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Details of k-mean clustering segmentation are described by Glide et al. For more quantitative comparison, we calculated the mean sound-speeds for fatty tissue and breast parenchyma based on these segmentation results. The mean sound-speed of a lesion for a single patient was calculated by summing all sound-speeds for every pixel within the ROI in the selected slices, then dividing this summation by the total number of pixels. To avoid bias because of different ROI selection methods, we compared the mean sound-speeds for benign and malignant lesions for the above two groups Table 4.

No systematic difference was seen between these two ROI selection methods. Mean sound-speed histograms for 13 benign lesion and 19 malignant lesions are depicted in Figure 9 , where malignant lesions show, on average, higher mean sound-speed than benign lesions. Histogram of mean sound-speeds for 13 benign lesions solid line and 19 malignant lesions dashed line. The results of the phantom study, summarized in Figure 3 and Table 1 provided the necessary calibration to justify the application of the TV bent-ray tomography to in vivo breast data.

In addition, the comparisons in Figure 4 make it clear that the TV reconstruction is superior to the reconstruction obtained with the classic Tikhonov regularization. Although TV is computationally more intensive than Tikhonov reconstruction, Vogel et al.

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Our own experience suggests that reconstruction time for TV and Tikhonov regularization are about the same. We also compared in vivo TV bent-ray tomograms with their straight-ray counterparts. It was also obvious that the straight-ray tomograms were strongly degraded relative to the TV bent-ray tomograms because the linear approximation in straight-ray tomography was not accurate enough for the nonlinear inverse problem.

For our TV bent-ray tomograms Fig. Perhaps more importantly, the improved contrast in the TV bent-ray tomograms leads to significantly greater enhancement of the masses relative to the background. The results of our study suggest three potential clinical applications for our TV bent-ray algorithm that require accurate differentiation of focal areas that have different sound-speeds, including tracking them over time as a means to potentially reduce overall x-ray exposure to the breast in screening and follow-up.

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First, our sound-speed tomograms may be used to improve the accuracy of assessing breast density. Second, they can help to improve the detection and characterization of breast lesions. Third, they also can be used to better monitor clinical response of breast cancer patients to neo-adjuvant chemotherapy. We now discuss each of these applications. Breast density is an important risk factor for developing breast cancer. Studies have shown that women with high mammographic breast density are at higher risk of developing breast cancer Boyd et. We have previously shown Glide et al.

From fatty to dense breasts, the mean sound-speed values tend to increase. Based on straight-ray reconstructions, Glide-Hurst et al. As a result, CURE sound-speed tomograms can be potentially used to assess this breast cancer risk factor. Our in vivo study indicates that the TV bent-ray tomography algorithm can successfully image fatty and glandular tissue within the breast with higher resolution than the straight-ray algorithm Fig. As a result, we expect more accurate and better quantitative correlation between sound-speed and breast density in future studies.

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Another potential clinical application is to help detect and characterize breast lesions. More importantly, our study suggests greater detection of these elevated sound-speeds over the background for both malignant and benign breast lesions with the TV bent-ray algorithm. This further confirmed the feasibility of using sound-speed UCT to detect breast lesions, allowing higher contrast settings and improved threshold values for more prospective assessment of mass detection in the future.

These more accurate sound-speed characterizations also applied to characterizing higher sound-speeds for malignant than benign lesions. One potential way to characterize a breast lesion is to compare a sound-speed tomogram with the corresponding CURE attenuation and reflection images. Statistically, the malignant lesions have elevated sound-speed and attenuation relative to surrounding tissue Greenleaf et al. The architectural distortion at the tumor region in the reflection image is another indicator of cancer Stavros et al.

The addition of reflection and attenuation data can potentially further improve the separation of benign from cancer as illustrated in the color-coded fused image in Figure Studies based on such image fusions are undergoing in our group.

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Color-coded fused image for a breast with an infiltrating ductal carcinoma. CURE images are constructed from the same data, so they can be fused together without any geometric discrepancies. The third potential clinical application of UCT is to monitor clinical response of breast cancer patients to neo-adjuvant chemotherapy. Although chemotherapy is widely used to treat cancers, it is important to identify patients who are not responding to chemotherapy as early as possible, to avoid unsuccessful treatment strategies and unnecessary side effects Rousseau et al.

Accurate evaluation of a tumor's response to therapy is also necessary to plan for surgery Partridge et al. In an ongoing study, we have used CURE images to monitor the progress of chemotherapy for six patients. CURE exams were performed at each cycle of chemotherapy. The sound-speed distribution from each scan was reconstructed to track the change in size, shape and mean sound-speed of the tumor.

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Compared with MRI, a significant potential advantage of using our sound-speed tomograms for chemotherapy monitoring is the low cost for both patients and health care providers. Again, the greater potential accuracy of sound-speed measurements with the TV bent-ray algorithm and the ability to increase the contrast over the background makes this a more feasible procedure which could easily be automated and compared for patients at each follow-up visit over time. The time resolution was 2 weeks. The large mass is in the 2 o'clock position and shows dramatic shrinkage over time.

There are several limitations in our study.

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First, the performance of our tomography algorithm declined when the lesion size dropped to and below the elevation beam width 5 mm for our ring array , since the signal dilution led to a loss of contrast. Another important factor influencing the performance of our algorithm is the signal-to-noise ratio of the acquired patient data. Showing of 1 reviews. Top Reviews Most recent Top Reviews. There was a problem filtering reviews right now.

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Compared with conventional B-mode imaging, there are a few advantages for ultrasound transmission imaging tomography: There are basically two types of UCT methods. The first is based on ray theory, which is fast and stable. The second applies inverse scattering principles, which are much more time consuming but have higher resolution Devaney , ; Johnson et al.

For ray-theory based breast UCT, there are primarily two modes. The first mode uses the time-of-flight measurements of the transmission US signals to reproduce the sound-speed distribution within the breast. The second mode reconstructs attenuation measurements to give a distribution of energy absorption and scatter within the breast. Our study focuses on the first mode to improve the quality of UCT by overcoming the shortcomings of previous noniterative straight-ray mathematical models, thereby making it more clinically acceptable for in vivo breast imaging.

Based on Fermat's Principle and Snell's Law, the ultrasound ray path in an inhomogeneous medium such as breast tissue is not straight, which makes the inverse problem nonlinear. The first bent-ray ultrasound tomography was proposed by Schomberg in Schomberg However, applications of bent-ray algorithm were limited to numerical simulations and phantom studies thereafter Norton ; Andersen , Since most abnormal breast lesions have higher sound-speed than normal breast tissue Gauss et al.

Therefore, a robust ultrasound sound-speed tomography algorithm is critical to ensure a high-resolution sound-speed tomogram of the breast data. In this study, we present an iterative bent-ray ultra-sound tomography method to extract sound-speed information from in vivo ultrasound breast data acquired by CURE. We investigate the use of total-variation TV to regularize the uneven ray coverage, which leads to a non-quadratic minimization problem.

The TV method was introduced by Rudin et al.