Browsing by Author "Nightingale, Kathryn R"

Prostate cancer is the most common cancer and second-leading cause of cancer death among men in the United States. Early and accurate diagnosis of prostate cancer remains challenging; following an abnormal rectal exam or elevated levels of prostate-specific antigen in serum, clinical guidelines recommend transrectal ultrasound-guided biopsy. However, lesions are often indistinguishable from noncancerous prostate tissue in conventional B-mode ultrasound images, which have a diagnostic sensitivity of about 30%, so the biopsy is not typically targeted to suspicious regions. Instead, the biopsy systematically samples 12 pre-specified regions of the gland. Systematic sampling often fails to detect cancer during the first biopsy, and while multiparametric MRI (mpMRI) techniques have been developed to guide a targeted biopsy, fused with live ultrasound, this approach remains susceptible to registration errors, and is expensive and less accessible.

The goal of this work is to leverage ultrasound elasticity imaging methods, including acoustic radiation force impulse (ARFI) imaging and shear wave elasticity imaging (SWEI), to develop and optimize a robust 3-D elasticity imaging system for ultrasound-guided prostate biopsies and to quantify its performance in prostate cancer detection. Towards that goal, in this dissertation advanced techniques for generating ARFI and SWEI images are developed and evaluated, and a deep learning framework is explored for multiparametric ultrasound (mpUS) imaging, which combines data from different ultrasound-based modalities.

In Chapter 3, an algorithm is implemented that permits the simultaneous imaging of prostate cancer and zonal anatomy using both ARFI and SWEI. This combined sequence involves using closely spaced push beams across the lateral field of view, which enables the collection of higher signal-to-noise (SNR) shear wave data to reconstruct the SWEI volume than is typically acquired. Data from different push locations are combined using an estimated shear wave propagation time between push excitations to align arrival times, resulting in SWEI imaging of prostate cancer with high contrast-to-noise ratio (CNR), enhanced spatial resolution, and reduced reflection artifacts.

In Chapter 4, a fully convolutional neural network (CNN) is used for ARFI displacement estimation in the prostate. A novel method for generating ultrasound training data is described, in which synthetic 3-D displacement volumes with a combination of randomly seeded ellipsoids are used to displace scatterers, from which simulated ultrasonic imaging is performed. The trained network enables the visualization of in vivo prostate cancer and prostate anatomy, providing comparable performance with respect to both accuracy and speed compared to standard time delay estimation approaches.

Chapter 5 explores the application of deep learning for mpUS prostate cancer imaging by evaluating the use of a deep neural network (DNN) to generate an mpUS image volume from four ultrasound-based modalities for the detection of prostate cancer: ARFI, SWEI, quantitative ultrasound, and B-mode. The DNN, which was trained to maximize lesion CNR, outperforms the previous method of using a linear support vector machine to combine the input modalities, and generates mpUS image volumes that provide clear visualization of prostate cancer.

Chapter 6 presents the results of the first in vivo clinical trial that assesses the use of ARFI imaging for targeted prostate biopsy guidance in a single patient visit, comparing its performance with mpMRI-targeted biopsy and systematic sampling. The process of data acquisition, processing, and biopsy targeting is described. The study demonstrates the feasibility of using 3-D ARFI for guiding a targeted biopsy of the prostate, where it is most sensitive to higher-grade cancers. The findings also indicate the potential for using 2-D ARFI imaging to confirm target location during live B-mode imaging, which could improve existing ultrasonic fusion biopsy workflows.

Chapter 7 summarizes the research findings and considers potential directions for future research. By developing advanced ARFI and SWEI imaging techniques for imaging the prostate gland, and combining information from different ultrasound modalities, prostate cancer and zonal anatomy can be imaged with high contrast and resolution. The findings from this work suggest that ultrasound elasticity imaging holds great promise for facilitating image-guided targeted biopsies of clinically significant prostate cancer.

Shear wave elastography imaging (SWEI) of skeletal muscle is of great interest to the medical community, as there is a large need for a non-invasive, quantitative biomarker of muscle health that relates to muscle function. SWEI measures mechanical properties by generating quantitative images of tissue stiffness using an acoustic radiation force (ARF) excitation in the material and measuring the resulting shear waves that propagate outward. Most SWEI tools assume an isotropic, linear, elastic material, however skeletal muscle is commonly modeled as transversely isotropic (TI) due to the alignment of the muscle fibers. This means that shear wave speed (c, SWS) is dependent on the direction of the traveling shear wave relative to the fibers in skeletal muscle.

