An AI Platform Integrating Imaging Data and Models, Supporting Precision Care Through Prostate Cancer's Continuum
In Europe, prostate cancer (PCa) is the second most frequent type of cancer in men and the fifth most lethal. Current clinical practices, often leading to overdiagnosis and overtreatment of indolent tumors, suffer from lack of precision calling for advanced AI models to go beyond SoA by deciphering non-intuitive, high-level medical image patterns and increase performance in discriminating indolent from aggressive disease, early predicting recurrence and detecting metastases or predicting effectiveness of therapies. To date efforts are fragmented, based on single-institution, size-limited and vendorspecific datasets while available PCa public datasets (e.g. US TCIA) are only few hundred cases making model generalizability impossible.
The ProCAncer-I project brings together 20 partners, including PCa centers of reference, world leaders in AI and innovative SMEs, with recognized expertise in their respective domains, with the objective to design, develop and sustain a cloud based, secure European Image Infrastructure with tools and services for data handling. The platform hosts the largest collection of PCa multi-parametric (mp)MRI, anonymized image data worldwide (>14,000 cases), based on data donorship, in line with EU legislation (GDPR). Robust AI models are developed, based on novel ensemble learning methodologies, leading to vendor-specific and -neutral AI models for addressing 8 PCa clinical scenarios.
To accelerate clinical translation of PCa AI models, we focus on improving the trust of the solutions with respect to fairness, safety, explainability and reproducibility. Metrics to monitor model performance and a causal explainability functionality are developed to further increase clinical trust and inform on possible failures and errors. A roadmap for AI models certification is defined, interacting with regulatory authorities, thus contributing to a European regulatory roadmap for validating the effectiveness of AI-based models for clinical decision making.
Study Overview
Status
Conditions
Intervention / Treatment
Study Type
Enrollment (Actual)
Contacts and Locations
Study Locations
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Italy
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Candiolo, Italy, Italy, 10060
- Fondazione del Piemonte per l'Oncologia
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Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- histological confirmed PCa or suspicion of PCa (abnormal PSA values and/or positive DRE);
- magnetic resonance imaging examination, including at least a high-resolution axial T2-weighted imaging and axila diffusion-weighted imaging (dynamic contrast-enhanced imaging is recommended, but not mandatory);
- age ≥ 18 years at the time of diagnosis
- signed written informed consent form (only for prospective enrollement).
Study Plan
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
|---|---|
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Retrospective (training model)
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Patients who underwent MRI with confirmed pathology data (either biopsy or prostatectomy)
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Prospective (validation model)
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Patients who underwent MRI with confirmed pathology data (either biopsy or prostatectomy)
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What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Time Frame |
|---|---|
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To create a repository (Prostate-NET) of retrospective MRI examinations with related clinical and pathology data dedicated to prostate cancer.
Time Frame: 24 months
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24 months
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To use the retrospective data collection (Prostate-NET) to solve 9 different clinical scenarios to improve diagnosis, characterization, treatment and follow-up of men with prostate cancer.
Time Frame: 36 months
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36 months
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To develop vendor-specific and vendor neutral AI models exploiting the prospective data that will be uploaded to the Prostate-NET platform.
Time Frame: 48 months
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48 months
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Collaborators and Investigators
Collaborators
Investigators
- Study Director: Manolis Tsiknakis, FORTH
- Study Chair: Nickolas Papanikolau, Fundacao Champalimaud
- Study Chair: Kostantinos Marias, FORTH
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Actual)
Study Completion (Actual)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
- Urogenital Diseases
- Genital Diseases
- Genital Neoplasms, Male
- Urogenital Neoplasms
- Neoplasms by Site
- Neoplasms
- Genital Diseases, Male
- Prostatic Diseases
- Male Urogenital Diseases
- Prostatic Neoplasms
- Prostate Cancer, Hereditary, 7
- Diagnostic Techniques and Procedures
- Diagnosis
- Tomography
- Diagnostic Imaging
- Magnetic Resonance Imaging
Other Study ID Numbers
- ProCAncer-I
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
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