A lightweight, 3D-printable, low-cost, "one-click" dorsal skin window for high-quality long-term multimodal subcutaneous tumor imaging

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Authors: Carlos Ortíz-de-Solórzano, Iván Cortés‐Domínguez, Xabier Morales
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Abstract

This is the repository of the data associated to the following publication: "A lightweight, 3D-printable, low-cost, “one-click” dorsal skin window for high-quality long-term multimodal subcutaneous tumor imaging" This is the abstract of the paper: Intravital microscopy (IVM) using dorsal skinfold chambers (DSCs) enables real-time, high-resolution imaging of the tumor microenvironment. However, traditional DSCs often cause animal distress, limit longitudinal studies, and require complex surgical implantation. To address these challenges and adhere to the 3Rs principles of animal welfare, this study presents a novel, 3D-printed, lightweight (0.69 g), and suture-free "one-click" DSC fabricated from biocompatible resin. This affordable platform simplifies surgical installation and minimizes postoperative inflammation, allowing for continuous multimodal imaging—including IVM, micro-CT, ultrasound, and optical fluorescence—for up to four weeks. The system was validated in murine models implanted with PDAC93-GFP pancreatic tumor organoids. Longitudinal high-resolution imaging successfully tracked biphasic tumor expansion, active stromal remodeling characterized by progressive collagen fiber compaction and alignment, and the emergence of a highly tortuous peritumoral vascular network. Furthermore, in vivo tracking in Catchup mice revealed a distinct transition of tumor-associated neutrophils from random acute inflammatory migration to directed tumor-driven chemotaxis. Overall, this ergonomic and robust DSC design provides a highly reliable platform for sustained, high-quality assessment of tumor-stroma-immune interactions while notably improving animal welfare.

Fields of Study & Subjects

3D Printing in Biomedical Research Optical Imaging and Spectroscopy Techniques Photoacoustic and Ultrasonic Imaging

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
3 March 2026
Language
EN
Document type
Dataset