- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT06206369
Developing Trustworthy Artificial Intelligence (AI)-Driven Tools to Predict Vascular Disease Risk and Progression (VASCULAIDRETRO)
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).
Study Overview
Status
Conditions
Intervention / Treatment
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.
Study Type
Enrollment (Estimated)
Contacts and Locations
Study Contact
- Name: Kak Khee Yeung, MD, PhD
- Phone Number: +31 6 14278725
- Email: k.yeung@amsterdamumc.nl
Study Contact Backup
- Name: Lotte Rijken, Msc.
- Email: l.rijken@amsterdamumc.nl
Study Locations
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Helsinki, Finland
- Recruiting
- Hospital District of Helsinki and Uusimaa (HUS)
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Contact:
- Riikka Tulamo
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Hamburg, Germany
- Recruiting
- Asklepios kliniken hamburg
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Contact:
- Christian Behrendt
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Amsterdam, Netherlands
- Recruiting
- Amsterdam UMC
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Contact:
- Kak Khee Yeung
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Porto, Portugal
- Recruiting
- University Hospital Center of São João
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Contact:
- Marina Dias-Neto
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Belgrade, Serbia
- Recruiting
- University Clinical Centre of Serbia
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Contact:
- Igor Koncar
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Oxford, United Kingdom
- Recruiting
- Oxford University Hospitals
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Contact:
- Regent Lee
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Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Males and females between 40 and 90 years of age with an abdominal aortic aneurysm and/or peripheral arterial disease.
Description
Inclusion Criteria AAA:
- Males and females
- 40-90 years old,
- Infrarenal, juxtarenal, suprarenal, iliac aneurysms (defined as 1.5x its normal diameter), and mycotic aneurysms.
- Starting AAA diameter >3cm,
- Patients that both have had or did not have interventions or ruptures.
Exclusion Criteria AAA:
- Patients with solely an ascending, thoracic, thoracoabdominal (type 1-3) aneurysm.
Inclusion Criteria PAD:
- Males and females,
- 40-90 years old,
- All PAD patients; all Fontaine stages 1,2,3, and 4.
Exclusion Criteria PAD: None
Study Plan
How is the study designed?
Design Details
- Observational Models: COHORT
- Time Perspectives: RETROSPECTIVE
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
|---|---|
|
Abdominal Aortic Aneurysm patients
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No intervention, retrospective study |
|
Peripheral Arterial Disease patients
|
No intervention, retrospective study |
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Development of disease progression prediction algorithms
Time Frame: 3 years
|
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 Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Internal validation of disease progression prediction algorithms
Time Frame: 3 years
|
The secondary objective will be the internal validation of the developed algorithms using data from retrospective cohorts. |
3 years
|
Collaborators and Investigators
Sponsor
Collaborators
Publications and helpful links
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Estimated)
Study Completion (Estimated)
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
Additional Relevant MeSH Terms
- Vascular Diseases
- Cardiovascular Diseases
- Atherosclerosis
- Arteriosclerosis
- Arterial Occlusive Diseases
- Peripheral Vascular Diseases
- Aortic Diseases
- Aneurysm
- Aortic Aneurysm
- Peripheral Arterial Disease
- Aortic Aneurysm, Abdominal
- Health Care Quality, Access, and Evaluation
- Investigative Techniques
- Epidemiologic Methods
- Health Care Evaluation Mechanisms
- Quality of Health Care
- Public Health
- Environment and Public Health
- Epidemiologic Studies
- Epidemiologic Study Characteristics
- Cohort Studies
- Case-Control Studies
- Retrospective Studies
Other Study ID Numbers
- 2011279
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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