Numerous small vessels making up the central nervous system blood and lymphatic vascular networks are heterogeneous and region-specific dynamic structures, whose segments, position, shape and function can change in response to physiological and pathophysiological conditions. To date it has not been possible to integrate blood and lymphatic vascular elements and their microenvironment to achieve a holistic quantitative characterization of the combined brain and meningeal tissue-scale vascular networks, its structure and function in normal and disease states. This application proposes to develop microscopy- based high-throughput image analysis techniques for automated extraction of blood and lymphatic vascular networks enabling quantitative morphodynamic characterization of cerebrovascular microenvironment changes in two intracranial compartments ? the brain and dura mater. The study will focus on new algorithms for precise region-specific microvessel registration, mosaicing, segmentation, fusion and colocalization for constructing large tissue scale spatially aligned dual blood/lymphatic vascular network structural maps in the animals of both sexes, as well as characterization of heterogeneities of microvascular networks, including blood and lymphatic vasculature, under estrogen and sleep deprivation (the conditions relevant to multiple cerebrovascular disorders) compared to physiological settings. In other words, advanced microscopy-based techniques will be used to image blood and lymphatic vessels at sub-micron resolution in dura mater and the brain, and then cutting-edge deep machine learning imaging analysis methods will be employed to segment and quantify these vessels, their geometry, vessel wall structure, functionality, and interrelationship. Detailed structural analysis of microvascular networks is essential for accurate evaluation of the distribution of physical forces, substrate delivery and tissue clearance of waste, as well as sex differences and consequences of intracranial networks remodeling under physiological and pathological conditions. This will create knowledge enabling a better understanding of the pathogenesis of vascular impairments under estrogen and sleep deprivation, identify common molecular mechanisms and the efficacy and effectiveness of different therapeutic treatments. Without the ability to construct total structural and functional blood/lymphatic vascular network maps from studies limited to individual tissue component parts, it is little wonder that translation from the molecular and cellular levels to the whole organ and system levels is deficient and hinders translational progress towards a comprehensive understanding of the pathophysiology associated with a range of neurological disorders.
Detailed analysis of structural relationships of both blood and lymphatic circulation in the brain system will have a direct impact on our general understanding of vascular function in brain/meningeal communication, and the cause and resolution of numerous diseases resulting from intracranial vascular disorders including impact of sex hormone (estrogen) deprivation, sleep deprivation, migraines, stroke, multiple sclerosis, dural arterio-venous fistulae, intradural hygroma and hematoma, spontaneous cerebral spinal fluid leaks, and intradural aneurysms that can lead to the development of neurological and cognitive impairment, including Alzheimer's. Quantitative description of blood and lymphatic vessel network structures using image analytics and machine learning algorithms distributed as software tools will have broad applications to quantification of other thin complex curvilinear anatomical structures (i.e. nerves, neuronal circuits, neurons, and neuroglia). The new software for blood and vessel network measurement will enable translation of fundamental pathophysiological knowledge gained from this proposal towards the development and assessment of the effectiveness of treatments and therapeutic interventions to enhance health, lengthen life, and reduce illness and disability associated with a range of neurological disorders.