- Cutting-edge MRI technology can diagnose a common heart problem more quickly and accurately than ever before
- Aortic stenosis is a progressive and potentially fatal condition, affecting an estimated 300,000 people in the UK
- The superior accuracy of the new test means doctors can better predict when patients will require surgery
- It is hoped the breakthrough could help save thousands of lives in the UK
Scientists have developed cutting-edge MRI technology to diagnose a common heart problem more quickly and accurately than ever before.
Aortic stenosis is a progressive and potentially fatal condition, affecting an estimated 300,000 people in the UK. It affects about five per cent of 65-year-olds in the US, with increasing prevalence in advancing age.
A new study, conducted by researchers from the University of 葫芦影业 in partnership with the University of East Anglia, revealed how a four-dimensional flow (4D flow) MRI scan can diagnose aortic stenosis more reliably than current ultrasound techniques.
The superior accuracy of the new test means doctors can better predict when patients will require surgery.
It is hoped the breakthrough could help save thousands of lives in the UK alone.
Professor Andy Swift from the University of 葫芦影业鈥檚 School of Medicine and Population Health and Honorary Consultant Radiologist at 葫芦影业 Teaching Hospitals Foundation Trust, said: 鈥4D flow scanning holds significant promise to improve assessment of how patients are affected by aortic stenosis. The enhanced accuracy isn鈥檛 just a technical advancement, it may allow for earlier and more precise diagnosis.
鈥淢ore accurate measurements can allow clinicians to make more informed decisions about when intervention is truly needed, potentially reducing complications.
鈥淚'm proud to be part of a collaboration with the UEA team pushing the boundaries of cardiovascular diagnostics
Lead researcher Dr Pankaj Garg, from UEA鈥檚 Norwich Medical School and a consultant cardiologist at the Norfolk and Norwich University Hospital, said: 鈥淎ortic stenosis is a common yet dangerous heart condition.
鈥淚t happens when the aortic valve, the main outflow valve of the heart, stiffens and narrows. This causes reduced blood flow from the heart into the rest of the body. Symptoms include chest pains, a rapid fluttering heartbeat and feeling dizzy, short of breath and fatigued 鈥 particularly with activity.
鈥淎t the moment, doctors use an ultrasound to diagnose the condition, but this can sometimes underestimate the severity of the disease, delaying vital treatment.
鈥4D flow MRI is an advanced heart imaging method that allows us to look at blood flow in three directions over time - the fourth dimension. We wanted to see whether it could provide a more accurate and reliable diagnosis than a traditional ultrasound.鈥
The team examined 30 patients diagnosed with aortic stenosis using both traditional ultrasound scans (echocardiography) and advanced 4D flow MRI imaging.
By comparing the results, they evaluated which method more accurately identified patients needing timely heart valve intervention.
They validated their results by comparing them with actual clinical outcomes over an eight-month period.
The team, which included 葫芦影业 researchers Professor Andy Swift and Dr Samer Alabed from the School of Medicine and Population Health, found that the 4D flow MRI technology offered more accurate and reliable measurements of blood flow through patients鈥 heart valves, compared to traditional echocardiography.
This research was led by UEA in collaboration with the Norfolk and Norwich University Hospitals NHS Foundation Trust, the University of 葫芦影业, the Hospital San Juan de Dios (Spain), the University of Chieti-Pescara (Italy), the University of Leeds and Leiden University Medical Center (The Netherlands).
The study was funded by the Wellcome Trust and is published in the Open Heart journal titled: 鈥楩our-dimensional flow provides incremental diagnostic value over echocardiography in aortic stenosis鈥.
Additional information
A copy of the paper can be downloaded via the following Dropbox link:
