arterial and venous networks with microvascular closure allow whole-brain hemodynamic predictions. Simulations across all length scales will potentially illuminate organ-wide supply and metabolic functions that are inaccessible to models reconstructed from image data with limited spatial coverage.

Simulation of oxygen transport and estimation of tissue perfusion in extensive microvascular networks: Application to cerebral cortex

Advanced imaging techniques have made available extensive three-dimensional microvascular network structures. Simulation of oxygen transport by such networks requires information on blood flow rates and oxygen levels in vessels crossing boundaries of the imaged region, which is difficult to obtain experimentally. Here, a computational method is presented for estimating blood flow rates, oxygen levels, tissue perfusion and oxygen extraction, based on incomplete boundary conditions. Flow rates in all segments are estimated using a previously published method. Vessels crossing the region boundary are classified as arterioles, capillaries or venules. Oxygen levels in inflowing capillaries are assigned based on values in outflowing capillaries, and similarly for venules. Convective and diffusive oxygen transport is simulated. Contributions of each vessel to perfusion are computed in proportion to the decline in oxygen concentration along that vessel. For a vascular network in the mouse cerebral cortex, predicted tissue oxygen levels show a broad distribution, with 99% of tissue in the range of 20 to 80 mmHg under reference conditions, and steep gradients near arterioles. Perfusion and extraction estimates are consistent with experimental values. A 30% reduction in perfusion or a 30% increase in oxygen demand, relative to reference levels, is predicted to result in tissue hypoxia.

Voxelized simulation of cerebral oxygen perfusion elucidates hypoxia in aged mouse cortex

Departures of normal blood flow and metabolite distribution from the cerebral microvasculature into neuronal tissue have been implicated with age-related neurodegeneration. Mathematical models informed by spatially and temporally distributed neuroimage data are becoming instrumental for reconstructing a coherent picture of normal and pathological oxygen delivery throughout the brain. Unfortunately, current mathematical models of cerebral blood flow and oxygen exchange become excessively large in size. They further suffer from boundary effects due to incomplete or physiologically inaccurate computational domains, numerical instabilities due to enormous length scale differences, and convergence problems associated with condition number deterioration at fine mesh resolutions. Our proposed simple finite volume discretization scheme for blood and oxygen microperfusion simulations does not require expensive mesh generation leading to the critical benefit that it drastically reduces matrix size and bandwidth of the coupled oxygen transfer problem. The compact problem formulation yields rapid and stable convergence. Moreover, boundary effects can effectively be suppressed by generating very large replica of the cortical microcirculation in silico using an image-based cerebrovascular network synthesis algorithm, so that boundaries of the perfusion simulations are far removed from the regions of interest. Massive simulations over sizeable portions of the cortex with feature resolution down to the micron scale become tractable with even modest computer resources. The feasibility and accuracy of the novel method is demonstrated and validated with in vivo oxygen perfusion data in cohorts of young and aged mice. Our oxygen exchange simulations quantify steep gradients near penetrating blood vessels and point towards pathological changes that might cause neurodegeneration in aged brains. This research aims to explain mechanistic interactions between anatomical structures and how they might change in diseases or with age. Rigorous quantification of age-related changes is of significant interest because it might aide in the search for imaging biomarkers for dementia and Alzheimer’s disease.

Brain function critically depends on the maintenance of physiological blood supply and metabolism in the cortex. Disturbances to adequate perfusion have been linked to age-related neurodegeneration. However, the precise correlation between age-related hemodynamic changes and the resulting decline in oxygen delivery is not well understood and has not been quantified. Therefore, we introduce a new compact, and therefore highly scalable, computational method for predicting the physiological relationship between hemodynamics and cortical oxygen perfusion for large sections of the cortical microcirculation. We demonstrate the novel mesh generation-free (MGF), multi-scale simulation approach through realistic in vivo case studies of cortical microperfusion in the mouse brain. We further validate mechanistic correlations and a quantitative relationship between blood flow and brain oxygenation using experimental data from cohorts of young, middle aged and old mouse brains. Our computational approach overcomes size and performance limitations of previous unstructured meshing techniques to enable the prediction of oxygen tension with a spatial resolution of least two orders of magnitude higher than previously possible. Our simulation results support the hypothesis that structural changes in the microvasculature induce hypoxic pockets in the aged brain that are absent in the healthy, young mouse.

