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\begin{document}

\title{Beyond Standard Echocardiography: Strain Imaging as the AI-Powered Key
to Comprehensive Cardiac Function Evaluation}



\author[1]{Samir Saha}%
\author[1]{Adnan Rahman}%
\author[2]{Anatoli Kiotsekoglou}%
\affil[1]{Region Stockholm}%
\affil[2]{Umea Universitet}%


\vspace{-1em}



  
  \date{May 27, 2024}


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\selectlanguage{english}
\begin{abstract}
Strain imaging as a tool to engage in unravelling the secrets of cardiac
motion in health and disease has opened a new horizon in the field of
clinical cardiology beyond the standard algorithm for quantification of
left ventricular function and dysfunction. As such, the wider
application of strain can probably be compared with the ubiquitous
application of the incretin molecule, glucagon like peptide 1 receptor
agonist (GLP 1RA) first applied to manage type 2 diabetes, that is now
indicated in many different conditions like obesity, heart failure, and
Alzheimer's disease! This commentary would focus on the role of
automated strain imaging in heart failure, aortic stenosis, cardiac
amyloidosis, atrial fibrillation, left atrial, and right ventricular
strain, on a 2-dimensional domain of spacetime navigated, to some
extent, by AI. This commentary thus argues that automated strain imaging
is becoming an essential tool for comprehensive cardiac assessment
across various conditions.%
\end{abstract}%



\sloppy


\textbf{Title page}

\textbf{Beyond Standard Echocardiography:~Strain Imaging as the
AI-Powered Key to Comprehensive Cardiac Function Evaluation}

Authors:

Samir Saha \textsuperscript{1} , Adnan Rahman\textsuperscript{1} , and
Anatoli Kiotsekoglou\textsuperscript{2}

Affiliations:

\selectlanguage{ngerman}\emph{\textsuperscript{1} Acudoc cardiac imaging laboratory, Stockholm,
and \textsuperscript{2} Umeå University Hospital, Umeå, Sweden} .

\textbf{Address of Correspondence:}

Samir K Saha. MD, PhD, FACC, FESC

Consultant Cardiologist,

Acudoc Cardiac Imaging Laboratory

Stockholm,

Sweden.

E mail: \emph{samirksaha@gmail.com}

Phone: + 46 7351351756

X: @samirsaha

WhatsApp +46761001303

``Spacetime tells matter how to move; matter tells spacetime how to
curve''.

John Wheller, an American theoretical physicist explaining Einstein´s
general theory of relativity.

\textbf{Abstract} :

Strain imaging as a tool to engage in unravelling the secrets of cardiac
motion in health and disease has opened a new horizon in the field of
clinical cardiology beyond the standard algorithm for quantification of
left ventricular function and dysfunction. As such, the wider
application of strain can probably be compared with the ubiquitous
application of the incretin molecule, glucagon like peptide 1 receptor
agonist (GLP 1RA) first applied to manage type 2 diabetes, that is now
indicated in many different conditions like obesity, heart failure, and
Alzheimer's disease! This commentary would focus on the role of
automated strain imaging in heart failure, aortic stenosis, cardiac
amyloidosis, atrial fibrillation, left atrial, and right ventricular
strain, on a 2-dimensional domain of spacetime navigated, to some
extent, by AI. This commentary thus argues that automated strain imaging
is becoming an essential tool for comprehensive cardiac assessment
across various conditions.

\ldots{}\ldots{}\ldots{}\ldots{}\ldots{}\ldots{}\ldots{}\ldots{}\ldots{}\ldots{}\ldots{}\ldots{}\ldots{}\ldots{}\ldots{}\ldots{}\ldots{}\ldots{}\ldots{}\ldots{}\ldots{}\ldots{}\ldots{}\ldots{}\ldots{}\ldots{}\ldots{}\ldots{}\ldots{}\ldots{}\ldots{}\ldots{}\ldots{}

Only about a few decades ago coronary artery disease (CAD) was the prime
focus of cardiovascular research. Limitations in detection methods led
to the exploration of new tools like tissue Doppler imaging (TDI). The
European MYDISE data confirmed the potential of TDI in enhancing
detection \textsuperscript{1},~as did those from
Australia\textsuperscript{2}. The investigators have shown that
application of the velocity of left ventricular motion enhances the
sensitivity and specificity of dobutamine stress echocardiography for
detection of coronary artery disease, non-invasively.

In the review published in this issue of the journal by Gherbesia E et
al \textsuperscript{3} the authors have shown that the 2D speckle
tracking strain imaging,~built upon the foundation of TDI,~is now a
reliable tool for assessment and management of various cardiac
conditions beyond CAD.

