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<p>Heart failure is one of the most common cardiac disorders and is projected to increase
in prevalence over the next few decades. It can arise from a wide variety of root
causes such as coronary artery disease, hypertension, cardiomyopathy, or cardiotoxicity
and can manifest as systolic and/or diastolic dysfunction. Traditionally, its diagnosis
has been based on monitoring qualitative changes in cardiac structure, such as chamber
geometry and wall motion patterns, or quantitative changes in indices of cardiac function,
such as the blood flow velocities and ventricular ejection fraction. These parameters
are assessed in clinical settings using medical imaging modalities like ultrasound
and magnetic resonance imaging. Recent research into cardiac pathophysiology has indicated
that the progression of cardiac disease is often accompanied by changes in the mechanical
properties of cardiac muscle. Interrogation of these changes could be used to gain
useful diagnostic insight into the etiology of heart failure.</p><p>Acoustic radiation
force (ARF)-based techniques, such as acoustic radiation force impulse (ARFI) imaging
and shear wave elasticity imaging (SWEI), provide the means to measure mechanical
properties of soft tissues using ultrasound. They operate on the principle that ultrasound
can be used to remotely generate as well as track micron-level vibrations in the body
and thus derive mechanical properties such as tissue stiffness. ARFI and SWEI have
previously been shown to capture dynamic changes in myocardial stiffness in Langendorff
set-ups, open-chest experiments, and intracardiac settings. This dissertation explores
the challenges and opportunities of implementing acoustic radiation force-based methods
for noninvasive applications via transthoracic imaging windows. </p><p>Transthoracic
imaging of the heart using ultrasound can be challenging for a number of reasons.
The two main sources of signal degradation that were hypothesized to impact ARFI and
SWEI in this environment are acoustic clutter and intrinsic tissue motion. Acoustic
clutter refers to incorrectly localized echoes which lead to the degradation of target
conspicuity, border delineation, and image quality. Intrinsic tissue motion, on the
other hand, impedes the ability to accurately measure the ARF-induced motion and consequently
affects the estimation of tissue stiffness. The work presented herein focuses on quantifying
the level of both sources of signal degradation under \textit{in vivo} imaging conditions
and evaluating the effectiveness of strategies to minimize their impact. Lastly, the
feasibility of tracking dynamic myocardial stiffness through the cardiac cycle via
transthoracic imaging windows on human volunteers was investigated.</p><p>Harmonic
imaging is often used to suppress acoustic clutter in clinical settings. Clutter levels
are also closely tied to the choice of beamforming configuration used. Quantifying
the impact of harmonic imaging and transmit beamforming (focused versus plane wave)
on acoustic clutter, under \textit{in vivo} transthoracic imaging conditions is therefore
important. Clutter level, for a given imaging scenario, was quantified using contrast
between the cardiac chambers and the interventricular septum. Substantial variations
in clutter levels were observed across as well as within volunteers. Harmonic imaging
had a measurable impact in suppressing clutter under both the plane wave (2.97$\,$dB)
and focused (6.1$\,$dB) configurations. However, even in the optimal configuration
(harmonic-focused), clutter levels varied over a broad range (4$\,$-$\,$22$\,$dB).
These results suggest that acoustic clutter, while consistently lowered through the
use of harmonic imaging, is still likely to be a major detriment to transthoracic
measurement of myocardial stiffness. </p><p>The heart exhibits complex and rapid
three-dimensional motion; this could be a dominant confounder when attempting to measure
micron-level ARF-induced displacements. Intrinsic cardiac motion of the interventricular
septum, as observed through the parasternal long- and short-axis views, was analyzed
in both the time- and frequency-domain. Two types of motion filters, frequency-based
(high-pass filters) and recovery-based (polynomial filters) were compared to assess
their ability to separate the axial component of cardiac motion from the ARF-induced
motion. The effect of non-axial cardiac motion on speckle decorrelation was quantified
using temporal coherence and related to the uncertainty of axial displacement estimation
or jitter. High-pass filters with cutoffs $>$75$\,$Hz and quadratic polynomial filters
were found to be equally effective at compensating for axial tissue motion. While
high-pass filters are independent of a recovery-time assumption, they introduce a
downward bias to measured ARF-induced motion; this bias increases with cutoff frequency.
Temporal coherence was empirically related to measured displacement estimation jitter.
At end-diastole, temporal coherence was high and jitter was low (0.5$\,$-$\,$2.5$\,\mu$m).
In other phases of the cardiac cycle, however, jitter was found to increase dramatically
with the span of the temporal window over which it was computed. Jitter for short
spans, 2$\,$ms, was found to be in the range of 2$\,$-$\,$8$\,\mu$m, However, for
spans of 10$\,$ms, it could be as high as 10$\,$-$\,$20$\,\mu$m. These results indicate
that the noise-floor for micron-level axial displacement estimation in the myocardium
via transthoracic imaging windows can be fairly high (compared to the magnitude of
ARF-induced displacements) and can vary considerably over the cardiac cycle. </p><p>In
the final study, M-mode ARFI imaging was performed on twelve healthy volunteers to
track stiffness changes within the interventricular septum in the parasternal long-
and short-axis views. Myocardial stiffness dynamics over the cardiac cycle were quantified
using five indices: stiffness ratio, rates of relaxation and contraction, and time
constants of relaxation and contraction. Yield of ARFI acquisitions was evaluated
based on metrics of signal strength and tracking fidelity such as displacement signal-to-noise,
signal-to-clutter level, temporal coherence of speckle, and spatial similarity within
the region-of-excitation. These were quantified using the mean ARF-induced displacements
over the cardiac cycle, the contrast between the myocardium and the cardiac chambers,
the minimum correlation coefficients of RF signals (over a 2$\,$ms window), and the
correlation between displacement traces across simultaneously-acquired azimuthal beams,
respectively. Forty-one percent of ARFI acquisitions were determined to be \say{successful}
using a mean ARF-induced displacement threshold of 1.5 $\mu$m. \say{Successful} acquisitions
were found to have higher i) signal-to-clutter levels, ii) temporal coherence, and
iii) spatial similarity compared to \say{unsuccessful} acquisitions. Median values
of these three metrics, between the two groups, were measured to be 13.42$\,$dB vs.
5.42$\,$dB, 0.988 vs. 0.976, and 0.984 vs. 0.849, respectively. Signal-to-clutter
level, temporal coherence, and spatial similarity were also found to correlate with
each other. Across the cohort of healthy volunteers, stiffness ratio was measured
to be 2.74$\,\pm\,$0.86; rate of relaxation was 7.82$\,\pm\,$4.69$\,$/s and contraction
was -7.31$\,\pm\,$3.79$\,$/s; time constant of relaxation was 35.90$\,\pm\,$20.04$\,$ms,
and contraction was 37.24$\,\pm\,$19.85$\,$ms. ARFI-derived indices of myocardial
stiffness were found to be similar in both views. </p><p>In summary, despite the many
challenges that are inherent to the transthoracic imaging environment, acoustic radiation
force-based techniques were found to capture the dynamic trends of myocardial stiffness
when appropriate conditions are met. Future work to improve the strength of ARF-excitations,
better characterize or circumvent the influence of noise sources such as acoustic
clutter and tissue motion, and explore the association between ARFI/SWEI-derived myocardial
stiffness and traditional indices of cardiac function will be critical to realizing
the diagnostic potential of acoustic radiation force-based ultrasound methods in clinical
cardiology.</p>
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