Anatomical Modeling of Brain Vasculature in Two-Photon Microscopy by Generalizable Deep Learning

Objective and Impact Statement. Segmentation of blood vessels from two-photon microscopy (2PM) angiograms of brains has important applications in hemodynamic analysis and disease diagnosis. Here, we develop a generalizable deep learning technique for accurate 2PM vascular segmentation of sizable regions in mouse brains acquired from multiple 2PM setups. The technique is computationally efficient, thus ideal for large-scale neurovascular analysis. Introduction. Vascular segmentation from 2PM angiograms is an important first step in hemodynamic modeling of brain vasculature. Existing segmentation methods based on deep learning either lack the ability to generalize to data from different imaging systems or are computationally infeasible for large-scale angiograms. In this work, we overcome both these limitations by a method that is generalizable to various imaging systems and is able to segment large-scale angiograms. Methods. We employ a computationally efficient deep learning framework with a loss function that incorporates a balanced binary-cross-entropy loss and total variation regularization on the network’s output. Its effectiveness is demonstrated on experimentally acquired in vivo angiograms from mouse brains of dimensions up to 808×808×702 μm. Results. To demonstrate the superior generalizability of our framework, we train on data from only one 2PM microscope and demonstrate high-quality segmentation on data from a different microscope without any network tuning. Overall, our method demonstrates 10× faster computation in terms of voxels-segmented-per-second and 3× larger depth compared to the state-of-the-art. Conclusion. Our work provides a generalizable and computationally efficient anatomical modeling framework for brain vasculature, which consists of deep learning-based vascular segmentation followed by graphing. It paves the way for future modeling and analysis of hemodynamic response at much greater scales that were inaccessible before.

Anatomical Modeling of Brain Vasculature in Two-Photon Microscopy by Generalizable Deep Learning

Objective and Impact Statement. Segmentation of blood vessels from two-photon microscopy (2PM) angiograms of brains has important applications in hemodynamic analysis and disease diagnosis. Here, we develop a generalizable deep learning technique for accurate 2PM vascular segmentation of sizable regions in mouse brains acquired from multiple 2PM setups. The technique is computationally efficient, thus ideal for large-scale neurovascular analysis. Introduction. Vascular segmentation from 2PM angiograms is an important first step in hemodynamic modeling of brain vasculature. Existing segmentation methods based on deep learning either lack the ability to generalize to data from different imaging systems or are computationally infeasible for large-scale angiograms. In this work, we overcome both these limitations by a method that is generalizable to various imaging systems and is able to segment large-scale angiograms. Methods. We employ a computationally efficient deep learning framework with a loss function that incorporates a balanced binary-cross-entropy loss and total variation regularization on the network's output. Its effectiveness is demonstrated on experimentally acquired in vivo angiograms from mouse brains of dimensions up to 808 × 808 × 702   μ m . Results. To demonstrate the superior generalizability of our framework, we train on data from only one 2PM microscope and demonstrate high-quality segmentation on data from a different microscope without any network tuning. Overall, our method demonstrates 10× faster computation in terms of voxels-segmented-per-second and 3× larger depth compared to the state-of-the-art. Conclusion. Our work provides a generalizable and computationally efficient anatomical modeling framework for brain vasculature, which consists of deep learning-based vascular segmentation followed by graphing. It paves the way for future modeling and analysis of hemodynamic response at much greater scales that were inaccessible before.