\textbf{Atrial fibrillation: the story begins with the left atrium.}

After half a dozen guidelines from the ACC, AHA, and ESC, the latest one
for the first time ever recommends rhythm control as a first line
management strategy either by ablation or by antiarrythmic
drugs\textsuperscript{4}. The document also elegantly presents criteria
for selection of patients most suitable for ablation. Among others the
size of the left atrium is the key. However, the size or the volume of
the left atrium may not matter more than its mechanical
integrity\textsuperscript{5}. Kuppahally, et al \textsuperscript{6} have
shown the left atrial strain is a surrogate for fibrosis and the degree
of fibrosis, and consequently magnitude of reservoir strain, depends on
whether the AF is paroxysmal (less fibrosis, better strain) or
persistent (more the fibrosis, worse is the strain). A just published
paper has shown that an increased glucose (FDG-PET) metabolism in LA
results in decreased LA strain: after successful ablation and
restoration of sinus rhythm, the uptake of glucose decreases, and the
longitudinal strain increases that coincides with decreased LA
volume\textsuperscript{7}. To negotiate the hydraulic and mechanical
properties of the LA, the new AFI software provides biplane LA volume
and all the three components of reservoir, conduit, and booster strain
in no time (Figure 1). The AFI software in fact utilizes machine
learning algorithms to automate LA volume and strain
measurements,~thereby significantly streamlining the process. We expect
that in the not- too- distant future, cardiologists and
electrophysiologists will utilize the ultra-modern SW for superfast
assessment of LA size and strain at one go before considering ablation
in eligible subjects.

\textbf{Heart failure with preserved ejection fraction (HFPEF).}

Although the currently available echo software does not use the large
language model (LLM) based neural network characteristic of classic AI,
the Mayo group \textsuperscript{8} has used and LLM-AI algorithm to
accurately diagnose HPPEF just by quantifying a single, apical 4-
chamber cine-loop of the LV! Quite fascinating that the model not only
could generate E/E´ ratio, but it also generated LV-GLS, on a
2-dimensional spacetime!

\textbf{Aortic stenosis and myocardial work}

It is known that severe aortic stenosis may lead to premature end of
life, if untreated, as shown by the scholarly paper by Ross and
Braunwald 54 years ago \textsuperscript{9}. However, the question
regarding timing of valve replacement is not a straightforward one for
several reasons mainly subjective development of symptoms and objective
evidence so called ``collateral damage'' (extra valvular damage due to
sustained afterload increase). Serial follow up is therefore necessary
to evaluate the progression of the disease. The 2020 ACC
recommendations\textsuperscript{10} has outlined a follow up interval
for example in case of moderate disease. Keeping in mind that, it is
also possible by analyzing myocardial work indices including global
wasted work and global work efficiency to accurately predict valve area
compared to traditional methods like the continuity equation,~aiding in
optimal decision-making for follow up prior to valve replacement
(Figures, 2, 3).

\textbf{The two familiar faces of thick hearts: hypertrophic
cardiomyopathy (HCM) and cardiac amyloidosis (CA).}

The two most recent triumphs of modern medicine have been the emergence
of medical management of HCM and CA. In both the cases, therefore,
accurate echocardiographic diagnosis is extremely important and strain
imaging is mandatory, particularly for phenotyping differentiation of
thick hearts. In HCM, all the three morphological distributions
(sigmoid, reverse curve, apical) have distinct strain patterns, while in
CA the demonstration of classic apical sparing of left ventricular
longitudinal strain ( ``cherry on the top'', one of the ``red flags'')
always necessitates referral for further investigation to confirm CA (by
hematologic, scintigraphic, genetic,
histologic)\textsuperscript{11}.While apical strain is generally spared
in CA,~different regions within the apex may exhibit subtle variations
in their response to pressure overload, as illustrated by differing
pressure strain loops obtained by myocardial work. These
variations~highlight the regional differences in how these areas respond
to demand of the poorly functioning heart (Figures 4,5). In case of
hypertrophic cardiomyopathy, in which there clearly exists a gradient of
strain within the Bull's eye plot differentiating HCM from CA,
myocardial work indices may also uncover how a poorly functioning left
ventricle distorting the pressure strain curve reminiscent of a stiff
chamber despite preserved LVEF ( Figure 6).

\textbf{Right ventricle: The unforgettable chamber}

For many years, the right ventricle received less attention than the
left ventricle and was relegated to a Cinderella status. Human folly, as
always have been, short lived, fortunately, and now we know that a
modernist approach to improve quality of life (6-mimue walk test) and
well-being of the RV (improved TAPSE) is at our disposal, as shown by
the Triluminate trial \textsuperscript{12}. Although the investigators
have used TAPSE in the trial, it is possible to simultaneously compute
TAPSE, RV strain and fractional area change (FAC\%) at one go, using 2D
strain in real time, providing a more comprehensive picture of RV
systolic function. (Fig 7).