If muscle is assumed to be incompressible and transversely isotropic (ITI) it can be described with three parameters: the longitudinal shear modulus μ_L, the transverse shear modulus μ_T, and a single parameter combining longitudinal and transverse Young's moduli (E_L and E_T) called tensile anisotropy χ_E. In an elastic ITI material, there are two shear wave modes with different polarizations that can be excited: the shear horizontal (SH) and the shear vertical (SV). Shear moduli μ_L and μ_T can be measured solely based on the observation of the SH mode, however to quantify tensile anisotropy χ_E using SWEI, it is necessary to observe the SV mode. This thesis explores characterizing skeletal muscle as an ITI material and explores factors that affect the measurement of the SV mode wave. In order to evaluate the use of χ_E as a biomarker of muscle health we must understand the factors that affect its measurement using SWEI.

Chapter 3 demonstrates feasibility of measuring both the SH and SV modes using a 3D rotational SWEI system in the vastus lateralis muscle in vivo. We develop and validate methodology to estimate μ_L, μ_T, and χ_E and describe measurements these parameters in vivo.

Chapter 4 explores the factors that affect the SV mode waves, using Green's function simulations to perform a parametric analysis to determine the optimal interrogation parameters to facilitate visualization and quantification of SV waves in muscle. We evaluate the impact of five factors: μ_L, μ_T, and χ_E as well as fiber tilt angle θ_tilt and F-number of the push geometry on SV mode speed, amplitude, and rotational distribution.

Chapter 5 extends the work in Chapter 4 to understand SH and SV wave propagation in 3D by simulating multiple observation tilt angles and all 3 components of displacement. Tilting the observation plane to particular angles allows for maximization of the strength of the SH or SV waves, demonstrating that observation of these tilted planes in in vivo data would increase opportunities for estimation of SH and SV waves.

The work presented in this thesis explores using 3D SWEI to better characterize skeletal muscle as an ITI material, specifically by assessing the SH and SV mode shear wave speed. This work also investigates factors that affect measurement of SV mode waves, and thus the ability to estimate χ_E, towards a better understanding of χ_E for use as a potential biomarker of muscle health.

Uganda is increasingly dependent upon imported biomedical pieces of equipment to support patient care and health related research. Most of this equipment arrives without the accompanying documentation, maintenance and support. In many cases, the equipment specifications are not suited to the local environment, which affects the durability and use of this equipment. The unfortunate result creates a vast array of medical equipment that lie about in various states of disrepair. Additionally, given the uniqueness of the environment and people in Africa, there is a need to design biomedical equipment that is suited to both the people and the environment. Although the graduates of the Makerere BME program participate in research, innovation and design of such low resource settings devices, these graduates lack a novel BME instrumentation course to implement their amazing innovations. This research thesis comes in to solve this dilemma by investigating economically effective lab components and skills necessary for designing such a course which will help grow the BME discipline and the institutional regional capacity to do basic science research.

The first chapter of this research comments about the medical equipment situation in Uganda in addition to the BME program in Makerere University. This chapter provides the researcher’s motivation and hypothesis for carrying out this research.

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The second chapter of this research focuses on the Duke BME instrumentation labs. This chapter concentrates on the 10 labs that the researcher carried out at Duke University and how such labs can gainfully be translated to the Makerere BME instrumentation course.

The third chapter deals with a discussion of the instrumentation laboratory and course experience that has been available to the BME majors at Makerere to date. This discussion involves results generated by a survey taken from the BME students who have just completed this course and those who have already graduated.

The fourth chapter discusses the current status and the researcher’s proposed BME lab design. Additionally, this chapter highlights the human resource, the current lab space dimensions, the furniture and fittings, the training equipment, lab reagents and consumables.

The fifth chapter comments about the BME instrumentation course currently carried out. This chapter is presents the progress of the first offering of the new BME instrumentation course taught at Makerere University that was designed this past summer following the Duke course model.

Finally, the last chapter six serves as the conclusion chapter for this thesis work. This chapter briefly analyzes the strengths, weaknesses, opportunities and threats (SWOT) for the current Makerere University BME instrumentation course. The chapter finally provides some critical findings and thereafter provides some recommendations.

Prostate cancer (PCa) is the most common non-cutaneous cancer in men in the United States. Early detection of PCa is essential for improving treatment outcomes and survival rates. However, diagnosis of PCa at an early stage is challenged by the lack of an imaging method that can accurately visualize PCas. Because pathological processes change the mechanical properties of the tissue, elasticity imaging methods have the potential to differentiate PCas from other prostatic tissues. Acoustic radiation force impulse (ARFI) imaging is a relatively new elasticity imaging method that visualizes the local stiffness variations inside soft tissue.

The work presented in this dissertation investigates the feasibility of prostate ARFI imaging. Volumetric ARFI data acquisition and display methods were developed to visualize anatomic structures and pathologies in ex vivo human prostates. The characteristic appearances of various prostatic tissues in ARFI images were identified by correlating ARFI images with McNeal's zonal anatomy and the correlated histological slides, in which prostatic pathologies were delineated by a pathologist blinded to the ARFI images. The results suggest ARFI imaging is able to differentiate anatomic structures and identify suspicious PCa regions in the prostate.