Blood flow, capillary transit times, and tissue oxygenation: the centennial of capillary recruitment

The transport of oxygen between blood and tissue is limited by blood's capillary transit time, understood as the time available for diffusion exchange before blood returns to the heart. If all capillaries contribute equally to tissue oxygenation at all times, this physical limitation would render vasodilation and increased blood flow insufficient means to meet increased metabolic demands in the heart, muscle, and other organs. In 1920, Danish physiologist August Krogh was awarded the Nobel Prize in Physiology or Medicine for his mathematical and quantitative, experimental demonstration of a solution to this conceptual problem: capillary recruitment, the active opening of previously closed capillaries to meet metabolic demands. Today, capillary recruitment is still mentioned in textbooks. When we suspect symptoms might represent hypoxia of a vascular origin, however, we search for relevant, flow-limiting conditions in our patients and rarely ascribe hypoxia or hypoxemia to short capillary transit times. This review describes how natural changes in capillary transit-time heterogeneity (CTH) and capillary hematocrit (HCT) across open capillaries during blood flow increases can account for a match of oxygen availability to metabolic demands in normal tissue. CTH and HCT depend on a number of factors: on blood properties, including plasma viscosity, the number, size, and deformability of blood cells, and blood cell interactions with capillary endothelium; on anatomical factors including glycocalyx, endothelial cells, basement membrane, and pericytes that affect the capillary diameter; and on any external compression. The review describes how risk factor- and disease-related changes in CTH and HCT interfere with flow-metabolism coupling and tissue oxygenation and discusses whether such capillary dysfunction contributes to vascular disease pathology.

High spatiotemporal vessel-specific hemodynamic mapping with multi-echo single-vessel fMRI

High-resolution fMRI enables noninvasive mapping of the hemodynamic responses from individual penetrating vessels in animal brains. Here, a 2D multi-echo single-vessel fMRI (MESV-fMRI) method has been developed to map the fMRI signal from arterioles and venules with a 100 ms sampling rate at multiple echo times (TE, 3-30 ms) and short acquisition windows (<1 ms). The T₂*-weighted signal shows the increased extravascular effect on venule voxels as a function of TE. In contrast, the arteriole voxels show an increased fMRI signal with earlier onset than venules voxels at the short TE (3 ms) with increased blood inflow and volume effects. MESV-fMRI enables vessel-specific T2* mapping and presents T2*-based fMRI time courses with higher contrast-to-noise ratios (CNRs) than the T2*-weighted fMRI signal at a given TE. The vessel-specific T2* mapping also allows semi-quantitative estimation of the oxygen saturation levels (Y) and their changes (ΔY) at a given blood volume fraction upon neuronal activation. The MESV-fMRI method enables vessel-specific T2* measurements with high spatiotemporal resolution for better modeling of the fMRI signal based on the hemodynamic parameters.

Real-time nanodiamond thermometry probing in vivo thermogenic responses

Real-time temperature monitoring inside living organisms provides a direct measure of their biological activities. However, it is challenging to reduce the size of biocompatible thermometers down to submicrometers, despite their potential applications for the thermal imaging of subtissue structures with single-cell resolution. Here, using quantum nanothermometers based on optically accessible electron spins in nanodiamonds, we demonstrate in vivo real-time temperature monitoring inside Caenorhabditis elegans worms. We developed a microscope system that integrates a quick-docking sample chamber, particle tracking, and an error correction filter for temperature monitoring of mobile nanodiamonds inside live adult worms with a precision of ±0.22°C. With this system, we determined temperature increases based on the worms' thermogenic responses during the chemical stimuli of mitochondrial uncouplers. Our technique demonstrates the submicrometer localization of temperature information in living animals and direct identification of their pharmacological thermogenesis, which may allow for quantification of their biological activities based on temperature.

The mass transfer coefficient for oxygen transport from blood to tissue in cerebral cortex

The functioning of cerebral cortex depends on adequate tissue oxygenation. MRI-based techniques allow estimation of blood oxygen levels, tissue perfusion, and oxygen consumption rate (CMRO₂), but do not directly measure partial pressure of oxygen (PO₂) in tissue. To address the estimation of tissue PO₂, the oxygen mass transfer coefficient (KTO₂) is here defined as the CMRO₂ divided by the difference in spatially averaged PO₂ between blood and tissue, and is estimated by analyzing Krogh-cylinder type models. Resistance to radial diffusion of oxygen from microvessels to tissue is distributed within vessels and in the extravascular tissue. The value of KTO₂ is shown to depend strongly on vascular length density and also on microvessel tube hematocrits and diameters, but to be insensitive to blood flow rate and to transient changes in flow or oxygen consumption. Estimated values of KTO₂ are higher than implied by previous studies, implying smaller declines in PO₂ from blood to tissue. Average tissue PO₂ can be estimated from MRI-based measurements as average blood PO₂ minus the product of KTO₂ and CMRO₂. For oxygen consumption rates and vascular densities typical of mouse cortex, the predicted difference between average blood and tissue PO₂ is about 10 mmHg.

