Conventional medical imaging technologies, including ultrasound, have continued to improve over the years. For example, in oncology, medical imaging is characterized by high sensitivity, i.e., the ability to detect anomalous tissue features, but the ability to classify these tissue features from images often lacks specificity. As a result, a large number of biopsies of tissues with suspicious image findings are performed each year with a vast majority of these biopsies resulting in a negative finding. To improve specificity of cancer imaging, quantitative imaging techniques can play an important role. Conventional ultrasound B-mode imaging is mainly qualitative in nature. However, quantitative ultrasound (QUS) imaging can provide specific numbers related to tissue features that can increase the specificity of image findings leading to improvements in diagnostic ultrasound. QUS imaging techniques can encompass a wide variety of techniques including spectral-based parameterization, elastography, shear wave imaging, flow estimation and envelope statistics. Currently, spectral-based parameterization and envelope statistics are not available on most conventional clinical ultrasound machines. However, in recent years QUS techniques involving spectral-based parameterization and envelope statistics have demonstrated success in many applications, providing additional diagnostic capabilities. Spectral-based techniques include the estimation of the backscatter coefficient, estimation of attenuation, and estimation of scatterer properties such as the correlation length associated with an effective scatterer diameter and the effective acoustic concentration of scatterers. Envelope statistics include the estimation of the number density of scatterers and quantification of coherent to incoherent signals produced from the tissue. Challenges for clinical application include correctly accounting for attenuation effects and transmission losses and implementation of QUS on clinical devices. Successful clinical and pre-clinical applications demonstrating the ability of QUS to improve medical diagnostics include characterization of the myocardium during the cardiac cycle, cancer detection, classification of solid tumors and lymph nodes, detection and quantification of fatty liver disease, and monitoring and assessment of therapy.

Quantitative imaging methods using high-frequency ultrasound (HFU) offer a means of characterizing biological tissue at the microscopic level. Previously, high-frequency, threedimensional (3D) quantitative-ultrasound (QUS) methods were developed to characterize 46 freshly-dissected lymph nodes of colorectal-cancer patients. 3D ultrasound radio-frequency data were acquired using a 25.6-MHz center-frequency transducer and each node was inked prior to tissue fixation to recover orientation after sectioning for 3D histological evaluation. Backscattered echo signals were processed using 3D cylindrical regions-of-interest (ROIs) to yield four QUS estimates associated with tissue microstructure (i.e., effective scatterer size, acoustic concentration, intercept, and slope). These QUS estimates, obtained by parameterizing the backscatter spectrum, showed great potential for cancer detection. In the present study, these QUS methods were applied to 112 lymph nodes from 77 colorectal and gastric cancer patients. Novel QUS methods parameterizing the envelope statistics of the ROIs using Nakagami and homodyned-K distributions also were developed; they yielded four additional QUS estimates. The ability of these eight QUS estimates to classify lymph nodes and detect cancer was evaluated using ROC curves. An area under the ROC curve of 0.996 with specificity and sensitivity of 95% were obtained by combining effective scatterer size and one envelope parameter based on the homodyned-K distribution. Therefore, these advanced 3D QUS methods potentially can be valuable for detecting small metastatic foci in dissected lymph nodes.

High-frequency ultrasound (HFU) offers a means of investigating biological tissue at the microscopic level. High-frequency, three-dimensional (3D) quantitative-ultrasound (QUS) methods were developed to characterize freshly-dissected lymph nodes of cancer patients. 3D ultrasound data were acquired from lymph nodes using a 25.6-MHz center-frequency transducer. Each node was inked prior to tissue fixation to recover orientation after sectioning for 3D histological evaluation. Backscattered echo signals were processed using 3D cylindrical regions-of-interest to yield four QUS estimates associated with tissue microstructure (i.e., effective scatterer size, acoustic concentration, intercept, and slope). QUS estimates were computed following established methods using two scattering models. In this study, 46 lymph nodes acquired from 27 patients diagnosed with colon cancer were processed. Results revealed that fully-metastatic nodes could be perfectly differentiated from cancer-free nodes using slope or scatterer-size estimates. Specifically, results indicated that metastatic nodes had an average effective scatterer size (i.e., 37.1 ± 1.7 um) significantly larger (p <0.05) than that in cancer-free nodes (i.e., 26 ± 3.3 um). Therefore, the 3D QUS methods could provide a useful means of identifying small metastatic foci in dissected lymph nodes that might not be detectable using current standard pathology procedures.

Determining the rupture pressure threshold of ultrasound contrast agent microbubbles has significant applications for contrast imaging, development of therapeutic agents, and evaluation of potential bioeffects. Using a passive cavitation detector, this work evaluates rupture based on acoustic emissions from single, encapsulated, gas-filled microbubbles. Sinusoidal ultrasound pulses were transmitted into weak solutions of Optison TM at different center frequencies (0.9, 2.8, and 4.6 MHz), pulse durations (three, five, and seven cycles of the center frequencies), and peak rarefactional pressures (0.07 to 5.39 MPa). Pulse repetition frequency was 10 Hz. Signals detected with a 13-MHz, center-frequency transducer revealed postexcitation acoustic emissions (between 1 and 5 μs after excitation) with broadband spectral content. The observed acoustic emissions were consistent with the acoustic signature that would be anticipated from inertial collapse followed by "rebounds" when a microbubble ruptures and thus generates daughter/free bubbles that grow and collapse. The peak rarefactional pressure threshold for detection of these emissions increased with frequency (e.g., 0.53, 0.87, and 0.99 MPa for 0.9, 2.8, and 4.6 MHz, respectively; five-cycle pulse duration) and decreased with pulse duration. The emissions identified in this work were separated from the excitation in time and spectral content, and provide a novel determination of microbubble shell rupture.