Medical Design Briefs - October 2021 - 26

Artificial Intelligence Tech Set to Transform Heart Imaging
AI enables examination of
hearts for scar tissue,
eliminating the need for
contrast injections.
UVA Health
Charlottesville, VA
A new artificial intelligence (AI) technology
for heart imaging can potentially
improve care for patients, allowing doctors
to examine their hearts for scar tissue
while eliminating the need for contrast
injections required for traditional
cardiovascular magnetic resonance
imaging (CMR).
A team of researchers who developed
the technology, including doctors at
UVA Health, reports the success of the
approach in an article in the scientific
journal Circulation. The team compared
its AI approach, known as virtual native
enhancement (VNE), with contrastenhanced
CMR scans now used to monitor
hypertrophic cardiomyopathy, the
most common genetic heart condition.
The researchers found that VNE produced
higher-quality images and better
captured evidence of scar in the heart, all
without the need for injecting the standard
contrast agent required for CMR.
" This is a potentially important ad -
vance, especially if it can be expanded to
other patient groups, " says researcher
Christopher Kramer, MD, the chief of the
Division of Cardiovascular Medicine at
UVA Health, Virginia's only designated
Center of Excellence by the Hypertrophic
Cardiomyopathy Association. " Being able
to identify scar in the heart, an important
contributor to progression to heart failure
and sudden cardiac death, without contrast,
would be highly significant. CMR
scans would be done without contrast, saving
cost and any risk, albeit low, from the
contrast agent. "
■ Hypertrophic Cardiomyopathy
Hypertrophic cardiomyopathy is the
most common inheritable heart disease,
and the most common cause of
sudden cardiac death in young athletes.
It causes the heart muscle to thicken
and stiffen, reducing its ability to pump
blood and requiring close monitoring
by doctors.
The new VNE technology will allow
doctors to image the heart more often
and more quickly, the researchers say. It
26
Intro
Cov
Christopher Kramer, MD, is developing a new AI approach to improve heart imaging. Kramer is the
chief of the Division of Cardiovascular Medicine at UVA Health. (Credit: UVA Health)
also may help doctors detect subtle
changes in the heart earlier, though
more testing is needed to confirm that.
The technology also would benefit
patients who are allergic to the contrast
agent injected for CMR, as well as
patients with severely failing kidneys, a
group that avoids the use of the agent.
The new approach works by using AI
to enhance " T1-maps " of the heart tissue
created by magnetic resonance
imaging (MRI). These maps are combined
with enhanced MRI " cines, "
which are like movies of moving tissue
- in this case, the beating heart.
Overlaying the two types of images creates
the artificial VNE image
Based on these inputs, the technology
can produce something virtually
identical to the traditional contrastenhanced
CMR heart scans doctors are
accustomed to reading - only better,
the researchers conclude. " Avoiding
the use of contrast and improving
image quality in CMR would only help
both patients and physicians down the
line, " Kramer says.
While the new research examined
VNE's potential in patients with hypertrophic
cardiomyopathy, the technology's
creators envision it being used for
many other heart conditions as well.
" While currently validated in the
HCM population, there is a clear pathway
to extend the technology to a
wider range of myocardial pathologies, "
they write. " VNE has enormous
potential to significantly improve cliniwww.medicaldesignbriefs.com
ToC
+
-
A
cal
practice, reduce scan time and
costs, and expand the reach of CMR in
the near future. "
The research team consisted of Qiang
Zhang, Matthew K. Burrage, Elena
Lukaschuk, Mayooran Shanmuganathan,
Iulia
A.
Popescu,
Chrysovalantou
Nikolaidou, Rebecca Mills, Konrad
Werys, Evan Hann, Ahmet Barutcu,
Suleyman D. Polat, HCMR investigators,
Michael Salerno, Michael JeroschHerold,
Raymond Y. Kwong, Hugh C.
Watkins, Christopher M. Kramer, Stefan
Neubauer, Vanessa M. Ferreira, and
Stefan K. Piechnik. Kramer has no financial
interests in the research, but some of
his collaborators are seeking a patent
related to the imaging approach. A full
list of disclosures is included in the paper.
The research was made possible by
work funded by the British Heart
Foundation, grant PG/15/71/31731; the
National Institutes of Health's National
Heart, Lung and Blood Institute, grant
U01HL117006-01A1; the John Fell
Oxford University Press Research Fund;
and the Oxford BHF Centre of Research
Excellence, grant RE/18/3/34214. The
research was also supported by British
Heart Foundation
Clinical
Research
Training Fellowship FS/19/65/34692,
National Institute for Health Research
(NIHR) Oxford Biomedical Research
Centre at The Oxford University
Hospitals NHS Foundation Trust, and the
National Institutes of Health.
For more information, visit https://
newsroom.uvahealth.com.
Medical Design Briefs, October 2021
µ
È

https://newsroom.uvahealth.com http://www.medicaldesignbriefs.com http://info.hotims.com/79418-966

Medical Design Briefs - October 2021

Table of Contents for the Digital Edition of Medical Design Briefs - October 2021