Developing Trustworthy Artificial Intelligence (AI)-Driven Tools to Predict Vascular Disease Risk and Progression
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: No intervention, retrospective study.
- Who it may be relevant to
- Registry conditions: Aneurysm Abdominal, Peripheral Arterial Disease. Basic parameters: 40 years — 90 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Finland, Germany, Netherlands, Portugal, Serbia +1
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Unsure about the terms? Read our patient guide →
Overview
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).
Detailed description
To date, it is unknown which abdominal aortic aneurysm (AAA) and peripheral arterial disease (PAD) patients will suffer cardiovascular events or in which patients the AAA or PAD will progress. In the VASCULAID project, the VASCULAID-RETRO study aims to leverage data from existing cohorts and retrospectively collected data to develop artificial intelligence (AI) algorithms able to evaluate the risk of cardiovascular events and extent of disease progression.
In order to build and train the algorithms for the predictions, we plan to retrospectively enroll at least 5000 AAA and 6000 PAD patients AI-tools will be applied to the patient data. Automatic anatomical segmentation on images and image analysis on US, CTA and MRI will be performed. Also, algorithms to predict cardiovascular events and AAA or PAD progression based on multi-source data analysis will be developed.
Patient data from European clinical consortium partners is available. This consortium has access to big cohorts with relevant data for the envisioned study that will be used to enrich the existing registries. These data will be used to refine the algorithms developed for the prediction of cardiovascular events and AAA/PAD progression.
Interventions
- Other No intervention, retrospective study
No intervention, retrospective study
Primary outcome measures
- Development of disease progression prediction algorithms [Time frame: 3 years]
Secondary outcome measures (1)
- Internal validation of disease progression prediction algorithms [Time frame: 3 years]
Eligibility criteria
Inclusion criteria
- 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).
Exclusion criteria
- Patients with an ascending, thoracic, thoracoabdominal (type 1-3) aneurysm.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Observational model
- Cohort
Study locations
Finland · 1 center
- Hospital District of Helsinki and Uusimaa (HUS) — Helsinki
Germany · 1 center
- Asklepios kliniken hamburg — Hamburg
Netherlands · 1 center
- Amsterdam UMC — Amsterdam
Portugal · 1 center
- University Hospital Center of São João — Porto
Serbia · 1 center
- University Clinical Centre of Serbia — Belgrade
United Kingdom · 1 center
- Oxford University Hospitals — Oxford
Publications
- 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 Trustw PMID 39921236
Identifiers
NCT: NCT06206369 · 2011279