Improved diagnostics through quantitative ultrasound imaging

Abstract

Conventional B-mode imaging in ultrasound consists of displaying the log-compressed envelope of the backscattered signal. While clinical ultrasonic B-mode images have good spatial resolution, i.e., better than a millimeter, the contrast resolution of ultrasonic B-mode images is typically low. However, additional information is contained in the ultrasonic backscattered signal, which can be used to create images related to tissue microstructure. Because diagnosis of disease is typically based on histological examination of tissue microstructure, the ability to quantify and describe tissue microstructure through ultrasound may result in improved diagnostic capabilities of ultrasound. Tissue-mimicking phantoms and animal models of breast cancer were used to assess the ability of novel ultrasonic imaging techniques to quantify microstructure. Four parameters were extracted from the ultrasonic backscattered signal and related to the microstructure. The effective scatterer diameter (ESD) and the effective acoustic concentration (EAC) parameters were based on modeling the frequency dependence of the backscatter. The k parameter (which quantifies the periodicity of scatterer locations) and the mu parameter (which estimates the number of scatterers per resolution cell) were based on modeling the statistics of the backscattered envelope. Images constructed with these parameters resulted in an increase in contrast between diseased tissue and normal tissues but at the expense of spatial resolution. Specifically, in simulation, quantitative ultrasound (QUS) increased the contrast-to-noise ratio (CNR) between targets and background by more than 10 times in some cases. Statistically significant differences were observed between three kinds of tumors using the ESD, EAC, and k parameters. QUS imaging was also improved with the addition of coded excitation. A novel coded excitation technique was used that improved the variance of estimates over conventional pulsing methods, e.g- , the variance of ESD estimates were reduced by a factor of up to 10.

Three-Dimensional High-Frequency Backscatter and Envelope Quantification of Cancerous Human Lymph Nodes

“…Nevertheless, in a recent study, the HK distribution was used in conjunction with computationally-extensive algorithms to characterize cardiac tissues (Hao et al, 2002). More recently, a new parameter-estimation algorithm for the HK distribution was developed that is efficient and robust (Hruska et al, 2009; Hruska and Oelze, 2009). This improved parameter-estimation algorithm provides more accurate information to elucidate better the relationships between the envelope statistics and the underlying structures responsible for the signals.…”

Evaluation of the impact of backscatter intensity variations on ultrasound attenuation estimation

“…Quantitative ultrasound (QUS) parameters such as the attenuation slope, sound speed, backscatter coefficient, effective scatterer diameter, and spacing have been investigated in order to evaluate the pathological state of tissue. [1][2][3][4][5] The ability to estimate the attenuation slope accurately is important for the estimation of many of the other QUS parameters. In addition, the attenuation slope may provide a direct correlation to diagnostic approaches that are used for clinical diagnosis currently.…”

High-Frequency Acoustic Impedance Imaging of Cancer Cells

“…The BSC has been used to characterize tissue microstructures in ocular, myocardial, liver and kidney tissues (Insana et al 1992;Lizzi et al 1983Lizzi et al , 1987Wear 1987). Additionally, maps of the spatial distribution of the BSC were used to monitor high-intensity focused ultrasound (HIFU) treatments (Kemmerer et al 2010), detect abnormal lymph nodes (Mamou et al 2011), differentiate between cancer tissues (Hruska et al 2009;Oelze et al 2004) and identify various forms of cell death (Kolios et al 2002(Kolios et al , 2003. In some cases, the BSC could not be used to identify breast cancers, although the optical images displayed a clear difference in the cellular microstructure (Oelze and Zachary 2006).…”