Browsing by Subject "Elasticity imaging"
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Item Open Access Acoustic Radiation Force Impulse Imaging of Myocardial Performance(2009) Hsu, Stephen JohnCardiovascular disease is the leading cause of death for developed countries, including the United States. In order to diagnose and detect certain cardiac diseases, it is necessary to assess myocardial performance and function. One mechanical property that has been shown to reflect myocardial performance is myocardial stiffness. Acoustic radiation force impulse (ARFI) imaging has been demonstrated to be capable of visualizing variations in local stiffness within soft tissue.
In this thesis, the initial investigations into the visualization of myocardial performance with ARFI imaging are presented. In vivo ARFI images were acquired with a linear array placed on exposed canine hearts. When co-registered with the electrocardiogram (ECG), ARFI images of the heart reflected the expected changes in myocardial stiffness through the cardiac cycle. With the implementation of a quadratic motion filter, motion artifacts within the ARFI images were reduced to below 1.5 &mu m at all points of the cardiac cycle. The inclusion of pre-excitation displacement estimates in the quadratic motion filter further reduced physiological motion artifacts at all points of the cardiac cycle to below 0.5 &mu m.
In order for cardiac ARFI imaging to more quantitatively assess myocardial performance, novel ARFI imaging sequences and methods were developed to address challenges specifically related to cardiac imaging. These improvements provided finer sampling and improved spatial and temporal resolution within the ARFI images. In vivo epicardial ARFI images of an ovine heart were formed using these sequences, and the quality and utility of the resultant ARFI-induced displacement curves were examined.
In vivo cardiac ARFI images were formed of canine left ventricular free walls while the hearts were externally paced by one of two electrodes positioned epicardially on either side of the imaging plane. Directions and speeds of myocardial stiffness propagation were measured within the ARFI imaging field of view. In all images, the myocardial stiffness waves were seen to be traveling away from the stimulating electrode. The stiffness propagation velocities were also shown to be consistent with propagation velocities measured from elastography and tissue velocity imaging as well as the local epicardial ECG.
ARFI-induced displacement curves of an ovine heart were formed and temporally registered with left ventricular pressure and volume measurements. From these plots, the synchronization of myocardial stiffening and relaxation with the four phases (isovolumic contraction, ejection, isovolumic relaxation, and filling) of the cardiac cycle was determined. These ARFI imaging sequences were also used to correlate changes in left ventricular performance with changes in myocardial stiffness. These preliminary results indicated that changes in the ARFI imaging-derived stiffnesses were consistent with those predicted by current, clinically accepted theories of myocardial performance and function.
These results demonstrate the ability of ARFI imaging to visualize changes in myocardial stiffness through the cardiac cycle and its feasibility to provide clinically useful insight into myocardial performance.
Item Open Access Improving Prostate Cancer Detection using Multiparametric Ultrasound(2021) Morris, Daniel CodyProstate 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.
Item Open Access Multi-Dimensional Ultrasonic Shear Wave Reconstructions: Improving the Accuracy of Viscoelastic Parameter Estimation(2018) Lipman, SamanthaHepatocellular 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.