Ultrasonic spectrum analysis for tissue evaluation

Abstract

Spectrum analysis procedures have been developed to improve upon the diagnostic capabilities afforded by conventional ultrasonic images. These procedures analyze the frequency content of broadband, coherent echo signals returned from the body. They include calibration procedures to remove system artifacts and thereby provide quantitative measurements of tissue backscatter. Several independent spectral parameters have been used to establish databases for various organs; several investigations have shown that these parameters can be used with statistical classifiers to identify tissue type. Locally computed spectra have been used to generate sets of images displaying independent spectral parameters. Stained images have been derived by analyzing these parameter images with statistical classifiers and using color to denote tissue type (e.g., cancer). This report describes spectrum analysis procedures, discusses how measured parameters are related to physical tissue properties, and summarizes results describing estimator precision. It also presents illustrative clinical results showing how such procedures are being adapted to address specific clinical problems for a number of organs. This report indicates where further developments are needed and suggests how these techniques may improve image segmentation for three-dimensional displays and volumetric assays.

Introduction

Over the past three decades, ultrasonic imaging has emerged as a standard diagnostic technique within a broad range of medical specialities (Kremkau, 1990). Pulse-echo ultrasound systems are routinely used to obtain cross-sectional images of the abdomen, heart, breast, prostate, and eye, and they have become the international standard for imaging the fetus. The use of ultrasound is motivated by its proven clinical utility as well as several other factors including its safety record, real-time visualization, ease of use, and the availability of economic systems. Ultrasonography is likely to become even more useful because of on-going developments (Goldberg et al., 1994; Sherar and Foster, 1989) that include advanced ultrasonic arrays and digital processing (for improved imaging), contrast agents (to enhance imaging and quantification of blood flow), probe miniaturization (for incorporation in catheters to examine blood-vessel disease), and very-high-frequency transducers (for improved spatial resolution).

While conventional ultrasonic images (termed B-mode images) convey key diagnostic information, these images are degraded by phenomena that are not usually encountered with other imaging modalities, such as magnetic resonance and computed tomography, used in radiology. As described in this report, image degradations occur because of the coherent nature of ultrasound, the complex interaction of tissues and ultrasonic waves, and the fact that reflections (echoes) are employed for imaging. These factors lead to random speckles, artifactual specular-reflection drop-outs, and spatially varying resolution in ultrasonic images. The extent of these degradations is affected by the instrument and the instrument settings which are used in examinations.

The image degradations impede the direct application of conventional pattern recognition procedures to ultrasonic images. They also hinder attempts to quantify tissue features for objective diagnostic schemes.

These considerations have prompted many investigations that seek to improve ultrasonic imaging and to provide a framework for quantitative tissue evaluation. This report describes frequency-domain approaches that have been developed to analyze ultrasonic echoes and to generate alternative types of ultrasonic images. Frequency-domain techniques offer fundamental advantages for addressing a number of constituent problems in ultrasonography. First, they permit a systems perspective that clarifies and separates the effects of system components and tissue properties on image features. Second, they afford a convenient means of incorporating well-established frequency-domain results describing ultrasonic beam propagation and tissue scattering. Third, averaged power spectra provide a cogent means of addressing the stochastic nature of tissue microstructure.

Spectral techniques are designed to analyze coherent radio frequency (RF) echo signals, digitally acquired at the outputs of ultrasonic transducers, as opposed to the RF-signal envelope (video signals) that are displayed in conventional B-mode ultrasonic images (Lizzi et al., 1983; Feleppa et al., 1986). This is an important distinction because calibration and corrective procedures that can be applied to RF spectra are usually not applicable following the non-linear process of envelope detection. Video detection also obliterates subtle RF-signal features that can convey important information regarding tissue microstructure.

The spectral techniques described in this report can evaluate two independent parameters that characterize ultrasonic scattering by tissues: one parameter provides a measure of overall scattering strength, while the other measures the frequency dependence of scattering. Under certain conditions (e.g., known or negligible acoustic attenuation), these spectral parameters can be used to estimate two independent physical properties of tissue constituents (related to their size and concentration) (Lizzi et al., 1987). Thus, unlike conventional ultrasonography, which provides a single qualitative image, spectral procedures can yield a pair of images depicting independent, quantitative tissue parameters.

