Developing Trustworthy Artificial Intelligence (AI)-Driven Tools to Predict Vascular Disease Risk and Progression

NCT06206369 | Recruiting

• 1 other identifier: 2011279
• Study Type: observational
• Target: 11,000
• Locations: 6 countries
• Sites: 6

Brief Summary

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).

Conditions

Aneurysm Abdominal; Peripheral Arterial Disease

Keywords

Artificial Intelligence, Prediction models, Image analysis, Abdominal Aortic Aneurysms, Peripheral Arterial Disease

Outcome Measures

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.

  3 years

Secondary Outcomes (1)

• Internal validation of disease progression prediction algorithms

  3 years

Study Arms (2)

Abdominal Aortic Aneurysm patients

Other: No intervention, retrospective study

Peripheral Arterial Disease patients

Other: No intervention, retrospective study

Interventions

No intervention, retrospective study OTHER

No intervention, retrospective study

Abdominal Aortic Aneurysm patients; Peripheral Arterial Disease patients

Eligibility Criteria

• Age: 40 Years - 90 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Males and females between 40 and 90 years of age with an abdominal aortic aneurysm and/or peripheral arterial disease.

You may qualify if:

• 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).

You may not qualify if:

• Patients with an ascending, thoracic, thoracoabdominal (type 1-3) aneurysm.

Sponsors & Collaborators

• Amsterdam UMC, location VUmc: lead
• 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

Study Sites (6)

Hospital District of Helsinki and Uusimaa (HUS)

Helsinki, Finland

RECRUITING

Asklepios kliniken hamburg

Hamburg, Germany

RECRUITING

Amsterdam UMC

Amsterdam, Netherlands

RECRUITING

University Hospital Center of São João

Porto, Portugal

RECRUITING

University Clinical Centre of Serbia

Belgrade, Serbia

RECRUITING

Oxford University Hospitals

Oxford, United Kingdom

RECRUITING

Related Publications (1)

• Rijken L, Zwetsloot S, Smorenburg S, Wolterink J, Isgum I, Marquering H, van Duivenvoorde J, Ploem C, Jessen R, Catarinella F, Lee R, Bera K, Buisan J, Zhang P, Dias-Neto M, Raffort J, Lareyre F, Muller C, Koncar I, Tomic I, Zivkovic M, Djuric T, Stankovic A, Venermo M, Tulamo R, Behrendt CA, Smit N, Schijven M, van den Born BJ, Delewi R, Jongkind V, Ayyalasomayajula V, Yeung KK. Developing Trustworthy Artificial Intelligence Models to Predict Vascular Disease Progression: the VASCUL-AID-RETRO Study Protocol. J Endovasc Ther. 2025 Feb 7:15266028251313963. doi: 10.1177/15266028251313963. Online ahead of print.

  PMID: 39921236 DERIVED

Biospecimen

Retention: SAMPLES WITH DNA

Blood and tissue samples (from existing biobanks)

MeSH Terms

Conditions

Aortic Aneurysm, Abdominal; Peripheral Arterial Disease

Interventions

Retrospective Studies

Condition Hierarchy (Ancestors)

Aortic Aneurysm; Aneurysm; Vascular Diseases; Cardiovascular Diseases; Aortic Diseases; Atherosclerosis; Arteriosclerosis; Arterial Occlusive Diseases; Peripheral Vascular Diseases

Intervention Hierarchy (Ancestors)

Case-Control Studies; Epidemiologic Studies; Epidemiologic Study Characteristics; Epidemiologic Methods; Investigative Techniques; Cohort Studies; Health Care Evaluation Mechanisms; Quality of Health Care; Health Care Quality, Access, and Evaluation; Public Health; Environment and Public Health

Central Study Contacts

Kak Khee Yeung, MD, PhD

CONTACT

+31 6 14278725; k.yeung@amsterdamumc.nl

Lotte Rijken, Msc.

CONTACT

l.rijken@amsterdamumc.nl

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: M.D., Ph.D., FEBVS

Study Record Dates

• First Submitted: January 4, 2024
• First Posted: January 16, 2024
• Study Start: October 31, 2023
• Primary Completion (Estimated): May 1, 2029
• Study Completion (Estimated): May 1, 2029
• Last Updated: January 16, 2024

Record last verified: 2024-01

Locations

NL (1); SE (1); GB (1); FI (1); PT (1); DE (1)