In vitro diagnosis of axillary lymph node metastases in breast cancer by spectrum analysis of radio frequency echo signals

Axillary lymph node status is of particular importance for staging and managing breast cancer. Currently, axillary lymph node dissection is performed routinely in cases of invasive breast cancer because of the lack of accurate noninvasive methods for diagnosing lymph node metastasis. We investigated the diagnostic ability of ultrasonic tissue characterization based on spectrum analysis of backscattered echo signals to detect axillary lymph node metastasis in breast cancer in vitro compared with in vitro B-mode imaging. Immediately after surgery, individual lymph nodes were isolated from axillary tissue. Each lymph node was scanned in a water bath using a 10-MHz instrument, and radio frequency data and B-mode images were acquired. Spectral parameter values were calculated, and discriminant analysis was performed to classify metastatic and nonmetastatic lymph nodes. Forty histologically characterized axillary lymph nodes were enrolled in this study, including 25 nonmetastatic and 15 metastatic lymph nodes. A significant difference existed in the spectral parameter values (slope and intercept) for metastatic and nonmetastatic lymph nodes. Spectral parameter-based discriminant function classification of metastatic vs. nonmetastatic lymph nodes provided a sensitivity of 93.3%, specificity of 92.0%, and overall accuracy of 92.5%. In comparison, B-mode ultrasound images of in vitro lymph nodes provided a sensitivity of 73.3%, specificity of 84.0%, and overall accuracy of 80.0%. Receiver operating characteristic (ROC) analysis comparing the efficacy of both methods gave an ROC curve area of 0.9888 for spectral methods, which was greater than the area of 0.8980 for B-mode ultrasound. Hence, this in vitro study suggests that the diagnostic ability of spectrum analysis may prove to be markedly superior to that of B-mode ultrasound in detecting axillary lymph node metastasis in breast cancer. Because of these encouraging results, we intend to conduct an investigation of the ability of spectral methods to classify metastatic axillary lymph nodes in vivo.     

Comparison of template-matching and singular-spectrum-analysis methods for imaging implanted brachytherapy seeds

Brachytherapy using small implanted radioactive seeds is becoming an increasingly popular method for treating prostate cancer, in which a radiation oncologist implants seeds in the prostate transperineally under ultrasound guidance. Dosimetry software determines the optimal placement of seeds for achieving the prescribed dose based on ultrasonic determination of the gland boundaries. However, because of prostate movement and distortion during the implantation procedure, some seeds may not be placed in the desired locations; this causes the delivered dose to differ from the prescribed dose. Current ultrasonic imaging methods generally cannot depict the implanted seeds accurately. We are investigating new ultrasonic imaging methods that show promise for enhancing the visibility of seeds and thereby enabling real-time detection and correction of seed-placement errors during the implantation procedure. Real-time correction of seed-placement errors will improve the therapeutic radiation dose delivered to target tissues. In this work, we compare the potential performance of a template-matching method and a previously published method based on singular spectrum analysis for imaging seeds. In particular, we evaluated how changes in seed angle and position relative to the ultrasound beam affect seed detection. The conclusion of the present study is that singular spectrum analysis has better sensitivity but template matching is more resistant to false positives; both perform well enough to make seed detection clinically feasible over a relevant range of angles and positions. Combining the information provided by the two methods may further reduce ambiguities in determining where seeds are located.     

Statistics of ultrasonic spectral parameters for prostate and liverexaminations

A theoretical analysis was performed to describe statistical characteristics of calibrated spectral parameters used for ultrasonic tissue evaluation in the prostate and liver. The analysis assumes that radiofrequency (rf) echo signals exhibit Gaussian statistics. It derives the probability density function (pdf) of spectral parameters that are computed using sliding-window analysis techniques. The analysis relates the standard deviations of linear-regression spectral-parameter estimates to system and analysis parameters including bandwidth, center frequency, and the length of the sliding analysis window. The analysis also derives the pdf for mid-band fit parameter images. Theoretical results are found to agree well with clinical data from homogeneous segments in liver and prostate. The results offer a basis for evaluating spectral-estimator precision and for conducting future studies of lesion detectability based on spectral features     

Simulation studies of ultrasonic backscattering and B-mode images of liver using acoustic microscopy data

Data obtained from a scanning laser acoustic microscope (SLAM) were used to examine several aspects of ultrasonic backscattering from the liver. Phase interferograms from normal and abnormal human-liver specimens were digitized, and a series of algorithms was used to compute images of propagation velocity within the specimens. The propagation velocity images were then employed to simulate A- and B-mode results. These initial simulations were used to investigate how ultrasonic echo signals are related to tissue microstructure. Among the topics examined were B-mode speckling, frequency and beamwidth effects, and angulation dependencies.     

Holography and Medicine

Holography has emerged from the laboratory and is slowly becoming a useful tool in a variety of engineering and scientific areas. The potential exists for holography to serve as such a tool in medical and biological research. Holography can be used to form three-dimensional images. Three dimensionality is a consequence of the recording of phase information in the hologram. The presence of phase information in holographic images makes them extremely versatile and amenable to such a posteriori techniques as interferometry and dark-field imagery. Holography can also be used to analyze images, that is, to enhance image contrast and resolution, or to perform such functions as correlation analyses and pattern recognition. Moreover, the versatility of holography extends beyond the visible portion of the electromagnetic spectrum; holograms made with infrared, ultraviolet, microwave, or ultrasonic illumination, or ``synthetic' holograms made using a computer can be used to produce visible images or to analyze nonvisible images. The manner in which holography's potential can be used in biomedical applications is discussed.     

Statistical framework for ultrasonic spectral parameter imaging

This study examines the statistics of ultrasonic spectral parameter images that are being used to evaluate tissue microstructure in several organs. The parameters are derived from sliding-window spectrum analysis of radiofrequency echo signals. Calibrated spectra are expressed in dB and analyzed with linear regression procedures to compute spectral slope, intercept and midband fit, which is directly related to integrated backscatter. Local values of each parameter are quantitatively depicted in gray-scale cross-sectional images to determine tissue type, response to therapy and physical scatterer properties. In this report, we treat the statistics of each type of parameter image for statistically homogeneous scatterers. Probability density functions are derived for each parameter, and theoretical results are compared with corresponding histograms clinically measured in homogeneous tissue segments in the liver and prostate. Excellent agreement was found between theoretical density functions and data histograms for homogeneous tissue segments. Departures from theory are observed in heterogeneous tissue segments. The results demonstrate how the statistics of each spectral parameter and integrated backscatter are related to system and analysis parameters. These results are now being used to guide the design of system and analysis parameters, to improve assays of tissue heterogeneity and to evaluate the precision of estimating features associated with effective scatterer sizes and concentrations.