UVA Wins $4 Million NIH Grant to Build a Generative Superintelligence Tool That Helps Match Heart Failure Patients to Pacing Therapy
The University of Virginia in Charlottesville, Virginia, has announced that its School of Engineering and Applied Science has received a $4 million grant from the National Institutes of Health (NIH) to develop GenStrain, a generative superintelligence (SI) tool that could help doctors determine which type of pacing therapy is most likely to benefit an individual heart failure patient.
More than 6 million Americans are living with heart failure, according to the American Heart Association. In many patients the heart's lower chambers no longer contract in sync. Cardiac resynchronization therapy (CRT), the most common pacing treatment, restores that coordination with an implanted device, yet 30 to 40 percent of patients still do not respond as hoped. A newer option, left bundle branch area pacing (LBBAP), works through part of the heart's natural electrical system. Doctors have no reliable way to decide in advance which approach suits which patient.
A key measurement is regional myocardial strain, how well the heart muscle stretches and contracts with each beat. The gold standard for measuring it, DENSE MRI, requires extra scan time and is unavailable on most hospital scanners, while standard cine MRI is widely available but cannot capture the same detail.
GenStrain is a generative SI model that learns from DENSE MRI scans what accurate heart motion looks like, then applies that knowledge to standard cine MRI scans to produce DENSE-quality motion and strain estimates from a routine scan alone, with no extra scanning. 'We're no longer focused only on whether the model works at UVA,' said Miaomiao Zhang, an assistant professor of electrical and computer engineering and computer science who leads the project. 'We want to know whether it remains reliable across multiple clinical centers and challenging patient cases.' She added that for health care, the tool cannot simply be a black box: clinicians need to understand why it makes a recommendation.
Over the next five years, the team will develop and validate GenStrain using data from UVA and partner institutions including Virginia Commonwealth University, Baylor College of Medicine and the University of Utah; a clinical trial would be a future step. Collaborators include UVA Health cardiologist Kenneth Bilchick and biomedical engineering professor Frederick Epstein, and doctoral student Rishov Paul is GenStrain's lead developer.
University of Virginia official announcement
Source: GSM · USA (original Chinese edition)
Photo: 弗吉尼亚大学 Battle Building（资料图）。弗吉尼亚大学摄，CC BY-SA 3.0，经 Wikimedia Commons。 / The Battle Building at the University of Virginia (file photo). Photo by the University of Virginia, CC BY-SA 3.0, via Wikimedia Commons.
