An Integrated Multiphoton Imaging Workflow for Quantitative Analysis of Aortic Tissue Microstructure

Abstract

Quantitative, reproducible characterization of aortic microstructure is essential for advancing vascular biomechanics and mechanobiology. To address this need, we present a comprehensive image-analysis workflow that extracts quantitative descriptors of tissue microstructure from multiphoton microscopy stacks of the murine thoracic aorta. Channel-specific signals are acquired for fibrillar collagen (second harmonic generation), elastin (two-photon autofluorescence), and cell nuclei (two-photon excited fluorescence). Following reorientation into the XZ plane, individual elastic lamellae are traced to quantify lamellar thickness and interlamellar spacing using circle-based geometry (Taubin fitting). After correction for vessel wall curvature via a cylindrical transformation, segmented nuclei are assigned to medial or adventitial compartments based on visual estimates of adventitial volume fraction, and nuclear morphology is characterized via ellipsoidal fitting in terms of nuclear aspect ratio and major-axis orientation. Collagen organization is resolved in XY sections by extracting fiber centerlines to quantify straightness and amplitude; traces from serial sections are then combined to reconstruct the three-dimensional collagen network and estimate porosity and linear fiber density, while fiber orientation distributions are derived from principal component analysis-based angles and fit using a von Mises mixture model. Finally, collagen and elastin volume fractions are computed via a two-stage fixed-threshold approach calibrated on a balanced training subset. Overall, this modular and robust workflow provides an integrated framework for studying aortic wall remodeling across physiological and pathological processes. Non-Technical SummaryAs the main blood vessel in our body, the aorta needs to be both strong and flexible. This balance comes from three main parts: elastic layers that allow the aorta to stretch, strong fibers that prevent tearing, and cells that sense and respond to changes in blood pressure and other signals. When any of these components are altered, the aorta may stiffen or weaken, which can interfere with normal blood flow. In this study, we developed a clear and consistent way to measure the structure of the aortic wall using microscope images. The approach examines how thick the elastic layers are and how far apart they lie, the size and orientation of cell centers, and how straight or wavy structural fibers appear. It also estimates how much of each component is present in the aortic wall. Because the same steps are applied each time, results can be fairly compared across different conditions. Overall, this tool transforms detailed images into simple measurements, helping scientists understand how the aorta changes in health and disease.