To investigate the correlation between ARFI displacement amplitudes and the underlying tissue stiffness in the prostate ARFI images, the mechanical properties of prostatic tissues were characterized using a quantitative method, based upon shear wave elasticity imaging (SWEI). Co-registered ARFI and SWEI datasets were acquired in excised prostate specimens to reconstruct the shear moduli of prostatic tissues. The results demonstrated that variations in ARFI displacement amplitudes were inversely related to the underlying tissue stiffness; and the reconstructed shear moduli of prostatic tissues had good agreements with those reported in literature. The study suggests the matched ARFI and SWEI datasets provide complementary

information about tissue's elasticity.

To increase the efficiency of the data acquisition, a novel imaging sequence was developed to acquired matched ARFI-SWEI datasets without increasing the number of excitations compared to a conventional ARFI imaging sequence. Imaging parameters were analyzed both theoretically and experimentally. An analytical model was derived to quantify the fundamental accuracy limit in the reconstructed shear modulus, and demonstrated good agreement with the experimental data. The novel sequence was demonstrated in tissue-mimicking phantoms.

Finally, ARFI imaging sequences were developed in a transrectal probe, and ARFI images were presented from in vivo data acquired in patients under radical prostatectomy. The in vivo ARFI images demonstrated decreased contrast and resolution as compared to the matched ex vivo ARFI data. However, prostate anatomy and some PCa were successfully visualized in the in vivo ARFI images. Thus, we conclude that ARFI imaging has the potential to provide image guidance for locating cancerous regions during PCa diagnosis and treatment.

Prostate cancer (PCa) is the most common non-cutaneous cancer in men with an estimated almost 30,000 deaths occurring in the United States in 2014. Currently, the most widely utilized methods for screening men for prostate cancer include the digital rectal exam and prostate specific antigen analysis; however, these methods lack either high sensitivity or specificity, requiring needle biopsy to confirm the presence of cancer. The biopsies are conventionally performed with only B-mode ultrasound visualization of the organ and no targeting of specific regions of the prostate, although recently, multi-parametric magnetic resonance imaging has shown promise for targeting biopsies. Earlier work has demonstrated the feasibility of acoustic radiation force impulse (ARFI) imaging and shear wave elasticity imaging (SWEI) to visualize cancer in the prostate, however multiple challenges with both methods have been identified.

The aim of this thesis is to contribute to both the technical development and clinical applications of ARFI and SWEI imaging using the latest advancements in ultrasound imaging technology.

The introduction of the Siemens Acuson SC2000 provided multiple technological improvements over previous generations of ultrasound scanners, including: an improved power supply, arbitrary waveform generator, and additional parallel receive beamforming. In this thesis, these capabilities were utilized to improve both ARFI and SWEI imaging and reduce acoustic exposure and acquisition duration. However, the SC2000 did not originally have radiation force imaging capabilities; therefore, a new tool set for prototyping these sequences was developed along with rapid data processing and display code. These tools leveraged the increasing availability of general purpose computing on graphics processing units (GPUs) to significantly reduce the data processing time, facilitating real-time display for ultrasonic research systems.

These technical developments for both acquisition and processing were applied to investigate new methods for ARFI and SWEI imaging. Specifically, the power supply on the SC2000 allowed for a new type of multi-focal zone ARFI images to be acquired, which are shown to provide improved image quality over an extended depth of field. Additionally, a new algorithm for SWEI image processing was developed using an adaptive filter based on a maximum a posteriori estimator, demonstrating increases in the contrast to noise ratio of lesion targets upwards of 50%.

Finally, the optimized ARFI imaging methods were integrated with a transrectal ultrasound transducer to acquire volumetric in vivo data in patients undergoing robotic radical prostatectomy procedures in an ongoing study. When the study was initiated, it was recognized that the technological improvements of Siemens Acuson SC2000 allowed for the off-axis response to the radiation force excitation to be concurrently recorded without impacting ARFI image quality. This volumetric SWEI data was reconstructed retrospectively using the approaches developed in this thesis, but the images were low quality. A further investigation identified multiple challenges with the SWEI sequence, which should be addressed in future studies. The ARFI image volumes were very high quality and are currently being analyzed to assess the accuracy of ARFI to visualize prostate anatomy and clinically significant prostate cancer tumors. After a blinded evaluation of the ARFI image volumes for suspicion of prostate cancer, three readers correctly identified 63% of all clinically significant tumors and 74% of clinically significant tumors in the posterior region, showing great promise for using ARFI in the context of prostate cancer visualization for targeting biopsies, focal therapy, and watchful waiting.

