PURPOSE: To investigate the feasibility of using a limited number of multispectral transmission ultrasound images acquired with a novel full-field liquid crystal ultrasonic detector to estimate the sizes of cystic and malignant breast lesions. METHODS: In our prototype ultrasound imaging system, a high-resolution liquid crystal detector measures the intensity of the acoustic field transmitted through the compressed breast. Projection images can be acquired at multiple transducer frequencies with several monochromatic sources. Assuming normal breast parenchyma containing either a simple breast cyst or infiltrating duct carcinoma, image data acquired at two or more transducer frequencies can potentially be used to estimate the size of the lesion present. The presence of electronic Gaussian noise precludes an exact lesion thickness determination; the lesion thickness can only be estimated with some uncertainty. We have used estimation theory to derive the Cramer-Rao lower bound on the uncertainty of the thickness estimate for cystic and malignant lesions of variable sizes. RESULTS: For a 1-cm simple breast cyst and SNR of 50, an uncertainty in the estimated cyst thickness of 0.095 cm can be obtained using two transmission ultrasound breast images acquired with transducer frequencies of 5 and 5.508 MHz. For a malignant breast lesion of the same size and SNR of 50, an uncertainty in the lesion thickness estimate of 0.197 cm can be obtained using two breast images acquired with frequencies of 5 MHz and 5.462 MHz. In general, the lower bound on the precision of the thickness estimate is found to improve with increasing SNR and lesion size. CONCLUSION: For the cases considered, the Cramer-Rao lower bound on the uncertainty of the thickness estimate is significantly less than the actual lesion size. Furthermore, the precision of the thickness estimate can be improved by using lower transducer frequencies, although diffraction artifacts might then become prohibitive. Department of Defense (DOD) Breast Cancer Research Program IDEA Award W81XWH-11-1-0332.