In vivo breast sound-speed imaging with ultrasound tomography

We discuss a bent-ray ultrasound tomography algorithm with total-variation (TV) regularization. We have applied this algorithm to 61 in vivo breast datasets collected with our in-house clinical prototype for imaging sound-speed distributions in the breast. Our analysis showed that TV regularization could preserve sharper lesion edges than the classic Tikhonov regularization. Furthermore, the image quality of our TV bent-ray sound-speed tomograms was superior to that of the straight-ray counterparts for all types of breasts within BI-RADS density categories 1-4. For all four breast types from fatty to dense, the improvements for average sharpness (in the unit of (m{center_dot} s) {sup -1}) of lesion edges in our TV bent-ray tomograms are between 2.1 to 3.4 fold compared to the straight ray tomograms. Reconstructed sound-speed tomograms illustrated that our algorithm could successfully image fatty and glandular tissues within the breast. We calculated the mean sound-speed values for fatty tissue and breast parenchyma as 1422 {+-} 9 mls (mean{+-} SD) and1487 {+-} 21 mls, respectively. Based on 32 lesions in a cohort of 61 patients, we also found that the mean sound-speed for malignant breast lesions (1548{+-}17 mls) was higher, on average, than that of benign ones (1513{+-}27 mls) (one-sided p<O.OOl). These results suggest that, clinically, sound-speed tomograms can be used to assess breast density (, and therefore, breast cancer risk), as well as detect and help differentiate breast lesions. Finally, our sound-speed tomograms may also be a useful tool to monitor clinical response of breast cancer patients to neo-adjuvant chemotherapy