"Using heart signals produced at the
body surface, we can try to reconstruct what's going on inside your
heart," said UC Santa Barbara graduate student Abhejit Rajagopal, an author on the paper .
"This is typically done by simulating a model for the propagation of
signals from your heart to the surface and inverting it. The 'inverted' model
is known as an
. Typically, if the forward model is linear so
is the inverse operator."
from
numerous ECG impulses on the surface of the chest. Quantitative interpretation
of these superficial signals in the context of the underlying cardiac
electrical activity is an inverse mathematical problem and the current study is
one of the many algorithms that have been developed to solve it
As stated above, the
basic concept
employed by the UC Santa Barbara group's work
is that the inverse operator,
(a mathematical function that maps body-surface ECG signals to electrical
potentials in the innermost layer of the heart),
can also be expressed in a non-linear fashion and optimized
by adding patient-specific parameters
By carefully including more parameters,
presumed models of body tissue can be optimized by actual patient data to
provide more precise reconstructions of endocardial potentials.
"This enables development of models for
predicting cardiac potentials that are accurate and realistic from
electrocardiograms, and may be used as a new
cardiac imaging tool," said Rajagopal.
Applications of the Inverse Operator Model
- Someday,
instead of a
doctor listening to the heart using a stethoscope, they may be able
to see a live video of the heart activity
via ultrasound with corresponding measurements of local electrical
potentials around the heart. This technology will enable doctors to
diagnose and treat patients with various heart conditions without the need
to perform invasive surgeries just to determine the cause of the problem
- In
some cases of atrial fibrillation, it may be possible to
localize the origin of the abnormal rhythm and
determine whether surgery is recommended for the patient.
"A lot of work remains to be done
before we can make this a reality," he said. "But our work is a good
step in that direction, since it shows that the resolution of the noninvasive
reconstruction can be sufficiently high to aid in diagnosis and prognosis of
such cardiac disorders."
Conclusion
The current research is significant
because it shows that that much higher resolution of the tissues is possible if
nonlinear reconstruction algorithms are employed using a few extended data,
compared with what is described theoretically using linear methods and partial
data.
Rajagopal said, "We were surprised that we didn't need
to explode the number of parameters allowed in the reconstruction. By adding
just a few extra parameters -- while still respecting the structure of the
original reconstruction algorithm -- we found that high-accuracy reconstruction
is possible."
References :- Noninvasive reconstruction of cardiac electrical activity: update on current methods, applications and challenges - (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4446282/)
- Nonlinear electrocardiographic imaging using polynomial approximation networks - (https://aip.scitation.org/doi/10.1063/1.5038046)
Source: Medindia
