Ignite Creation Date:
2024-05-06 @ 7:59 PM
Last Modification Date:
2024-10-26 @ 3:18 PM
Study NCT ID:
NCT06206369
Status:
RECRUITING
Last Update Posted:
2024-01-16
First Post:
2024-01-04
Brief Title:
Developing Trustworthy Artificial Intelligence AI-Driven Tools to Predict Vascular Disease Risk and Progression
Sponsor:
Amsterdam UMC location VUmc
Organization:
Amsterdam UMC location VUmc
Study Overview
Official Title:
Developing Trustworthy Artificial Intelligence AI-Driven Tools to Predict Vascular Disease Risk and Progression
Status:
RECRUITING
Status Verified Date:
2024-01
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
VASCULAIDRETRO
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
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 AAAPAD 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 AAAPAD progression
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None