Addition of tomosynthesis to digital mammography was associated with a decrease in recall rate and an increase in cancer detection rate. Further studies are needed to assess the relationship to clinical outcomes.

Purpose:To compare radiologists' diagnostic accuracy and recall rates for breast tomosynthesis combined with digital mammography versus digital mammography alone. Materials and Methods:Institutional review board approval was obtained at each accruing institution. Participating women gave written informed consent. Mediolateral oblique and craniocaudal digital mammographic and tomosynthesis images of both breasts were obtained from 1192 subjects. Two enriched reader studies were performed to compare digital mammography with tomosynthesis against digital mammography alone. Study 1 comprised 312 cases (48 cancer cases) with images read by 12 radiologists; study 2, 312 cases (51 cancer cases) with 15 radiologists. Study 1 readers recorded only that an abnormality requiring recall was present; study 2 readers had additional training and recorded both lesion type and location. Diagnostic accuracy was compared with receiver operating characteristic analysis. Recall rates of noncancer cases, sensitivity, specificity, and positive and negative predictive values determined by analyzing Breast Imaging Reporting and Data System scores were compared for the two methods. Results:Diagnostic accuracy for combined tomosynthesis and digital mammography was superior to that of digital mammography alone. Average difference in area under the curve in study 1 was 7.2% (95% confidence interval [CI]: 3.7%, 10.8%; P , .001) and in study 2 was 6.8% (95% CI: 4.1%, 9.5%; P , .001). All 27 radiologists increased diagnostic accuracy with addition of tomosynthesis. Recall rates for noncancer cases for all readers significantly decreased with addition of tomosynthesis (range, 6%-67%; P , .001 for 25 readers, P , .03 for all readers). Increased sensitivity was largest for invasive cancers: 15% and 22% in studies 1 and 2 versus 3% for in situ cancers in both studies. Conclusion:Addition of tomosynthesis to digital mammography offers the dual benefit of significantly increased diagnostic accuracy and significantly reduced recall rates for noncancer cases.q RSNA, 2012 Supplemental material: http://radiology.rsna.org/lookup /suppl

Three algorithms for breast tomosynthesis reconstruction were compared in this paper, including (1) a back-projection (BP) algorithm (equivalent to the shift-and-add algorithm), (2) a Feldkamp filtered back-projection (FBP) algorithm, and (3) an iterative Maximum Likelihood (ML) algorithm. Our breast tomosynthesis system acquires 11 low-dose projections over a 50 degree angular range using an a-Si (CsI:Tl) flat-panel detector. The detector was stationary during the acquisition. Quality metrics such as signal difference to noise ratio (SDNR) and artifact spread function (ASF) were used for quantitative evaluation of tomosynthesis reconstructions. The results of the quantitative evaluation were in good agreement with the results of the qualitative assessment. In patient imaging, the superimposed breast tissues observed in two-dimensional (2D) mammograms were separated in tomosynthesis reconstructions by all three algorithms. It was shown in both phantom imaging and patient imaging that the BP algorithm provided the best SDNR for low-contrast masses but the conspicuity of the feature details was limited by interplane artifacts; the FBP algorithm provided the highest edge sharpness for microcalcifications but the quality of masses was poor; the information of both the masses and the microcalcifications were well restored with balanced quality by the ML algorithm, superior to the results from the other two algorithms.

MRI appears to provide the best correlation with pathology-better than physical examination, mammography, and sonography-in patients undergoing neoadjuvant chemotherapy. However, MRI may overestimate (6%) or underestimate (23%) residual disease in approximately 29% of the patients (95% confidence interval, 14-48%).

We describe what is, to the best of our knowledge, the first pilot study of coregistered tomographic x-ray and optical breast imaging. The purpose of this pilot study is to develop both hardware and data processing algorithms for a multimodality imaging method that provides information that neither x-ray nor diffuse optical tomography (DOT) can provide alone. We present in detail the instrumentation and algorithms developed for this multimodality imaging. We also present results from our initial pilot clinical tests. These results demonstrate that strictly coregistered x-ray and optical images enable a detailed comparison of the two images. This comparison will ultimately lead to a better understanding of the relationship between the functional contrast afforded by optical imaging and the structural contrast provided by x-ray imaging.

Breast density is associated with reduced mammographic sensitivity and specificity. Additionally, increased tumor size and worsened prognosis are associated with increased breast density. 1,2 Dense breast tissue may also represent an independent risk factor for breast cancer. 3 Currently, 24 states have laws mandating that women be notified of the implications of breast density, thereby encouraging discussions between patients and physicians regarding the need for supplemental screening. 4 However, which, if any, additional modalities should be recommended for women with dense breasts is not known. Using data from our previous multicenter study, 5 we evaluated differential screening performance of digital mammography combined with tomosynthesis compared with digital mammography alone as a function of breast density.

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We use optical spectroscopy to characterize the influence of mammographic-like compression on the physiology of the breast. We note a reduction in total hemoglobin content, tissue oxygen saturation, and optical scattering under compression. We also note a hyperemic effect during repeated compression cycles. By modeling the time course of the tissue oxygen saturation, we are able to obtain estimates for the volumetric blood flow (1.64+/-0.6 mL/100 mL/min) and the oxygen consumption (1.97+/-0.6 micromol/100 mL/min) of compressed breast tissue. These values are comparable to estimates obtained from previously published positron emission tomography (PET) measurements. We conclude that compression-induced changes in breast physiological properties are significant and should be accounted for when performing optical breast imaging. Additionally, the dynamic characteristics of the changes in breast physiological parameters, together with the ability to probe the tissue metabolic state, may prove useful for breast cancer detection.