Prostate cancer (PCa) is the second most common cancer diagnosis, behind skin cancer, and the second most common cause of cancer-related death, behind lung cancer, for men in the United States. The prevalence of PCa increases with age and ranges from 1.8% of men being diagnosed with PCa before age 59 to 11.6% of men being diagnosed with PCa over the course of their entire lives. PCa is typically diagnosed using transrectal ultrasound (TRUS) guided biopsy which commonly consists of 10-12 systematically sampled biopsy cores taken from specified regions within the prostate. In TRUS guided biopsy, the TRUS B-mode imaging is used by the clinician to ensure the biopsy needles remain within the prostate but is not sensitive nor specific enough to identify and target PCa-suspicious regions. Multiparametric magnetic resonance imaging (mpMRI) fusion biopsy is the current gold standard for targeted PCa biopsy, though this approach comes at added cost and is not widely available. mpMRI fusion biopsy also requires the registration of the pre-biopsy mpMRI with real-time TRUS B-mode imaging which can result in an incorrectly targeted lesion due to registration error.This thesis explores advanced ultrasound techniques, such as acoustic radiation force impulse (ARFI) imaging, shear wave elasticity imaging (SWEI), quantitative ultrasound’s (QUS) midband fit parameter (MF), and multiparametric ultrasound (mpUS), for PCa identification and targeting during biopsy. The goals of this thesis are to (1) establish a shear wave speed (SWS) threshold for identifying PCa using SWEI, (2) create an mpUS approach which combines ARFI, SWEI, MF, and B-mode imaging and assess the improvement in PCa visibility when using mpUS and (3) assess the performance of ARFI, SWEI, MF, and mpUS when locating suspicious regions which align with mpMRI-identified PCa to provide registration validation during fusion biopsy. Combined, this thesis provides preliminary data and motivation for future work developing and assessing advanced ultrasound imaging methods for image-guided targeted prostate biopsy. The data included throughout this thesis was acquired using a custom ultrasound setup capable of acquiring both elasticity (ARFI and SWEI) and acoustic backscatter (B-mode and MF) data in a single imaging session. Additionally, the ultrasound system was paired with a rotation stage allowing for 3D data acquisition which yielded co-registered image volumes for each of the four ultrasound modalities. This data was acquired in patients immediately preceding radical prostatectomy. Histopathology analysis of the excised prostates was used to determine the ground truth locations of PCa for each patient, allowing for the labeling of the ultrasound data as PCa or healthy tissue. In Chapter 3, the SWEI data volumes were used to identify a shear wave speed (SWS) value threshold to separate PCa from healthy prostate tissue. This SWS threshold yielded sensitivities and specificities akin to mpMRI fusion biopsy. Additionally, a SWS ratio was assessed to normalize for tissue compression and patient variability. This threshold was accompanied by a substantial increase in specificity, positive predictive value (PPV), and area under the receiver operating characteristic curve (AUC). This section demonstrates the feasibility of using 3D SWEI data to detect and localize PCa and demonstrates the benefits of normalizing for applied compression during data acquisition for use in biopsy targeting studies. In Chapter 4, a linear support vector machine (SVM) was used to combine B-mode imaging, ARFI, SWEI, and MF into a synthesized mpUS volume to enhance lesion visibility. mpUS led to improvements in lesion visibility metrics compared to each individual ultrasound modality. The individual advanced ultrasound modalities (ARFI, MF, and SWEI) also all outperformed B-mode in contrast. The improved performance of mpUS demonstrates the benefit of combining ultrasound techniques based on different contrast mechanisms, supporting its utility for ultrasound-based targeted prostate biopsy. In Chapter 5, the histologically determined PCa locations were identified in mpMRI’s T2 and apparent diffusion coefficient (ADC) images and compared to the corresponding regions in B-mode, ARFI, SWEI, MF, and mpUS images. SWEI only failed to identify one PCa lesion in the posterior of the prostate and B-mode, MF, and ARFI all successfully identified 100% of the anterior lesions, indicating that, when combined, advanced ultrasound techniques facilitate the visualization of the majority of mpMRI-identified regions of interest throughout the entire prostate. Additionally, the mpUS combination developed in Chapter 4 was applied to a subset of 10 patients and resulted in correct localization of 88% (14/16) of the mpMRI-identified lesions. This work demonstrates the feasibility of using advanced ultrasound techniques to locate mpMRI-identified lesions, which would enable improved registration validation during fusion biopsy. Finally, Chapter 6 includes further insights into this work and the implications it may have on the diagnosis of PCa. Advanced ultrasound is a promising approach for both targeted PCa biopsy and for screening. Additionally, combining information from multiple advanced ultrasound techniques (ARFI, SWEI, and MF) yields improved performance over any single method indicating that the future of prostate ultrasound is multiparametric.

