Estimation of Sound Velocity and Attenuation Coefficient for Breast Ultrasound Imaging
Date Issued
2010
Date
2010
Author(s)
Chang, Chen-Han
Abstract
Recently, breast cancer has been one of the leading causes of death from cancer in females. Therefore, the study of its early detection has become an important issue now. Mammography has always been considered as the most common and the most effective screening method for detecting breast cancer because it can detect non-palpable and small tumors. However, the issue about ionization radiation is disputable. Besides, the images of dense breast region cover the images of small tumor region so that misdiagnosis happens. Toward this drawback, ultrasonic breast imaging can provide some aid. In short, ultrasonic breast imaging has many advantages, including noninvasive method, without ionizing radiation, portable, not limited to dense breast, and real-time. However, the use of conventional ultrasonic pulse-echo B-mode imaging to find breast tumors is also often limited by the image distortion caused by sound-velocity inhomogeneities in the breast tissue. Using other characteristics of tissue, such as sound velocity and attenuation coefficient, would provide diagnosticians additional information to increase the accuracy of diagnosis.
The aim of the first part of this study was to determine the efficacy of using sound velocity and tissue attenuation to clinically discriminate breast cancer from healthy tissues. The method requires only raw channel data acquired by a linear transducer array and can therefore be implemented on existing clinical systems. In this study, these methods were tested on clinical data. A total of 19 biopsy-proven cases were evaluated. A imaging setup consisting of a 5-MHz, 128-channel linear array was used to simultaneously obtain B-mode image data, time-of-flight data and attenuation data. The sound velocity and attenuation coefficient can be reconstructed inside and outside a region of interest manually selected in the B-mode image. To reduce distortion caused by tissue inhomogeneities, an optimal filter derived from pulse-echo data—with water replacing the breast tissue—is applied. These results indicate that carcinoma (CA) can be discriminated from fibroadenoma (FA) and fat by choosing an appropriate threshold for the relative sound velocity (i.e., 18.5 m/s). However, the large variations in the attenuation within the same type of tissue make simple thresholding ineffective. Nevertheless, the method described in this study has the potential to reduce negative biopsies and to improve the accuracy of breast cancer detection in clinics.
In the second part of this study, we implemented three different approaches to evaluate attenuation and one combined method in order to help the differentiation of breast cancer. Performance of these approaches is investigated based on simulation data. The three approaches are: video signal analysis (VSA), spectral estimation using periodogram (PER), and minimum side difference (MSD). Note that all approaches can readily be implemented using current B-mode imaging setup. First, VSA is to observe the gray-level gradient on a B-mode image. Second, PER is implemented by estimating the center frequency from the periodogram of the beamform data. Third, MSD is calculated using gray-level values of areas posterior to the region of interest, and left and right posterior to the ROI. In VSA, an effective frequency is required and typically the nominal center frequency is used. However, with a broadband pulse an accurate estimate of the effective frequency is needed to avoid large errors in VSA. In this study, we propose a modified VSA method in which PER is used to estimate the effective frequency. It is shown that accuracy of the VSA method can be improved by the proposed method particularly when the transmit bandwidth is large.
Subjects
Time-of-flight
Attenuation
Region-of-interest
Sound velocity
Attenuation coefficient
Video signal analysis
Periodogram
Minimum side difference
SDGs
Type
thesis
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