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

Condition(s) studied

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.

Eligibility

Primary outcome measure(s)

• Image-processing methods — From image acquisition to study end at 10 years
  Develop AI-based image processing methods using medical images and associated clinical data from ADPKD studies ad repositories

Trial sites (1)

More Mario Negri Institute for Pharmacological Research trials in Italy

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