Developing Trustworthy Artificial Intelligence (AI)-Driven Tools to Predict Vascular Disease Risk and Progression
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age40-90
SponsorAmsterdam UMC, location VUmc
About this trial
The VASCULAID-RETRO study, within the broader VASCULAID project, aims to create artificial intelligence (AI) algorithms that can predict cardiovascular events and the progression of abdominal aortic aneurysm (AAA) and peripheral arterial disease (PAD). The study plans to gather and analyze data from at least 5000 AAA and 6000 PAD patients, combining existing cohorts and retrospectively collected data. During this project, AI tools will be developed to perform automatic anatomical segmentation and analyses on multimodal imaging. AI prediction algorithms will be developed based on multisource data (imaging, medical history, -omics).
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Males and females, 40-90 years old, with an AAA >3cm. This includes patients with infrarenal, juxtarenal, suprarenal, iliac (defined as 1.5x its normal diameter) aneurysms, as well as mycotic aneurysms. Patients that have had interventions or ruptures will also be included
Males and females, 40-90 years old, all PAD patients (Fontaine stages 1,2,3, and 4).
Disqualifiers
Patients with an ascending, thoracic, thoracoabdominal (type 1-3) aneurysm.
Trial population
Males and females between 40 and 90 years of age with an abdominal aortic aneurysm and/or peripheral arterial disease.
Trial design
Design model
Cohort
Time perspective
Retrospective
Treatments tested in this trial
No intervention, retrospective study
Other interventionNo intervention, retrospective study
Treatment groups
11,000 Participants
are divided into 2 treatment groupsGroup A: Abdominal Aortic Aneurysm patients1 intervention
Group B: Peripheral Arterial Disease patients1 intervention
Trial outcomes
Primary outcomes
1
Development of disease progression prediction algorithms
The primary goal of this retrospective study is to develop and train algorithms to predict disease progression and risk of cardiovascular events in AAA and PAD patients by leveraging multi-parametric data from 5000 AAA (\>1000 in AUMC) and 6000 PAD (\>1000 in AUMC) patients from existing cohorts and biobanks.
Time frame
3 yearsSecondary outcomes
1
Internal validation of disease progression prediction algorithms
The secondary objective will be the internal validation of the developed algorithms using data from retrospective cohorts.
Time frame
3 yearsSponsors and contacts
Click on the lead sponsor to view all of their trials.
Amsterdam UMC, location VUmc
Lead sponsor
Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)
Collaborator
Technical University of Twente
Collaborator
Universidade do Porto
Collaborator
Centre Hospitalier Universitaire de Nice
Collaborator
Stichting Allai
Collaborator
University of Belgrade
Collaborator
Brightfish Be
Collaborator
Hospital District of Helsinki and Uusimaa
Collaborator
University of Bergen
Collaborator
Asklepios Kliniken Hamburg GmbH
Collaborator
University of Oxford
Collaborator
VINČA INSTITUTE OF NUCLEAR SCIENCES Belgrado
Collaborator
Source ClinicalTrials.gov