Artificial Intelligence-based Techniques to Characterize KIdney Microstructure on Histological ImagEs
Condition(s) studied
Study summary
The primary aim of this observational exploratory study will be to use fully anonymized histological images of kidney human tissue from patients with any kidney disease and normal kidney tissue to develop novel deep learning-based image processing techniques allowing to characterize kidney microstructure across different pathologies and/or disease stages.
Secondly, the study will aim at validating the novel techniques against gold standard (manual) methods, when available, and at developing novel histological imaging biomarkers that could support differential diagnosis, staging of the disease, monitoring of disease progression and response to therapy, and prediction of the disease progression.
Other exploratory aims will include:
* The use of radiomics techniques to identify disease-specific kidney morphology patterns.
* The implementation of uncertainty quantification techniques, able to increase AI explainability.
Eligibility
Primary outcome measure(s)
- Image processing techniques — From image acquisition to study end at 10 years
Develop novel deep learning-based image processing techniques allowing to characterize kidney microstructure across different pathologies and/or disease stages.
Trial sites (1)
| Facility | City | Region | Status |
|---|---|---|---|
| Clinical Research Centre for Rare Diseases Aldo e Cele Daccò | Ranica | BG |
More Mario Negri Institute for Pharmacological Research trials in Italy
Other trials for the same condition
This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.
View NCT06690190 on ClinicalTrials.gov ↗ ← All trials in Italy