Spectral techniques have been clinically deployed in two complementary modes. The first computes average spectral parameters within a demarcated spatial region: this mode is often employed in database studies that elucidate parameter values indicative of specific diseases. The second mode generates spectral parameter images that have been linked to quantitative clinical databases to assist disease detection and diagnosis (Feleppa et al., 1986). Spectral parameter images offer new opportunities for pattern recognition based on conjoint, independent parameters. They may become particularly valuable for automated boundary determination and segmentation of different tissue structures. These opportunities are just beginning to be explored and promise to become key elements for automated tissue biometry and three-dimensional (3-D) imaging.

This report first summarizes the operation of ultrasonic systems and describes image artifacts associated with different types of tissues. It then describes spectrum analysis and calibration procedures, and presents illustrative averaged spectra for different types of tissue. The report next describes how local spectral features are computed and displayed to form sets of cross-sectional spectral parameter images. Next, the report summarizes how spectral parameters are related to physical scatterer properties including the effective sizes, concentrations, and mechanical properties of subresolution tissue constituents. The statistics of spectral parameters are described in terms of system and analysis parameters, and explicit relationships are presented regarding the trade-offs between, e.g., spatial resolution and statistical variability in spectral parameter images.

The last section of the report summarizes clinical spectral results for several organs and illustrates how spectral techniques can be adapted to meet particular medical needs. Because calibrated spectrum analysis provides quantitative outputs, images of spectral parameters can be compared to organ-specific databases that characterize sets of spectral parameters indicative of particular diseases. In examinations of the eye, where biopsies are precluded, database information is being used to identify and subclassify ocular tumors (Feleppa et al., 1986; Feleppa and Lizzi, 1993), using colored “stains” superimposed on two-dimensional (2-D) and 3-D images. Non-invasive treatment monitoring is also being implemented by staining tumor segments whose spectral parameters have changed due to microstructural alterations induced by radiotherapy or intense-ultrasonic therapy (Lizzi et al., 1997a). In prostate examinations, database information combining spectral parameters and blood levels of prostate specific antigen (PSA) are being used to detect prostate cancer (Feleppa et al., 1996, Feleppa et al., 1997); “suspicious” regions are being color coded to guide biopsy placement. In breast examinations, spectral parameters and morphological descriptors of tumor shapes are being used with the goal of differentiating benign and malignant tumors to avoid the risks, expense, and anxiety associated with unneeded biopsies (Alam et al., 2000, Alam et al., 2002a, Alam et al., 2002b).

Cardiac examinations have employed a spectral parameter (integrated backscatter (IB)) to detect aberrant cyclic variations associated with myocardial infarction (O’Donnell et al., 1981; Vered et al., 1987). Studies of the kidney have shown how spectral parameters and derived estimates can elucidate kidney microstructure and characterize kidney disease (Insana et al., 1991; Garra et al., 1994). Several studies have shown how spectral techniques may help diagnose local and diffuse liver disease (Oosterveld et al., 1991; King et al., 1985). Other promising results have been obtained for characterizing threats posed by vascular plaque (Lee et al., 1999) and for identifying cancerous metastases in lymph nodes (Tateishi et al., 1998). Recent in vitro studies have shown that spectral techniques may sense cell division and death (Kolios et al., 1999), thereby providing an important non-invasive potential for monitoring the efficacy of emerging tumor-therapy agents.

In addition to tissue applications, the theoretical framework for spectrum analysis has been modified to treat ultrasonic contrast agents, so that spectra can be used to help improve ultrasonic evaluation of blood flow and tissue perfusion (Deng et al., 1998).

This report cites our own research results to explain key points involved in spectral procedures and to provide a unified framework for describing the relations between theory, implementation, and clinical results. Using this framework, the report also cites relevant reports of the many other investigators who have made important contributions to developing frequency-domain approaches for ultrasonic examinations.