Quantitative cytoarchitectural phenotyping of deparaffinized human brain tissues
Advanced 3D imaging techniques and image segmentation and classification methods can transform biomedical research by offering insights into the human brain cytoarchitecture under pathological conditions. We propose a comprehensive pipeline for 3D imaging and automated quantitative cellular phenotyping on Formalin-Fixed Paraffin-Embedded human brain specimens. We exploit the versatility of our method by applying it to different human specimens from both adult and pediatric, normal and abnormal brain regions. Quantitative data on neuronal morphology, local density, and spatial clustering level are obtained from a machine-learning-based analysis of the 3D cytoarchitectural organization of cells identified by different molecular markers in two subjects with malformations of cortical development. This approach grants access to a wide range of clinical specimens, allowing for volumetric imaging and quantitative analysis of human brain samples at cellular resolution. Possible genotype-phenotype correlations can be unveiled, providing insights into the pathogenesis of various brain diseases and enlarging treatment opportunities.
Authors
- Valerio Conti (ORCID: https://orcid.org/0000-0002-8326-6378)
- Giacomo Mazzamuto (ORCID: https://orcid.org/0000-0003-3077-3904)
- Renzo Guerrini (ORCID: https://orcid.org/0000-0002-7272-7079)
- Rita Garbelli (ORCID: https://orcid.org/0000-0002-6475-4974)
- Andrea Porzionato
- Danila Di Meo (ORCID: https://orcid.org/0000-0001-6545-0676)
- Michele Sorelli (ORCID: https://orcid.org/0000-0002-0546-3157)
- Irene Costantini (ORCID: https://orcid.org/0000-0002-8464-7324)
- Cristiana Pelorosso (ORCID: https://orcid.org/0000-0003-3610-5819)
- Francesco S. Pavone (ORCID: https://orcid.org/0000-0002-0675-3981)
- Josephine Ramazzotti (ORCID: https://orcid.org/0009-0007-0341-9607)
- Aron Emmi (ORCID: https://orcid.org/0000-0002-2796-5676)
- Franco Cheli
- Raffaele De
- Beatrice Lorenzon
- Dalila Biancheri
- Samuel Bradley
- L. Perego
Institutions
- University of Padua (IT)
- Meyer Children's Hospital (IT)
- National Research Council (IT)
- Fondazione IRCCS Istituto Neurologico Carlo Besta (IT)
- University of Florence (IT)
Publication Details
- Journal
- Communications Biology
- Published
- 2025-11-05
- DOI
- https://doi.org/10.1038/s42003-025-08887-y
- Citations
- 1
- Primary Topic
- Cell Image Analysis Techniques
- Type
- article
- Field-Weighted Citation Impact
- 1.63
Funders
- Laserlab-Europe
- European Commission
- Ministero della Salute
- Università degli Studi di Firenze
- Regione Toscana
- Fondazione Cassa di Risparmio di Firenze
- National Institutes of Health
- HORIZON EUROPE Framework Programme