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 through 4. Our analysis showed that the improvements for average sharpness (in the unit of (m x s)(-1)) of lesion edges in our TV bent-ray tomograms are between 2.1 to 3.4-fold compared with 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 m/s (mean +/- SD) and 1487 +/- 21 m/s, 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 m/s) was higher, on average, than that of benign ones (1513 +/- 27 m/s) (one-sided p<0.001). 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 the clinical response of breast cancer patients to neo-adjuvant chemotherapy.
Li
Cuiping
C
Karmanos Cancer Institute, Hudson-Webber Cancer Research Center, Detroit, MI 48201, USA. lic@karmanos.org
Duric
Nebojsa
N
Littrup
Peter
P
Huang
Lianjie
L
D000328:Adult; D000465:Algorithms; D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D018270:Carcinoma, Ductal, Breast / Q000000981:diagnostic imaging; D015331:Cohort Studies; D003937:Diagnosis, Differential; D005260:Female; D018226:Fibroadenoma / Q000000981:diagnostic imaging; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D008875:Middle Aged; D018579:Patient Selection; D019047:Phantoms, Imaging; D014054:Tomography / Q000295:instrumentation / Q000379:methods; D016217:Ultrasonography, Mammary / Q000295:instrumentation / Q000379:methods