Hepatocellular carcinoma (HCC) lesions are often preceded by liver cirrhosis or Hepatitis C, and patients with these diagnoses are monitored every six months with an ultrasound screening. B-mode ultrasound is an ideal imaging modality for regular screening; however, ultrasound has demonstrated a low sensitivity for detecting small, early stage HCCs. Studies using ultrasonic elasticity methods have shown increased HCC lesion contrast compared to B-mode ultrasound. This thesis presents the preliminary work of shear wave elasticity imaging (SWEI) methods to improve estimates of viscoelastic parameters in the context of liver screening for tumors, with the goals of (1) using multi-dimensional directional filtering and shear wave reconstruction to reduce reflection artifacts, (2) evaluating bias introduced from small depth-of-field (DOF) excitations into frequency dependent shear wave speed (SWS) and attenuation estimates and (3) evaluating the feasibility of combining on-axis and off-axis elasticity methods to screen the entire liver.

Interfaces of different shear stiffness causes propagating shear waves to be reflected, which can lead to artifacts in SWS reconstructions due to the reflections both in and out of the imaging plane. Two-dimensional (2-D), three-dimensional (3-D), and four- dimensional (4-D) directional filters were applied to shear wave data, and SWS images were reconstructed with 2-D and 3-D shear wave reconstruction methods to quantify the reduction in image artifacts. For 2-D SWS image reconstructions, 3-D directional filters showed greater improvements in image quality than 2-D filters, and 4-D directional filters showed marginal improvement over 3-D filters. The 4-D directional filters have the largest impact in reducing reflection artifacts in 3-D SWS volumes.

Commercial scanners reconstruct shear wave speeds for a region of interest using time-of-flight (TOF) methods reporting a single SWS (or elastic modulus) to the end user under the assumptions that tissue is elastic and independent of frequency. Human tissues are known to be viscoelastic (VE), resulting in dispersion and attenuation. Existing methods to quantify shear wave dispersion and attenuation commonly make an assumption that the acoustic radiation force excitation acts as a cylindrical source with a known geometric shear wave amplitude decay. The bias in shear dispersion and attenuation estimates associated with making this cylindrical wave assumption (up to 15% for dispersion and 41% for attenuation) when applied to shear wave sources with finite depth extents in realistic focal geometries is greater for more tightly-focused acoustic radiation force sources with smaller DOF.

Curvilinear transducers are the standard probe used in ultrasound HCC screenings; however, previous studies using curvilinear arrays performing liver SWEI have been limited by penetration depth of the acoustic radiation force excitation. In order for SWEI to be feasible as an imaging method to screen for and detect HCC lesions, large, low frequency arrays designed for deep abdominal imaging must be used. A prototype low frequency deep abdominal curvilinear array and a proposed low frequency matrix array were simulated, and the combined dynamic on-axis response in the region of excitation (ROE) and the propagating shear wave (off-axis) response were used to create quantitative shear wave images of a spherical lesion using sparse acoustic radiation force excitations. The on-axis behavior in the ROE is related to the underlying stiffness of the material and a lookup table (LUT) approach can be used to determine a SWS in this region. Combined with traditional off-axis TOF methods, the combined methods can reduce the sparsity that would otherwise occur inside the ROE, which allows a larger field-of-view (FOV) to be interrogated with the same number of excitations. The on-axis and off-axis methods can be combined in either 2-D or 3-D reconstructions. The performance of the deep abdominal curvilinear array was comparable to the matrix array for 2-D SWEI imaging. A benefit of the curvilinear array over a large matrix array is its ability to image through intercostal acoustic windows. If there is not a sufficient subcostal acoustic window to use the matrix array to image the entire liver, a combination of both the matrix array and the curvilinear array can be used to scan the entire organ.

Ultrasound imaging is one of the most widely used diagnostic imaging modalities. Abdominal ultrasound is typically used for screening liver diseases, and it is the recommended modality for six month screening in patients at risk for hepatocellular carcinoma (HCC). The major drawback of abdominal ultrasound is poor image quality that is insufficient for diagnosis, which is reported in 25-60% of patients, and is often correlated with obesity. Tissue harmonic imaging (THI) has become the default imaging mode for most abdominal imaging exams. It has also been applied in motion tracking in ultrasound elastrography. THI provides better image quality through decreased sidelobe energy and decreased reverberation clutter in the abdominal wall compared to fundamental imaging. However, THI can be both signal-to-noise ratio (SNR) and penetration-depth limited during clinical imaging, resulting in decreased diagnostic utility.