Automatic Graph-Based Modeling of Brain Microvessels Captured With Two-Photon Microscopy

Graph models of cerebral vasculature derived from two-photon microscopy have shown to be relevant to study brain microphysiology. Automatic graphing of these microvessels remain problematic due to the vascular network complexity and two-photon sensitivity limitations with depth. In this paper, we propose a fully automatic processing pipeline to address this issue. The modeling scheme consists of a fully-convolution neural network to segment microvessels, a three-dimensional surface model generator, and a geometry contraction algorithm to produce graphical models with a single connected component. Based on a quantitative assessment using NetMets metrics, at a tolerance of 60 μm, false negative and false positive geometric error 19 rates are 3.8% and 4.2%, respectively, whereas false nega- 20 tive and false positive topological error rates are 6.1% and 4.5%, respectively. Our qualitative evaluation confirms the efficiency of our scheme in generating useful and accurate graphical models.

Small Vessels Are a Big Problem in Neurodegeneration and Neuroprotection

The cerebral microcirculation holds a critical position to match the high metabolic demand by neuronal activity. Functionally, microcirculation is virtually inseparable from other nervous system cells under both physiological and pathological conditions. For successful bench-to-bedside translation of neuroprotection research, the role of microcirculation in acute and chronic neurodegenerative disorders appears to be under-recognized, which may have contributed to clinical trial failures with some neuroprotectants. Increasing data over the last decade suggest that microcirculatory impairments such as endothelial or pericyte dysfunction, morphological irregularities in capillaries or frequent dynamic stalls in blood cell flux resulting in excessive heterogeneity in capillary transit may significantly compromise tissue oxygen availability. We now know that ischemia-induced persistent abnormalities in capillary flow negatively impact restoration of reperfusion after recanalization of occluded cerebral arteries. Similarly, microcirculatory impairments can accompany or even precede neural loss in animal models of several neurodegenerative disorders including Alzheimer's disease. Macrovessels are relatively easy to evaluate with radiological or experimental imaging methods but they cannot faithfully reflect the downstream microcirculatory disturbances, which may be quite heterogeneous across the tissue at microscopic scale and/or happen fast and transiently. The complexity and size of the elements of microcirculation, therefore, require utilization of cutting-edge imaging techniques with high spatiotemporal resolution as well as multidisciplinary team effort to disclose microvascular-neurodegenerative connection and to test treatment approaches to advance the field. Developments in two photon microscopy, ultrafast ultrasound, and optical coherence tomography provide valuable experimental tools to reveal those microscopic events with high resolution. Here, we review the up-to-date advances in understanding of the primary microcirculatory abnormalities that can result in neurodegenerative processes and the combined neurovascular protection approaches that can prevent acute as well as chronic neurodegeneration.

More homogeneous capillary flow and oxygenation in deeper cortical layers correlate with increased oxygen extraction

Our understanding of how capillary blood flow and oxygen distribute across cortical layers to meet the local metabolic demand is incomplete. We addressed this question by using two-photon imaging of resting-state microvascular oxygen partial pressure (PO₂) and flow in the whisker barrel cortex in awake mice. Our measurements in layers I-V show that the capillary red-blood-cell flux and oxygenation heterogeneity, and the intracapillary resistance to oxygen delivery, all decrease with depth, reaching a minimum around layer IV, while the depth-dependent oxygen extraction fraction is increased in layer IV, where oxygen demand is presumably the highest. Our findings suggest that more homogeneous distribution of the physiological observables relevant to oxygen transport to tissue is an important part of the microvascular network adaptation to local brain metabolism. These results will inform the biophysical models of layer-specific cerebral oxygen delivery and consumption and improve our understanding of the diseases that affect cerebral microcirculation.

