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Artificial Intelligence-based Image Processing Methods to Advance the Characterization of Polycystic Kidney Disease

NCT06688981 · Status: ACTIVE_NOT_RECRUITING · Type: OBSERVATIONAL · Enrollment: 100

Last updated 2024-11-14

No results posted yet for this study

Summary

The primary aim of this observational exploratory study is to develop AI-based image processing methods to advance the characterization of Polycystic Kidney Disease using medical images and associated clinical data, including:

1. AI-based fully automatic segmentation techniques for the accurate identification of kidneys, liver, and cysts, with a focus on AI interpretability and robustness;
2. advanced AI-based image processing techniques allowing to identify new imaging biomarkers, including through the use of radiomics, to characterize ADPKD tissue microstructure and therefore stage the disease and monitor and predict disease progression and response to therapy;
3. multiparametric models including image-based radiomic features alongside clinical and laboratory data to stratify ADPKD patients and predict ADPKD progression over time.

The study will also have the secondary aim of validating the novel techniques against gold standard (manual) methods, when available.

Conditions

  • Autosomal Dominant Polycystic Kidney Disease (ADPKD)

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
No

Timeline & Regulatory

Start
2024-10-12
Primary Completion
2034-10-31
Completion
2034-10-31

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 NCT06688981 on ClinicalTrials.gov