Oxford Heartbeat (OxHB) is an early-stage start-up developing innovative technology to make cardiovascular surgeries more efficient and effective.
We are building software that helps surgeons plan and rehearse minimally invasive stent placements inside blood vessels — currently the most popular treatment for common cardiovascular disorders.
The software allows surgeons to simulate how different stents will fit and behave in a patient’s anatomy and select the best surgical scenario for every patient.
The software will be installed in hospitals and used in surgery preparation, reducing the number of complications and the associated cost to hospitals and society.
Having developed the minimal viable product for placements of cerebral stents in the brain, the next stage is to validate the accuracy of our simulated results.
Since we are operating within the domain of surgery, it is paramount that the technology delivers highly accurate results to reliably support clinical decision-making.
Therefore, we need to compare the results of our simulations with real clinical outcomes.
To enable comparison to our simulations, we need to measure the configurations of real stent devices that have been deployed inside patients using clinically available historic 2D scans — solving this complex measurement problem is the focus of this project.
In the proposed project we aim to develop and evaluate a novel methodology for obtaining accurate measurements of the size and position of the complex 3D shape of stents inside brain blood vessels from the 2-plane projection view of the patient’s brain captured by X-ray angiography.
The expertise in accurate measurements and uncertainty quantifications will be provided by the National Physical Laboratory (NPL).
The main activities include developing the new method for measuring the reference configuration of the stent from 2D patient scans by aligning them with preoperative anatomy (constructed in our software) using the metadata stored in the scans.
We will test out potential steps to achieve accurate alignment and measurements in a synthetic model, then transfer it to real anonymised clinical images and, finally, perform uncertainty analysis for the main variables.
The proposed project builds upon the successfully completed IUK SMART Proof of Market(PoM, 2016), Biomedical Catalyst Feasibility (BMC-F, 2017), as well as funding from NIHR i4i Connect and SBRI Healthcare (2018).
The results of our previous projects have received numerous awards, including the NHS Innovation Award 2017(HEE).
Oxford Heartbeat was also named the UK Start-up of 2017 at Medilink UK and the WIRED “”Best Healthcare Start-up of 2018.”