A logical approach to increase the SNR of harmonic imaging is to increase the acoustic source pressure, but the acoustic output of diagnostic imaging has been subject to a de facto upper limit based upon the Food and Drug Administration (FDA) guideline for the Mechanical Index (MI < 1.9). This value was derived from historic values, rather than being linked to scientific evidence of bioeffects. A recent report from the American Institute of Ultrasound in Medicine (AIUM) concluded that exceeding the recommended maximum MI given in the FDA guidance up to an estimated in situ value of 4.0 could be warranted without concern for increased risk of cavitation in non-fetal tissues without gas bodies, if there there were concurrent improvement in diagnostic utility.

This thesis presents the preliminary work of evaluating the potential diagnostic benefit of employing acoustic output beyond the FDA guideline of MI = 1.9 in the context of hepatic imaging. Three clinical studies were performed with goals of: (1) quantifying the image quality improvement of using elevated acoustic output in B-mode harmonic imaging; (2) assessing penetration depth changes in harmonic imaging; and assessing elevated MI in (3) harmonic motion tracking and in (4) acoustic radiation force impulse (ARFI) excitation of shear wave elasticity imaging (SWEI). High MI B-mode harmonic imaging resulted in modest increases in the contrast-to-noise ratio of hypoechoic hepatic vessels. Difficult-to-image patients who suffer from poor ultrasound image quality demonstrated larger improvement than easy-to-image subjects. The imaging penetration depth increased linearly with increasing MI, on the order of 4 - 8 cm per unit MI increase for a given focal depth. High MI harmonic motion tracking resulted in considerable increase in shearwave speed (SWS) estimation yield, by 27% and 37% at focal depths of 5 cm and 9 cm respectively, due to improved harmonic tracking data quality through increased SNR and decreased jitter of tissue motion data. In addition, SWS estimation yield was shown to be linearly proportional to the push (ARFI excitation) energy. SWEI measurements with elevated push energy were successful in patients for whom standard push energy levels failed. These studies suggested that liver capsule depth could be used prospectively to identify patients who would benefit from elevated output in push energy. These results indicate that using elevated acoustic output has the potential to provide clinical benefit for diagnostic ultrasound.

Diagnostic ultrasound imaging is sometimes unable to yield clinically useful data. This is caused by the presence of body walls. This thesis examines how body walls impacts the propagation of ultrasound in the human body and searches for ways to improve image quality.Previous works have demonstrated remarkable improvements in tissue stiffness quantification with the use of elevated Mechanical Index (MI) during ultrasonic harmonic shear wave elasticity imaging (SWEI). Since ultrasound SWEI sequences consist of a long push pulse and a short tracking pulse, it remains unclear which one of the two pulses is impacted more by the body wall and benefits more from elevated MI. In Chapter 3, an opposing window experiment is devised and built to isolate the impacts of the body wall on push and track beams. Track beams are found to be more affected by the presence of body walls and to benefit from higher MI transmits. In Chapter 4, 3D nonlinear ultrasound simulations and experimental measurements were used to estimate the range of in situ pressures that can occur during transcutaneous abdominal imaging, and to identify the sources of error when estimating in situ peak rarefaction pressures (PRP) using linear derating as specified by the MI guideline. Using simulations, it was found that for a large transmit aperture (F/1.5) MI consistently overestimated in situ PRP by 20-48%, due primarily to phase aberration. For a medium transmit aperture (F/3), the MI accurately estimated the in situ PRP to within 8%. For a small transmit aperture (F/5), MI consistently underestimated the in situ PRP by 32-50%, with peak locations occurring 1-2 cm before the focal depth, often within the body wall itself. The large variability across body wall samples and focal configurations demonstrates the limitations of the simplified linear derating scheme. The results suggest that patient specific in situ PRP estimation would allow for increases in transmit pressures, particularly for tightly focused beams, to improve diagnostic image quality while ensuring patient safety. Tissue harmonic signal quality has been shown to improve with elevated acoustic pressure. The peak rarefaction pressure (PRP) for a given transmit, however, is limited by the FDA guideline for the mechanical index (MI). In Chapter 4, We demonstrated that the MI overestimates in situ PRP for tightly focused beams in vivo due primarily to phase aberration. In Chapter 5, we evaluate two spatial coherence-based image quality metrics, short-lag spatial coherence (SLSC) and harmonic short-lag spatial coherence (HSC), as proxy estimates for phase aberration and assess their correlation with in situ PRP in simulations and experimentally when imaging through abdominal body walls. We demonstrate strong correlation between both spatial coherence-based metrics with in situ PRP (r2 = 0.77 for HSC, r2 = 0.67 for SLSC), an observation that could be leveraged in the future for patient-specific selection of acoustic output.

Tissue stiffness can be an indicator of various types of ailments. However, no standard diagnostic imaging modality has the capability to depict the stiffness of tissue. To overcome this deficiency, various elasticity imaging methods have been proposed over the past 20 years. A promising technique for elasticity imaging is acoustic radiation force impulse (ARFI) based shear wave imaging. Spatially localized acoustic radiation force excitation is applied impulsively to generate shear waves in tissue and its stiffness is quantified by measuring the shear wave speed (SWS).

