Tel Aviv-based MedHub’s artificial intelligence (AI) decision-support system for cardiologists, AutocathFFR, has entered the initial stages of a pivotal multi-centre clinical trial to demonstrate its efficacy.
AutocathFFR detects stenosis, or narrowing, of the coronary arteries surrounding the heart while providing cardiologists with relevant physiological parameters that aid them in assessing the severity of their patients’ condition. The system then helps them devise an optimal treatment strategy for each patient.
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The efficacy trial follows a successful feasibility study done in close collaboration with the Rambam Healthcare Campus in Haifa, Israel. The results of the feasibility study will be published at the Innovation in Cardiovascular Interventions conference in December 2019.
MedHub CEO Or Bruch-El said: “Nowadays, we fly in automated airplanes and rely on smart navigation systems in our private cars to make better decisions than we do. I don’t see why we shouldn’t make use of similar capabilities when it comes to our health and well-being.
“Healthcare systems everywhere are burning out and collapsing under immense loads, making quality of treatment directly dependent on patient access to private capital. AI has the potential to change that. Our reality calls for it.”
With current diagnostic methods, re-stenosis occurs after treatment in 15% of cases. Clinically redundant interventions such as unnecessary stent placement procedures have also reached 30%, costing the US healthcare system around $4bn a year, MedHub said.
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By GlobalDataGreater automation in diagnosis could help prevent the inaccurate diagnoses that drive many of these unnecessary procedures, the company added.
MedHub chief medical officer Dr Edward Koifman said: “As interventional cardiologists performing catheterizations on a daily basis, we face significant challenges in accurate diagnosis of cardiac disease that stem from difficulty in precisely assessing the severity of a patient’s condition and in making the appropriate connections between a patient’s complaints and the subsequent diagnosis.
“I believe that this kind of technology will assist cardiologists in the decision-making process when determining the best course of action.”