Robust Tracing and Visualization of Heterogeneous Microvascular Networks

Advances in high-throughput imaging allow researchers to collect three-dimensional images of whole organ microvascular networks. These extremely large images contain networks that are highly complex, time consuming to segment, and difficult to visualize. In this paper, we present a framework for segmenting and visualizing vascular networks from terabyte-sized three-dimensional images collected using high-throughput microscopy. While these images require terabytes of storage, the volume devoted to the fiber network is ≈ 4 percent of the total volume size. While the networks themselves are sparse, they are tremendously complex, interconnected, and vary widely in diameter. We describe a parallel GPU-based predictor-corrector method for tracing filaments that is robust to noise and sampling errors common in these data sets. We also propose a number of visualization techniques designed to convey the complex statistical descriptions of fibers across large tissue sections-including commonly studied microvascular characteristics, such as orientation and volume.

Tumor Ensemble-Based Modeling and Visualization of Emergent Angiogenic Heterogeneity in Breast Cancer

There is a critical need for new tools to investigate the spatio-temporal heterogeneity and phenotypic alterations that arise in the tumor microenvironment. However, computational investigations of emergent inter- and intra-tumor angiogenic heterogeneity necessitate 3D microvascular data from 'whole-tumors' as well as "ensembles" of tumors. Until recently, technical limitations such as 3D imaging capabilities, computational power and cost precluded the incorporation of whole-tumor microvascular data in computational models. Here, we describe a novel computational approach based on multimodality, 3D whole-tumor imaging data acquired from eight orthotopic breast tumor xenografts (i.e. a tumor 'ensemble'). We assessed the heterogeneous angiogenic landscape from the microvascular to tumor ensemble scale in terms of vascular morphology, emergent hemodynamics and intravascular oxygenation. We demonstrate how the abnormal organization and hemodynamics of the tumor microvasculature give rise to unique microvascular niches within the tumor and contribute to inter- and intra-tumor heterogeneity. These tumor ensemble-based simulations together with unique data visualization approaches establish the foundation of a novel 'cancer atlas' for investigators to develop their own in silico systems biology applications. We expect this hybrid image-based modeling framework to be adaptable for the study of other tissues (e.g. brain, heart) and other vasculature-dependent diseases (e.g. stroke, myocardial infarction).

Awake Mouse Imaging: From Two-Photon Microscopy to Blood Oxygen Level-Dependent Functional Magnetic Resonance Imaging

BACKGROUND

Functional magnetic resonance imaging (fMRI) in awake behaving mice is well positioned to bridge the detailed cellular-level view of brain activity, which has become available owing to recent advances in microscopic optical imaging and genetics, to the macroscopic scale of human noninvasive observables. However, though microscopic (e.g., two-photon imaging) studies in behaving mice have become a reality in many laboratories, awake mouse fMRI remains a challenge. Owing to variability in behavior among animals, performing all types of measurements within the same subject is highly desirable and can lead to higher scientific rigor.

METHODS

We demonstrated blood oxygenation level-dependent fMRI in awake mice implanted with long-term cranial windows that allowed optical access for microscopic imaging modalities and optogenetic stimulation. We started with two-photon imaging of single-vessel diameter changes (n = 1). Next, we implemented intrinsic optical imaging of blood oxygenation and flow combined with laser speckle imaging of blood flow obtaining a mesoscopic picture of the hemodynamic response (n = 16). Then we obtained corresponding blood oxygenation level-dependent fMRI data (n = 5). All measurements could be performed in the same mice in response to identical sensory and optogenetic stimuli.

RESULTS

The cranial window did not deteriorate the quality of fMRI and allowed alternation between imaging modalities in each subject.

CONCLUSIONS

This report provides a proof of feasibility for multiscale imaging approaches in awake mice. In the future, this protocol could be extended to include complex cognitive behaviors translatable to humans, such as sensory discrimination or attention.