The aim of this thesis is to contribute to both the clinical application of ARFI shear wave imaging and its technical development using the latest advancements in ultrasound imaging capabilities.

To achieve the first of these two goals, a pilot imaging study was conducted to evaluate the suitability of ARFI shear wave imaging for the assessment of liver fibrosis using a rodent model of the disease. The stiffness of severely fibrotic rat livers were found to be significantly higher than healthy livers. In addition, liver stiffness was correlated with fibrosis as quantified using collagen content.

Based on these findings, an imaging study was conducted on patients undergoing liver biopsy at the Duke University Medical Center. A robust SWS estimation algorithm was implemented to deal with noisy patient shear wave data using the random sample consensus (RANSAC) approach. RANSAC estimated liver stiffness was found to be higher in severely fibrotic and cirrhotic livers, suggesting that ARFI shear wave imaging may potentially be useful for the staging of severe

fibrosis in humans.

To achieve the second aim of this thesis, a system capable of monitoring ARFI induced shear wave propagation in 3D was implemented using a 2D matrix array transducer. This capability was previously unavailable with conventional 1D arrays. This system was used to study the precision of time-of-flight (TOF) based SWS estimation. It was found that by placing tracking beam locations at the edges of the SWS measurement region of interest using the 2D matrix array, TOF SWS precision could be improved in a homogeneous medium.

The 3D shear wave imaging system was also used to measure the SWS in muscle, which does not conform to the isotropic mechanical behavior usually assumed for tissue, due to the parallel arrangement of muscle fibers. It is shown that the SWS along and across the fibers, as well as the 3D fiber orientation can be estimated from a single 3D shear wave data-set. In addition, these measurements can be made independent of the probe orientation relative to the fibers. This suggests that 3D shear wave imaging can be useful for characterizing anisotropic mechanical properties of tissue.

Ultrasound can be used for a variety of therapeutic purposes. High-intensity focused ultrasound (HIFU) has progressed over the past decade to become a viable therapeutic method and is valuable as a non-invasive alternative to many surgical procedures. Ultrasonic thermal therapies can also be used to release thermally sensitive liposomes encapsulating chemotherapeutic drugs. In the brain, the permeability of the blood-brain barrier to drugs, antibodies, and gene transfer can be increased with a mechanical mechanism using ultrasound and contrast agent.

The work presented in this dissertation tests the hypothesis that a diagnostic system can be used for combined imaging and therapeutic applications. In order to evaluate the effectiveness of a diagnostic system for use in therapeutic applications, a set of non-destructive tests is developed that can predict the potential for high acoustic output. A rigorous, nondestructive testing regimen for standard, diagnostic transducers to evaluate their potential for therapeutic use is formulated. Based on this work, transducer heating is identified as the largest challenge. The design and evaluation of several custom diagnostic transducers with various modifications to reduce internal heating are described. These transducers are compared with diagnostic controls using image contrast, face heating, hydrophone, and ARFI displacement measurements. From these results, we conclude that the most promising design is a passively and actively cooled, PZT-4 multilayer composite transducer, while the acoustically lossless lens and capactive micro-machined transducers evaluated herein are determined to be ineffective.

Three therapeutic applications are evaluated for the combined system. Image-guided spot ablations, such as in the treatment of early stage liver cancers, could not be successfully performed; however, the additional acoustic output requirements are determined to be on the order of 2.4 times those that can be currently produced without transducer damage in a clinically relevant amount of time (10-20 seconds per spot). The potential of a diagnostic system for a hyperthermia application is shown by producing temperatures for the duration necessary to release chemotherapeutic agents from thermally-activated liposomes without damage to the transducer. Finally, a mechanically-based therapeutic method for opening the BBB with ultrasonic contrast agent and specialized sonication regimes under ultrasonic B-mode guidance is demonstrated.

These studies indicate that a diagnostic system is capable of both moderate thermal and mechanical therapeutic applications under co-registered image-guidance.

In this work, I investigate the mechanical response of the liver to increasing pressure in the portal vein using ultrasonic approaches. In advancing liver disease, portal venous pressure increases lead to severe clinical problems and death. Monitoring these pressure increases can predict patient outcomes and guide treatment. Current methods for measurement of portal venous pressure are invasive, expensive, and therefore are rarely repeated. Ultrasonic methods show promise because they are noninvasive, but traditional ultrasound images and doppler measurements do not yield accurate repeatable measures of hepatic pressure. However, increases in portal venous pressure have been associated with higher estimates of liver stiffness using ultrasound-based shear wave speed estimation algorithms. These quantitative estimates of shear wave speed may provide a mechanism for noninvasive hepatic pressure characterization, but they cannot currently be distinguished from the increases in shear wave speed estimates that are also observed in patients with normal portal venous pressures with advancing liver diseases. Thus, a better understanding of the mechanisms by which hepatic pressure modulates estimates of liver stiffness could provide information needed to distinguish increasing hepatic pressure from advancing brosis stage. This work is devoted to identifying and characterizing the underlying mechanism behind the observed increases in hepatic shear wave speed with pressurization.

