TY - JOUR
T1 - In-depth 3D exploration of autosomal dominant polycystic kidney disease through light sheet fluorescence microscopy
AU - Delgado-Rodriguez, Pablo
AU - Vitoria, Itsaso
AU - Ríos-Muñoz, Gonzalo R.
AU - Bardia, Lídia
AU - Lamanna-Rama, Nicolás
AU - Nicolas-Saenz, Laura
AU - Sporring, Jon
AU - Soto-Montenegro, María L.
AU - Aldabe, Rafael
AU - Colombelli, Julien
AU - Muñoz-Barrutia, Arrate
N1 - Publisher Copyright:
© The Author(s) 2025.
PY - 2025/12
Y1 - 2025/12
N2 - Autosomal Dominant Polycystic Kidney Disease (ADPKD) is the most prevalent genetic kidney disorder. Animal preclinical studies are one of the main tools to study this disease, often through either 2D histology imaging for high-resolution analysis or CT or MRI for full kidney segmentation. As an alternative to these modalities, we propose the use of Light Sheet Fluorescence Microscopy (LSFM) for high-resolution 3D imaging of healthy and ADPKD-induced mouse kidneys, enabling a detailed volumetric morphological analysis of the disease’s effects. In a mouse ADPKD model, ex vivo imaging of the kidneys was performed through LSFM, after which a combination of machine learning and other processing techniques allowed us to perform an in-depth image analysis. This includes the segmentation of key structures, such as the full kidney volume and, within it, its internal cavities, cortex, glomeruli, and cysts, complemented by texture analysis of tubular structures in the cortical area. Pathological kidneys exhibited significant volume enlargement and increased internal cavities due to cystogenesis. While glomerular count remained stable, their spatial distribution was altered, showing increased interglomerular distances and showcasing the deformations produced by the disease. The texture analysis of tubules from the cortex region identified Local Binary Pattern (LBP) uniformity and porosity as key biomarkers of tissue deformation, which could be used as markers to further evaluate the development of the disease. These findings underscore the potential of LSFM imaging as a powerful tool for detailed ADPKD characterization and treatment assessment.
AB - Autosomal Dominant Polycystic Kidney Disease (ADPKD) is the most prevalent genetic kidney disorder. Animal preclinical studies are one of the main tools to study this disease, often through either 2D histology imaging for high-resolution analysis or CT or MRI for full kidney segmentation. As an alternative to these modalities, we propose the use of Light Sheet Fluorescence Microscopy (LSFM) for high-resolution 3D imaging of healthy and ADPKD-induced mouse kidneys, enabling a detailed volumetric morphological analysis of the disease’s effects. In a mouse ADPKD model, ex vivo imaging of the kidneys was performed through LSFM, after which a combination of machine learning and other processing techniques allowed us to perform an in-depth image analysis. This includes the segmentation of key structures, such as the full kidney volume and, within it, its internal cavities, cortex, glomeruli, and cysts, complemented by texture analysis of tubular structures in the cortical area. Pathological kidneys exhibited significant volume enlargement and increased internal cavities due to cystogenesis. While glomerular count remained stable, their spatial distribution was altered, showing increased interglomerular distances and showcasing the deformations produced by the disease. The texture analysis of tubules from the cortex region identified Local Binary Pattern (LBP) uniformity and porosity as key biomarkers of tissue deformation, which could be used as markers to further evaluate the development of the disease. These findings underscore the potential of LSFM imaging as a powerful tool for detailed ADPKD characterization and treatment assessment.
KW - ADPKD
KW - LSFM
KW - Segmentation
KW - Texture analysis
UR - https://www.scopus.com/pages/publications/105022231933
U2 - 10.1038/s41598-025-24473-y
DO - 10.1038/s41598-025-24473-y
M3 - Article
C2 - 41258212
AN - SCOPUS:105022231933
SN - 2045-2322
VL - 15
JO - Scientific Reports
JF - Scientific Reports
IS - 1
M1 - 40843
ER -