Deconstructing the principles of ductal network formation in the pancreas

The mammalian pancreas is a branched organ that does not exhibit stereotypic branching patterns, similarly to most other glands. Inside branches, it contains a network of ducts that undergo a transition from unconnected microlumen to a mesh of interconnected ducts and finally to a treelike structure. This ductal remodeling is poorly understood, both on a microscopic and macroscopic level. In this article, we quantify the network properties at different developmental stages. We find that the pancreatic network exhibits stereotypic traits at each stage and that the network properties change with time toward the most economical and optimized delivery of exocrine products into the duodenum. Using in silico modeling, we show how steps of pancreatic network development can be deconstructed into two simple rules likely to be conserved for many other glands. The early stage of the network is explained by noisy, redundant duct connection as new microlumens form. The later transition is attributed to pruning of the network based on the flux of fluid running through the pancreatic network into the duodenum.

In the pancreas of mammals, digestive enzymes are transported from their production site in acini (clusters of cells that secrete the enzymes) to the intestine via a network of ducts. During organ development in fetuses, the ducts initially form by the coordinated polarization of cells to form small holes, which will connect and fuse, to constitute a meshwork. This hyperconnected network further develops into a treelike structure by the time of birth. In this article, we use methods originally developed to analyze road, rail, web, or river networks to quantify the network properties at different developmental stages. We find that the pancreatic network properties are similar between individuals at specific time points but eventually change to achieve the most economical and optimized structure to deliver pancreatic juice into the duodenum. Using in silico modeling, we show how the stages of pancreatic network development follow two simple rules, which are likely to be conserved for the development of other glands. The early stage of the network is explained by noisy, redundant duct connection as new small ductal holes form. Later on, the secretion of fluid that runs through the pancreatic network into the duodenum leads to the widening of ducts with the greatest flow, while nonnecessary ducts are eliminated, akin to how river beds are formed.

In Vivo Imaging of Microglia With Multiphoton Microscopy

Neuroimaging has become an unparalleled tool to understand the central nervous system (CNS) anatomy, physiology and neurological diseases. While an altered immune function and microglia hyperactivation are common neuropathological features for many CNS disorders and neurodegenerative diseases, direct assessment of the role of microglial cells remains a challenging task. Non-invasive neuroimaging techniques, including magnetic resonance imaging (MRI), positron emission tomography (PET) and single positron emission computed tomography (SPECT) are widely used for human clinical applications, and a variety of ligands are available to detect neuroinflammation. In animal models, intravital imaging has been largely used, and minimally invasive multiphoton microcopy (MPM) provides high resolution detection of single microglia cells, longitudinally, in living brain. In this study, we review in vivo real-time MPM approaches to assess microglia in preclinical studies, including individual cell responses in surveillance, support, protection and restoration of brain tissue integrity, synapse formation, homeostasis, as well as in different pathological situations. We focus on in vivo studies that assess the role of microglia in mouse models of Alzheimer’s disease (AD), analyzing microglial motility and recruitment, as well as the role of microglia in anti-amyloid-β treatment, as a key therapeutic approach to treat AD. Altogether, MPM provides a high contrast and high spatial resolution approach to follow microglia chronically in vivo in complex models, supporting MPM as a powerful tool for deep intravital tissue imaging.

Aging-associated changes in cerebral vasculature and blood flow as determined by quantitative optical coherence tomography angiography

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.

Biomimetic 3D-printed neurovascular phantoms for near-infrared fluorescence imaging

Emerging three-dimensional (3D) printing technology enables the fabrication of optically realistic and morphologically complex tissue-simulating phantoms for the development and evaluation of novel optical imaging products. In this study, we assess the potential to print image-defined neurovascular phantoms with patent channels for contrast-enhanced near-infrared fluorescence (NIRF) imaging. An anatomical map defined from clinical magnetic resonance imaging (MRI) was segmented and processed into files suitable for printing a forebrain vessel network in rectangular and curved-surface biomimetic phantoms. Methods for effectively cleaning samples with complex vasculature were determined. A final set of phantoms were imaged with a custom NIRF system at 785 nm excitation using two NIRF contrast agents. In addition to demonstrating the strong potential of 3D printing for creating highly realistic, patient-specific biophotonic phantoms, our work provides insight into optimal methods for accomplishing this goal and elucidates current limitations of this approach.

