Monitoring Desk
LONDON: Researchers at University College London (UCL) have unveiled a groundbreaking electrocardiographic imaging (ECGI) vest that holds promise for standard medical care.
This reusable and time-efficient device, requiring just five minutes per patient, is designed to map the intricate electric impulses of the heart, potentially enabling the early detection of abnormalities linked to the life-threatening condition hypertrophic cardiomyopathy.
Hypertrophic cardiomyopathy is a cardiac ailment characterized by the thickening and stiffening of the heart’s muscle wall, impairing its ability to efficiently pump blood throughout the body.
Despite affecting approximately one in 300 adults, some individuals with genetic predispositions to the disease may not exhibit any symptoms.
The UCL-led study suggests that this innovative vest has the capability to identify signs of hypertrophic cardiomyopathy at an earlier stage than current diagnostic methods, offering a crucial window for intervention.
Given that hypertrophic cardiomyopathy can lead to heart failure and is frequently implicated in sudden, unexpected deaths among young people, the development of this technology marks a significant stride towards proactive and timely healthcare.
The vest’s reusability and quick assessment time further enhance its potential for widespread adoption in routine medical practice.
“By finding subtle electrical abnormalities using our new technique, we are able to detect hypertrophic cardiomyopathy earlier,” said lead author Dr George Joy (UCL Institute of Cardiovascular Science and Barts Heart Centre).
“This is important as it means we can potentially act earlier, providing new treatment to slow the disease as well as fast-tracking individuals to clinical trials that have the potential to stop the disease entirely.”
The reusable ECGI vest, with its potential to become a standard screening tool, underwent testing on a cohort of 174 patients, including those with genetic testing, recruited from three London hospitals, as well as 37 healthy volunteers.
The participants encompassed individuals already diagnosed with hypertrophic cardiomyopathy and tose with disease-causing genetic mutations who did not display evident symptoms.
Results revealed that the ECGI vest successfully identified electrical abnormalities in 25% of individuals with a genetic mutation, even when conventional cardiac imaging and ECG tests failed to detect any signs of the disease.
The vest uncovered an irregular pattern of electrical signal recovery and slowed conduction of electrical signals through the heart in these cases.
In a noteworthy development, the researchers also employed machine learning to create a model assessing disease severity and the risk of sudden cardiac death based on 12 markers from the ECGI vest.
Remarkably, this grading system aligned with risk estimates derived from standard protocols, incorporating factors like age and specific structural features of the heart.
This breakthrough suggests the potential for the ECGI vest to provide valuable insights and complement existing diagnostic methodologies.
