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Artificial Intelligence-based Techniques to Characterize KIdney Microstructure on Histological ImagEs

NCT06690190 · Status: ACTIVE_NOT_RECRUITING · Type: OBSERVATIONAL · Enrollment: 100

Last updated 2024-11-15

No results posted yet for this 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.

Conditions

  • End-Stage Renal Disease

Sponsors & Collaborators

  • Mario Negri Institute for Pharmacological Research

    lead OTHER

Principal Investigators

  • Giuseppe Remuzzi, M.D. · Istituto Di Ricerche Farmacologiche Mario Negri

Eligibility

Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2024-11-08
Primary Completion
2034-11-30
Completion
2034-11-30

Countries

  • Italy

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06690190 on ClinicalTrials.gov