Two experiments were designed in order to dene the mechanical properties of liver tissue that underlie the observed increase in shear wave speeds with increasing portal venous pressure. First, the behavior of the liver was shown to be nonlinear (or strain-dependent) by comparing stiness estimates in livers that were free to expand and constrained from expansion at increasing hepatic pressures. Shear wave speeds were observed to increase only in the unconstrained case in which the liver was observed to qualitatively deform. Second, the deformation of the liver was quantied using a clinical scanner and 3-D transducer to generate estimates of axial strain during pressurization. Axial strain was found to increase with elevation in portal venous pressure. This axial expansion of the liver also corresponded to increases in shear wave speed estimates with portal venous pressure.

The techniques developed herein were used to elucidate mechanical properties of the pressurized liver by concurrent ultrasound-based quantication of hepatic deformation and stiffness. This work shows that increasing shear wave speed estimates with hepatic pressurization are associated with increases in hepatic axial strain measurements. These results provide the basis for quantifying the relationship between pressurization and hepatic strain, laying the foundation for hyperelastic material modeling of the liver. Such nonlinear mechanical models can provide the basis for noninvasive characterization of hepatic pressure using stiffness metrics in the future.

Ultrasound shear wave elasticity imaging (SWEI) has the potential to fill a critical clinical gap by providing biomarkers of muscle health that are noninvasive, inexpensive, and quantitative, which could augment or replace the current limited clinical options. However, skeletal muscle does not obey the typical isotropic assumption of SWEI systems, and instead has different properties in directions parallel and perpendicular to the muscle fibers (commonly modeled as a transversely isotropic material), complicating muscle characterization. Studies using traditional 2D-SWEI systems in skeletal muscle have been challenged by a high degree of variability, an inability to consistently measure properties perpendicular to the muscle fibers, and a reliance on manual probe alignment to the fiber direction. This dissertation investigates the ability of a rotational 3D-SWEI system to mitigate these limitations and presents preliminary research to move rotational 3D-SWEI for in vivo skeletal muscle characterization towards clinical translation.

Chapter 3 demonstrates the ability of a 3D-SWEI system to reconstruct shear wave speed (SWS) values along and across the muscle fibers without any manual probe alignment in the vastus lateralis of 10 healthy volunteers. The study demonstrates that 3D-SWEI improves the repeatability of SWS measurements both along and across the muscle fibers compared to 2D-SWEI measurements. Additionally, SWS in both dominant and non-dominant legs is evaluated, and no significant difference in SWS due to leg dominance is found along or across the fibers.

Chapter 4 presents the development and optimization of an algorithm for the automatic processing of 3D-SWEI skeletal muscle data. The results of several automatic algorithm implementations are compared to the results obtained using manual processing in 130 in vivo 3D-SWEI datasets, with analysis metrics including the percent of valid acquisitions (non-gross-error), percent bias, and absolute percent error. The optimal algorithm choice for relaxed muscle is determined to be a fixed lateral range (2–18 mm) Radon Sum method with multiwave detection and a shear wave speed ellipse fitting in the plane of symmetry. Additional results and conclusions are presented that can guide algorithm optimization for other applications.

In Chapter 5, the 3D-SWEI system and automatic analysis methods are used to evaluate the change in muscle stiffness with passive stretch in 10 healthy volunteers. A BioDex system is used to change the knee flexion angle, modulating the passive stretch of the vastus lateralis. These data are fit to report values of potential biomarkers that capture the change in muscle stiffness along and across the fibers with changing knee flexion, and the median within-subject variability of these biomarkers is found to be <16%. Additionally, the performance of the SWEI system is found to be best at high passive stretch states. The amplitude of shear waves propagating in different directions relative to the muscle fibers is also evaluated. This analysis shows that shear wave signal amplitude is higher along the fibers than across the fibers, that the difference in signal amplitude between the directions increases with increasing stretch, and that the magnitude of the difference is not explained by on-axis push strength differences or differences seen in TI material Green’s function simulations with matched shear moduli.

Overall, this work illustrates use of 3D-SWEI for in vivo skeletal muscle characterization and addresses key questions in the implementation of this technology for clinical use, including the repeatability of the system, methods to automatically analyze data, and the effects of passive stretch and joint position on 3D-SWEI measurements. This research can inform and enable further studies exploring the clinical application and development of 3D-SWEI biomarkers for skeletal muscle health.