Browsing by Subject "Shear Wave Elasticity Imaging"

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.

Implemented on an intracardiac echocardiography transducer, acoustic radiation force methods may provide a useful means of characterizing the heart's elastic properties. Elasticity imaging may be of benefit for diagnosis and characterization of infarction and heart failure, as well as for guidance of ablation therapy for the treatment of arrhythmias. This thesis tests the hypothesis that with appropriately designed imaging sequences, intracardiac acoustic radiation force impulse (ARFI) imaging and shear wave elasticity imaging (SWEI) are viable tools for quantification of myocardial elasticity, both temporally and spatially. Multiple track location SWEI (MTL-SWEI) is used to show that, in healthy in vivo porcine ventricles, shear wave speeds follow the elasticity changes with contraction and relaxation of the myocardium, varying between 0.9 and 2.2 m/s in diastole and 2.6 and 5.1 m/s in systole. Infarcted tissue is less contractile following infarction, though not unilaterally stiffer. Single-track-location SWEI (STL-SWEI) is proven to provide suppression of speckle noise and enable improved resolution of structures smaller than 2 mm in diameter compared to ARFI and MTL-SWEI. Contrast to noise ratio and lateral edge resolution are shown to vary with selection of time step for ARFI and arrival time regression filter size for STL-SWEI and MTL-SWEI.

In 1.5 mm targets, STL-SWEI achieves alternately the tightest resolution (0.3 mm at CNR = 3.5 for a 0.17 mm filter) and highest CNR (8.5 with edge width = 0.7 mm for a 0.66 mm filter) of the modalities, followed by ARFI and then MTL-SWEI.

In larger, 6 mm targets, the CNR-resolution tradeoff curves for ARFI and STL-SWEI overlap for ARFI time steps up to 0.5 ms and kernels $\leq$1 mm for STL-SWEI. STL-SWEI can operate either with a 25 dB improvement over MTL-SWEI in CNR at the same resolution, or with edge widths 5$\times$ as narrow at equivalent CNR values, depending on the selection of regression filter size. Ex vivo ablations are used to demonstrate that ARFI, STL-SWEI and MTL-SWEI each resolve ablation lesions between 0.5 and 1 cm in diameter and gaps between lesions smaller than 5 mm in 3-D scans. Differences in contrast, noise, and resolution between the modalities are discussed. All three modalities are also shown to resolve ``x''-shaped ablations up to 22 mm in depth with good visual fidelity and correspondence to surface photographs, with STL-SWEI providing the highest quality images. Series of each type of image, registered using 3-D data from an electroanatomical mapping system, are used to build volumes that show ablations in in vivo canine atria. In vivo images are shown to be subject to increased noise due to tissue and transducer motion, and the challenges facing the proposed system are discussed. Ultimately, intracardiac acoustic radiation force methods are demonstrated to be promising tools for characterizing dynamic myocardial elasticity and imaging radiofrequency ablation lesions.