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Deviation of blood flow from an optimal range is known to be associated withthe initiation and progression of vascular pathologies. Important openquestions remain about how the abnormal flow drives specific wall changes inpathologies such as cerebral aneurysms where the flow is highly heterogeneousand complex. This knowledge gap precludes the clinical use of readily availableflow data to predict outcomes and improve treatment of these diseases. As bothflow and the pathological wall changes are spatially heterogeneous, a crucialrequirement for progress in this area is a methodology for co-mapping localdata from vascular wall biology with local hemodynamic data. In this study, wedeveloped an imaging pipeline to address this pressing need. A protocol thatemploys scanning multiphoton microscopy was designed to obtain 3D data sets forsmooth muscle actin, collagen and elastin in intact vascular specimens. Acluster analysis was developed to objectively categorize the smooth musclecells (SMC) across the vascular specimen based on SMC density. In the finalstep in this pipeline, the location specific categorization of SMC, along withwall thickness was co-mapped with patient specific hemodynamic results,enabling direct quantitative comparison of local flow and wall biology in 3Dintact specimens.

Co-mapping Cellular Content and Extracellular Matrix with Hemodynamics  in Intact Arterial Tissues Using Scanning Immunofluorescent Multiphoton  Microscopy