AI Image Guidance for Endovascular Surgery
Research type
Research Study
Full title
A randomised controlled trial to assess the clinical-, technical- and cost-effectiveness of a cloud-based, ARtificially Intelligent image fusion system in comparison to standard treatment to guide endovascular Aortic aneurysm repair (ARIA)
IRAS ID
280257
Contact name
Rachel Clough
Contact email
Sponsor organisation
King's College London
ISRCTN Number
ISRCTN13832085
Duration of Study in the UK
3 years, 0 months, 1 days
Research summary
The overarching purpose of this clinical trial is to evaluate the clinical, technical and cost-effectiveness of a novel type of medical device comprised of real-time cloud computing, Artificial Intelligence and computer vision (Cydar EV) compared to standard treatment in endovascular aortic aneurysm repair.
Background
X-ray fluoroscopy-guided surgery is a large and growing segment of the minimally-invasive surgery market, but is limited by 2D imaging that visualises soft tissues poorly. This poor visualisation contributes to imprecision and variable patient outcomes. Cydar EV uses computer vision to augment X-ray fluoroscopy imaging by fusing it with 3D soft tissue information from the patient’s diagnostic CT scan with high accuracy and robustness. Pilot data from commercial test sites have shown Cydar EV is associated with reduced operating times and lower radiation exposure.
We propose a multi-centre, two-armed, randomised clinical trial of 340 patients with abdominal and/or thoraco-abdominal aortic disease who will be randomly allocated to undergo endovascular repair using standard X-ray fluoroscopy imaging alone or augmented with Cydar-EV image fusion.
The primary outcome measure is procedure time, and secondary outcome measures include procedural efficiency, patient outcomes, technical success and cost effectiveness.Anticipated impact and dissemination
Cydar EV is a pioneering a new class of cloud digital products that promise to revolutionise the precision and consistency of patient outcomes. As a value-based subscription, they offer an alternative to high capital- expenditure procurement of imaging capabilities and clinical data insights. Establishing strong clinical evidence would accelerate adoption of Cydar EV for the benefit of patients, hospitals, and health services globally, as well as stimulating development of future products in this class.REC name
London - South East Research Ethics Committee
REC reference
22/LO/0081
Date of REC Opinion
10 Feb 2022
REC opinion
Further Information Favourable Opinion