Capillary flow homogenization during functional activation revealed by optical coherence tomography angiography based capillary velocimetry

Elaborate modeling study suggests an important role of capillary transit time heterogeneity (CTTH) reduction in brain oxygenation during functional hyperemia. Here, we use optical coherence tomography angiography (OCTA) capillary velocimetry to probe blood flow dynamics in cerebral capillary beds and validate the change in CTTH during functional activation in an in vivo rodent model. Through evaluating flow dynamics and consequent transit time parameters from thousands of capillary vessels within three-dimensional (3-D) tissue volume upon hindpaw electrical stimulation, we observe reductions in both capillary mean transit time (MTT) (9.8% ± 2.2) and CTTH (5.9% ± 1.4) in the hindlimb somatosensory cortex (HLS1). Additionally, capillary flow pattern modification is observed with a significant difference (p < 0.05) between the HLS1 and non-activated cortex regions. These quantitative findings reveal a localized microcirculatory adjustment during functional activation, consistent with previous studies, and support the critical contribution of capillary flow homogenization to brain oxygenation. The OCTA velocimetry is a useful tool to image microcirculatory dynamics in vivo using animal models, enabling a more comprehensive understanding as to hemodynamic-metabolic coupling.

Insights into cerebral haemodynamics and oxygenation utilising in vivo mural cell imaging and mathematical modelling

The neurovascular mechanisms underpinning the local regulation of cerebral blood flow (CBF) and oxygen transport remain elusive. In this study we have combined novel in vivo imaging of cortical microvascular and mural cell architecture with mathematical modelling of blood flow and oxygen transport, to provide new insights into CBF regulation that would be inaccessible in a conventional experimental context. Our study indicates that vasoconstriction of smooth muscle actin-covered vessels, rather than pericyte-covered capillaries, induces stable reductions in downstream intravascular capillary and tissue oxygenation. We also propose that seemingly paradoxical observations in the literature around reduced blood velocity in response to arteriolar constrictions might be caused by a propagation of constrictions to upstream penetrating arterioles. We provide support for pericytes acting as signalling conduits for upstream smooth muscle activation, and erythrocyte deformation as a complementary regulatory mechanism. Finally, we caution against the use of blood velocity as a proxy measurement for flow. Our combined imaging-modelling platform complements conventional experimentation allowing cerebrovascular physiology to be probed in unprecedented detail.

Hemorrhagic Shock and the Microvasculature

The microvasculature plays a central role in the pathophysiology of hemorrhagic shock and is also involved in arguably all therapeutic attempts to reverse or minimize the adverse consequences of shock. Microvascular studies specific to hemorrhagic shock were reviewed and broadly grouped depending on whether data were obtained on animal or human subjects. Dedicated sections were assigned to microcirculatory changes in specific organs, and major categories of pathophysiological alterations and mechanisms such as oxygen distribution, ischemia, inflammation, glycocalyx changes, vasomotion, endothelial dysfunction, and coagulopathy as well as biomarkers and some therapeutic strategies. Innovative experimental methods were also reviewed for quantitative microcirculatory assessment as it pertains to changes during hemorrhagic shock. The text and figures include representative quantitative microvascular data obtained in various organs and tissues such as skin, muscle, lung, liver, brain, heart, kidney, pancreas, intestines, and mesentery from various species including mice, rats, hamsters, sheep, swine, bats, and humans. Based on reviewed findings, a new integrative conceptual model is presented that includes about 100 systemic and local factors linked to microvessels in hemorrhagic shock. The combination of systemic measures with the understanding of these processes at the microvascular level is fundamental to further develop targeted and personalized interventions that will reduce tissue injury, organ dysfunction, and ultimately mortality due to hemorrhagic shock. Published 2018. Compr Physiol 8:61-101, 2018.

