Browsing by Subject "Shear Wave Imaging"

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.

Heart Failure (HF) is a major cause of morbidity and mortality in the world. This disorder is characterized by compromised systolic and/or diastolic function of the myocardium that reduces the pumping and/or filling efficiency resulting in diminished cardiac output. Cardiovascular researchers have been attempting to develop tools for assessment of cardiac function for decades. Evaluating cardiac function helps clinicians to diagnose and to follow the progress of HF patients.

The gold standard technique for cardiac functional assessment, including systolic and diastolic function, is the pressure-volume (PV) loop measurement; however, this measurement is not typically used clinically due to the invasiveness of the technique. PV loop measurement requires the introduction of a pressure or pressure-volume catheter into the left ventricle. Cardiovascular researchers have been attempting to develop non-invasive tools for assessment of cardiac function primarily by measuring surrogates of ventricular contractility and compliance.

These measures are based on imaging and include Ejection Fraction and Doppler and ultrasound strain imaging. These measurements are indirect measures that rely on cardiac motion or volume changes. The measurements are load dependent and could be affected by the heart rhythm and valvular disorders. Despite research toward this goal, there is no clinically accepted noninvasive technique to provide a direct myocardial measurement of cardiac function.

Acoustic radiation force (ARF) based ultrasound elastography techniques were developed in early 2000s and have been used to measure the static stiffness of tissue. These techniques are being used in the clinic for diagnosis of disorders and malignancies in tissues such as liver. When applied to the heart, it was shown that dynamic changes in the stiffness of the myocardium during the cardiac cycle could be recorded using modified versions of these static techniques.

This had the potential to be a direct measure of the time-varying elastance measured during the cardiac cycle using pressure-volume measurements. The question arose as to whether these ARF based measurements of dynamic stiffness could be used for cardiac functional assessments during systole and diastole; and if so, what the relationship is between these measurements and the gold standard method. The goal of this research was to assess the ability of ARF based measurements of cardiac dynamic stiffness to provide meaningful indices of cardiac function.

In this dissertation both acoustic radiation force impulse (ARFI) and shear wave elasticity imaging (SWEI) ultrasound elastography techniques were studied. These are qualitative and quantitative measures of stiffness, respectively. While the focus of the studies was more on SWEI due to its quantitative nature, ARFI measurements of cardiac function were also investigated and compared to SWEI.

The studies were performed in isolated rabbit hearts in Langendorff or working modes because the preparation has several significant advantages. 1) Parameters including preload, afterload, and coronary perfusion can be accurately controlled. 2) The heart’s left ventricular free wall can be easily imaged from multiple angles. 3) Confounding neurohormonal reflexes of the body can be eliminated.

SWEI measurements of stiffness were used to characterize changes in contractility induced using the Gregg effect. The Gregg effect is the active effect of coronary perfusion on cardiac contractility. It was shown that SWEI measurements of stiffness could detect the changes in contractility induced by this known effect and that the effect was blocked using a Ca channel blocker.

The relationship between ARFI and SWEI measurements was characterized and the possibility of deriving functional indices such as systolic/diastolic ratio and isovolumic relaxation time constant (τ) using either of these techniques was evaluated. It was shown that in the same imaging configuration, the measurements of ARFI and SWEI are linearly related to one another. This could be important, as the ARFI technique will likely be the first cardiac elastography measurement technique to be implemented using transthoracic ultrasound throughout the cardiac cycle.

The Garden Hose effect was used to investigate SWEI’s ability to measure cardiac compliance. SWEI was used to detect the passive effect of coronary perfusion on cardiac compliance and the relationship between perfusion pressure and stiffness was characterized. Finally, SWEI derived measurements of diastolic function were compared to the gold standard PV measurements of cardiac diastolic function including end diastolic stiffness and the relaxation time constant. It was shown that SWEI could detect the changes in cardiac stiffness after induction of global ischemia. These changes were similar to the changes in the PV measure of diastolic stiffness. Furthermore, the results indicated that SWEI could be used to derive the relaxation time constant similar to the relaxation constant derived from intra-ventricular pressure recordings.

In summary, the results of the studies presented in this thesis illustrate the assessments of systolic and diastolic function using ARFI and SWEI ultrasound based elastography. It is concluded that these measurements can be used to derive cardiac functional indices that would have the advantages of an ultrasound based technique; they would be noninvasive, less expensive and could be widely applied outside of the cath lab.

Radiofrequency ablation (RFA) is commonly used to treat cardiac arrhythmias, by generating a series of discrete RFA lesions in the myocardium to isolate arrhythmogenic conduction pathways. The size of each lesion is controlled by the temperature of the tissue at the surface or the duration of RF power delivery, but feedback on the extent and transmurality of the generated lesion are unavailable with current technology. Intracardiac Echocardiography (ICE) may provide a solution through Acoustic Radiation Force Impulse (ARFI) imaging or Shear Wave Imaging (SWI), which each generate images of local mechanical compliance from very small ultrasonically-induced waves. This work compares ARFI and SWI in an ex-vivo experiment for lesion boundary assessment and lesion gap resolution.