To conclude, the painstakingly written review
\textsuperscript{3}published simultaneously in this issue of the
journal, the authors focused on the mechanistic, computational, and
clinical aspects of speckle tracking strain imaging of the left
ventricle. This document may stand out as a stand-alone reference guide
for the application of strain in a wide variety of cardiac illnesses by
novice and expert sonographers and cardiologists alike. Non only that,
the review could be useful for the ultrasound physicists and engineers
for future advancements in AI-powered strain imaging technologies,
eventually contributing to improved diagnosis,~prognosis,~and management
of various cardiac conditions. With that goal, it is time that we had an
ultrafast, AI-driven full-proof tool for quantifying cardiac
quadri-chamber mechanical function that can ``revolutionize''
cardiology\textsuperscript{13} in a similar fashion as did Einstein´s E=
mc.\textsuperscript{2} Given the superior spatial and temporal
resolution of the modern stain software, this is no longer a distant
dream, unlike in the cases of celestial bodies.

\textbf{Figure Legends:}

Legend to Fig 1

Simultaneous computation of biplane left atrial volume and strain
(reservoir, conduit and booster strain) using the 2D strain software on
images sampled at \textgreater{}60 Hz. Data obtained using the 3-click
method (the 2 basal segments and at the roof of the atrium)

Legend to Fig 2

Application of indices of myocardial work in different phenotypes and
grades of aortic stenosis (AS). Left panel: Low flow low gradient
phenotype of severe AS with poor GWE, very low LV-GLS, and very high
global wasted work, necessitating emergent referral for valve
replacement. In comparison, a patient with moderate AS with preserved
global work efficiency (GWE) (upper right) may have a delayed follow up
while the patient in the lower right panel with reduced global wasted
work (GWW), would require a follow up echo sooner than the one with
preserved GWE.

Legend to Fig 3

Aortic valve area estimation using indices of myocardial work.
Parameters included in the model are LVEF\%, LV-GLS\%, global work
efficiency (GWE), global wasted work (GWW), global work index (GWI), and
global constructive work (GCW). Significant p-values are in red.

Legend to Fig 4

Left ventricular longitudinal strain with apical sparing pattern in
cardiac amyloidosis. The photo collage has been created just by 3-
clicking the apical 3-chamber cine-loops. The AI based software searches
the 2 other apical loops to compute the Bull´s eye with'' cherry on the
top'' without any more human aid on the 2D spacetime with the LV in
motion.

Legend to Fig 5

Myocardial work efficiency and the apical sparing strain: the differing
pressure strain loops in different apical segments (the green pressure
strain loops in panels B, C, and D) may suggest that the preserved
apical strain may not be homogeneously distributed. Fig A is the global
pressure strain loop in red. Bar diagrams: the green represents
constructive work; blue represents wasted work. Pathophysiological
significance of such heterogeneity is currently unknown.

Legend to Figures 6.

A patient with sigmoid type hypertrophic cardiomyopathy. On the right
side a Bull´s eye plot, created by tracking 3 apical loops, shows
regional strain gradients. On the left side myocardial work index
showing a distorted and truncated pressure strain loop, suggesting a
stiff left ventricle with low global strain and low work efficiency.

Legend to Fig 7

Fig 7. 2 D strain imaging of the right ventricle. Applying a ''3-click''
method that is by placing the cursor at the two basal and the third at
the apical segment, the software simultaneously generates TAPSE, FAC\%
and global strain in no time, thereby facilitating an accurate
assessment of RV systolic function.

\textbf{Legend to the summary slide:}

Application of left ventricular and left atrial strain to tell apart
cardiac from non- cardiac dyspnea.

Upper left: a patient with non-cardiac dyspnea without elevation of
filling pressure despite E/E´ratio 20. All other parameters are normal.
Lower right: A patient with HFPEF and atrial fibrillation. Upper right.
A patient with HFPEB in sinus rhythm showing significantly impaired
LV-GLS\% value. Lower right: Correlation between LA reservoir strain and
NT-proBNP in a small cohort of HFPEF population in a primary care
setting. The data emphasizes the value of incorporating LA strain in
evaluating LV diastolic function/filling pressure \textsuperscript{14}.

\textbf{Acknowledgements:}

The authors would like to thank the Google´s Bard Chatbot for assisting
us rephrasing some AI-related expressions used in this commentary. Part
of the data in this commentary was presented at the quality summit of
the American College of Cardiology, October 2023 and at the Mayo
Clinic´s Key Imaging Meeting, autumn 2023.

\textbf{References}

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