Functional oxygen extraction fraction (OEF) imaging with turbo gradient spin echo QUIXOTIC (Turbo QUIXOTIC)

PURPOSE

QUantitative Imaging of eXtraction of Oxygen and TIssue Consumption (QUIXOTIC) is a recent technique that measures voxel-wise oxygen extraction fraction (OEF) but suffers from long scan times, limiting its application. We implemented multiecho QUIXOTIC dubbed turbo QUIXOTIC (tQUIXOTIC) that reduces scan time eightfold and then applied it in functional MRI.

METHODS

tQUIXOTIC utilizes a novel turbo gradient spin echo readout enabling measurement of venular blood transverse relaxation rate in a single tag-control acquisition. Using tQUIXOTIC, we estimated cortical gray matter (GM) OEF, created voxel-by-voxel GM OEF maps, and quantified changes in visual cortex OEF during a blocked design flashing checkerboard visual stimulus. Contamination from cerebrospinal fluid partial volume averaging was estimated and corrected.

RESULTS

The average cortical GM OEF was estimated as 0.38 ± 0.06 (n = 8) using a 3.4-min acquisition. The average OEF in the visual cortex was estimated as 0.43 ± 0.04 at baseline and 0.35 ± 0.05 during activation, with an average %ΔOEF of -20%. These values are consistent with those of past studies.

CONCLUSION

tQUIXOTIC successfully estimated cortical GM OEF in clinical scan times and detected changes in OEF during blocked design visual stimulation. tQUIXOTIC will be useful to monitor regional OEF clinically and in blocked design or event-related functional MRI experiments. Magn Reson Med 79:2713-2723, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Theoretical model of blood flow measurement by diffuse correlation spectroscopy

Diffuse correlation spectroscopy (DCS) is a noninvasive method to quantify tissue perfusion from measurements of the intensity temporal autocorrelation function of diffusely scattered light. However, DCS autocorrelation function measurements in tissue better match theoretical predictions based on the diffusive motion of the scatterers than those based on a model where the advective nature of blood flow dominates the stochastic properties of the scattered light. We have recently shown using Monte Carlo (MC) simulations and assuming a simplistic vascular geometry and laminar flow profile that the diffusive nature of the DCS autocorrelation function decay is likely a result of the shear-induced diffusion of the red blood cells. Here, we provide theoretical derivations supporting and generalizing the previous MC results. Based on the theory of diffusing-wave spectroscopy, we derive an expression for the autocorrelation function along the photon path through a vessel that takes into account both diffusive and advective scatterer motion, and we provide the solution for the DCS autocorrelation function in a semi-infinite geometry. We also derive the correlation diffusion and correlation transfer equation, which can be applied for an arbitrary sample geometry. Further, we propose a method to take into account realistic vascular morphology and flow profile.

Two-photon microscopy measurement of cerebral metabolic rate of oxygen using periarteriolar oxygen concentration gradients

The cerebral metabolic rate of oxygen ([Formula: see text]) is an essential parameter for evaluating brain function and pathophysiology. However, the currently available approaches for quantifying [Formula: see text] rely on complex multimodal imaging and mathematical modeling. Here, we introduce a method that allows estimation of [Formula: see text] based on a single measurement modality-two-photon imaging of the partial pressure of oxygen ([Formula: see text]) in cortical tissue. We employed two-photon phosphorescence lifetime microscopy (2PLM) and the oxygen-sensitive nanoprobe PtP-C343 to map the tissue [Formula: see text] distribution around cortical penetrating arterioles. [Formula: see text] is subsequently estimated by fitting the changes of tissue [Formula: see text] around arterioles with the Krogh cylinder model of oxygen diffusion. We measured the baseline [Formula: see text] in anesthetized rats and modulated tissue [Formula: see text] levels by manipulating the depth of anesthesia. This method provides [Formula: see text] measurements localized within [Formula: see text] and it may provide oxygen consumption measurements in individual cortical layers or within confined cortical regions, such as in ischemic penumbra and the foci of functional activation.