Development of the new tool that analyzes the morphology of childhood tumors in 3D faster and more accurately.

DANEELpath (click here for demonstration) allows for automated characterization of three-dimensional models (3D) of neuroblastoma and to obtain information faster and in more reproducible way, which facilitates its use in research and pre-clinical evaluation of the possible treatments. In addition, its uses in pediatric tumors are studied.

The tool is integrated as an extension into the QuPath digital pathology software and combines artificial intelligence with mathematical morphology techniques to analyze histological images. Being open access, any researchers can consult its operation, modify the code and share it with other scientific groups.

The research was being led by Rosa Noguera, professor of the Histology at the UV and main researcher of one of the CIBERONC group (Centro de Investigación Biomédica en Red de Cáncer), of the Carlos III Institute of Health.In this projest, Nougera coordinated the Translational Research Group on Pediatric Solid Tumors group and the authors are Samuel Navarro, Pathology professor at the UV; Isaac Viecomartí, pre-doctoral researcher with the FPU scholarship; and Sofía Granados-Aparici y Amparo López-Carrasco, and postdoctoral researchers.

The tumor is a complex structure and its aggressiveness does not depend only on the malignant cells, but also on the microenvironment surrounding them. In this context, the extracellular matrix - the protein network that surrounds cells - and some of its components can become therapeutic targets.

In previous group work, vitronectin, a protein of the extracellular matrix, was studied and its role in cell adhesion and association with more aggressive tumor behaviors was highlighted, placing it as a possible therapeutic target. To study and control this process, the laboratory developed 3D biomimetic models that reproduce the environment of the tumor and allow to reproduce environments with or without vitronectin and test drugs aimed at blocking their cellular interactions.

Nethertheless, the analysis of only one image could require up to 3 days of work, what limits the quantity of possible data collection. With the DANEELpath quantitative data can be extracted from histological sections of 3D models quickly and accurately, and the process moves from requiring days to minutes.

This study was sponsored by the Carlos III Institue of Health in Madrid/FEDER (PI20/01107), the CIBERONC (CB16/12/00484), The Neuroblastoma Foundation (PRV/00166), and the Ministry of Innovative Science and Universities of Spain (beca FPU20/05344)

Reference of the article:Vieco-Martí, I., López-Carrasco, A., Navarro, S. et al. DANEELpath open source digital analysis tools for histopathological research in neuroblastoma models. Sci Rep 16, 6162 (2026). https://doi.org/10.1038/s41598-026-37134-