Anatomical 3D Reconstruction of Murine Lymph Nodes for Visualization, Quantitation, and Numerical Simulation

Abstract

Lymph nodes (LNs) function as pharmacological sanctuary sites in HIV and metastatic cancer due to anatomical barriers that limit drug penetration. Accurate 3D reconstructions of lymph node architecture are essential for computational modeling of drug transport, yet existing methods lack compartment-specific resolution, accessibility, or throughput. Here, we present a scalable, high-fidelity pipeline for the 3D anatomical reconstruction of murine LNs, integrating optimized vibratome sectioning, multiplexed immunofluorescence staining, confocal microscopy, and custom automated segmentation algorithms. Our method precisely reconstructs key LN compartments, including lobules and high endothelial venules, with high spatial accuracy, achieving Sorensen-Dice indices >0.93 for lobules and contour-matching scores up to 77% for vasculature, as validated by quantitative comparison to manual segmentation. Compared to existing methodologies, this pipeline markedly reduces reagent usage ([~] 88%), labor time ([~] 97%), and technical complexity, offering a broadly accessible and efficient approach to high-fidelity 3D anatomical reconstruction of LN architecture. These digital twins can support computational simulations of drug distribution, immune cell trafficking, and spatial pharmacokinetics, providing critical insights into LN-resident disease mechanisms and informing therapeutic design.