Researchers took routine CMR scans from more than 1,000 patients and used a new...
Researchers took routine CMR scans from more than 1,000 patients and used a new automated artificial intelligence technique to analyse the images.
Source: University College London

AI helps predict heart attacks and stroke

Artificial intelligence has been used for the first time to instantly and accurately measure blood flow, in a study led by University College London (UCL) and Barts Health NHS Trust. The results were found to be able to predict chances of death, heart attack and stroke, and can be used by doctors to help recommend treatments which could improve a patient’s blood flow.

Heart disease is the leading global cause of death and illness. Reduced blood flow, which is often treatable, is a common symptom of many heart conditions. International guidelines therefore recommend a number of assessments to measure a patient’s blood flow, but many are invasive and carry a risk.

Non-invasive blood flow assessments are available, including Cardiovascular Magnetic Resonance (CMR) imaging, but up until now, the scan images have been incredibly difficult to analyse in a manner precise enough to deliver a prognosis or recommend treatment.

In the largest study of its kind, researchers took routine CMR scans from more than 1,000 patients attending St Bartholomew's Hospital and the Royal Free Hospital and used a new automated artificial intelligence technique to analyse the images. By doing this, the teams were able to precisely and instantaneously quantify the blood flow to the heart muscle and deliver the measurements to the medical teams treating the patients.

By comparing the AI-generated blood flow results with the health outcomes of each patient, the team found that the patients with reduced blood flow were more likely to have adverse health outcomes including death, heart attack, stroke and heart failure.

The AI technique was therefore shown for the first time to be able to predict which patients might die or suffer major adverse events, better than a doctor could on their own with traditional approaches.

Professor James Moon (UCL Institute of Cardiovascular Science and Barts Health NHS Trust) said: “Artificial intelligence is moving out of the computer labs and into the real world of healthcare, carrying out some tasks better than doctors could do alone. We have tried to measure blood flow manually before, but it is tedious and time-consuming, taking doctors away from where they are needed most, with their patients.”

Dr Kristopher Knott (UCL Institute of Cardiovascular Science and Barts Health NHS Trust) added: “The predictive power and reliability of the AI was impressive and easy to implement within a patient’s routine care. The calculations were happening as the patients were being scanned, and the results were immediately delivered to doctors. As poor blood flow is treatable, these better predictions ultimately lead to better patient care, as well as giving us new insights into how the heart works.”

Dr Peter Kellman from the National Institutes of Health (NIH) in the US, who working with Dr Hui Xue at the NIH, developed the automated AI techniques to analyse the images that were used in the study, said: “This study demonstrates the growing potential of artificial intelligence-assisted imaging technology to improve the detection of heart disease and may move clinicians closer to a precision medicine approach to optimize patient care. We hope that this imaging approach can save lives in the future.”

Subscribe to our newsletter

Related articles

AI measures fat around heart to predict diabetes

AI measures fat around heart to predict diabetes

Researchers have developed a new artificial intelligence tool that is able to automatically measure the amount of fat around the heart from MRI scan images.

Necklace detects abnormal heart rhythm

Necklace detects abnormal heart rhythm

A necklace which detects abnormal heart rhythm will be showcased for the first time on EHRA Essentials 4 You, a scientific platform of the European Society of Cardiology (ESC).

How AI is already helping physicians save lives

How AI is already helping physicians save lives

With RAPID AI, the physicians now can get find parts of the brain that are not currently getting enough blood flow within minutes.

In emergencies: AI can improve X-ray identification of pacemakers

In emergencies: AI can improve X-ray identification of pacemakers

Researchers have created new AI software that can identify cardiac rhythm devices in x-rays more accurately and quickly than current methods.

AI system learns to diagnose intracranial hemorrhage

AI system learns to diagnose intracranial hemorrhage

Researchers have developed a system using artificial intelligence to quickly diagnose and classify brain hemorrhages and to provide the basis of its decisions from relatively small image datasets.

Deep learning helps visualize X-ray data in 3D

Deep learning helps visualize X-ray data in 3D

Scientists have leveraged artificial intelligence to train computers to keep up with the massive amounts of X-ray data taken at the Advanced Photon Source.

Skin patch for early warning of strokes

Skin patch for early warning of strokes

Engineers developed a soft and stretchy ultrasound patch that can be worn on the skin to monitor blood flow through major arteries and veins deep inside a person’s body.

Artificial intelligence shortcuts introduce bias in cancer treatment

Artificial intelligence shortcuts introduce bias in cancer treatment

AI tools models are a powerful tool in cancer treatment. However, unless these algorithms are properly calibrated, they can sometimes make inaccurate or biased predictions.

Ultrasound sensor measures blood pressure

Ultrasound sensor measures blood pressure

Imec uses an ultrasound sensor to measure the central pulse wave velocity, to determine arterial stiffness, and monitoring blood pressure.

Popular articles

Subscribe to Newsletter