Health & medicine Science & tech

HeartFlow Analysis: a better way to diagnose disease?

A technology called HeartFlow Analysis has been rolled out by the NHS to aid the diagnosis of coronary heart disease. Using data captured by a CT scan, it generates a 3D model of a patient’s heart, and applies deep learning techniques to predict the impact of any blockages. Abi Millar spoke to HeartFlow’s founder to find out its benefits. 

For patients with symptoms of heart disease, getting an accurate diagnosis can be challenging. Not only is the process quite protracted – hospitals can take several weeks to make their diagnosis – it can also be clouded with uncertainty. In some cases, patients’ heart disease is missed, while in other cases they undergo invasive tests that ultimately prove unnecessary.

According to data from the American College of Cardiology, around 60% of coronary angiograms (an invasive procedure) found no obstructive coronary heart disease. This suggests the test is being overused – a real problem considering the cost to health services and the risk of complications for patients.

In recent years, there has been much discussion around reducing unnecessary angiography, as well as ensuring all patients receive an accurate diagnosis. Since coronary heart disease is the leading cause of death worldwide, killing approximately 17.3 million people a year, it’s crucial that the signs are identified and that patients are given an appropriate course of treatment.

It’s for this reason that a technology called HeartFlow Analysis is being rolled out across the NHS. Developed by Silicon Valley med-tech company HeartFlow, the technology was recommended by NICE in 2017 and is now being used in more than 40 hospitals across NHS England.

Read the rest of this article in the October 2019 edition of Medical Technology

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