IntroductionMammographic density is a strong, independent risk factor for breast cancer. A critical unanswered question is whether cancers tend to arise in mammographically dense tissue (i.e. are densities directly related to risk or are they simply a marker of risk). This question cannot be addressed by studying invasive tumors because they manifest as densities and cannot be confidently differentiated from the densities representing fibrous and glandular tissue. We addressed this question by studying ductal carcinoma in situ (DCIS), as revealed by microcalcifications.MethodWe studied the cranio-caudal and the mediolateral-oblique mammograms of 28 breasts with a solitary DCIS lesion. Two experienced radiologists independently judged whether the DCIS occurred in a mammographically dense area, and determined the density of different areas of the mammograms.ResultsIt was not possible to determine whether the DCIS was or was not in a dense area for six of the tumors. Of the remaining 22 lesions, 21 occurred in dense tissue (test for difference from expected taken as the percentage of density of the 'mammographic quadrant' containing DCIS; P < 0.0001). A preponderance of DCIS (17 out of 28) occurred in the mammographic quadrant with the highest percentage density.ConclusionDCIS occurs overwhelmingly in the mammographically dense areas of the breast, and pre-DCIS mammograms showed that this relationship was not brought about by the presence of the DCIS. This strongly suggests that some aspect of stromal tissue comprising the mammographically dense tissue directly influences the carcinogenic process in the local breast glandular tissue.

Our objective was to determine whether early change in standardized uptake values (SUVs) of 3′deoxy-3′-18F-fluorothymidine (18F-FLT) using PET with CT could predict pathologic complete response (pCR) of primary breast cancer to neoadjuvant chemotherapy (NAC). The key secondary objective was to correlate SUV with the proliferation marker Ki-67 at baseline and after NAC. Methods This prospective, multicenter phase II study did not specify the therapeutic regimen, thus, NAC varied among centers. All evaluable patients underwent 18F-FLT PET/CT at baseline (FLT1) and after 1 cycle of NAC (FLT2); 43 patients were imaged at FLT1, FLT2, and after NAC completion (FLT3). The percentage change in maximum SUV (%ΔSUVmax) between FLT1 and FLT2 and FLT3 was calculated for the primary tumors. The predictive value of ΔSUVmax for pCR was determined using receiver-operating-characteristic curve analysis. The correlation between SUVmax and Ki-67 was also assessed. Results Fifty-one of 90 recruited patients (median age, 54 y; stage IIA–IIIC) met the eligibility criteria for the primary objective analysis, with an additional 22 patients totaling 73 patients for secondary analyses. A pCR in the primary breast cancer was achieved in 9 of 51 patients. NAC resulted in a significant reduction in %SUVmax (mean Δ, 39%; 95% confidence interval, 31–46). There was a marginal difference in %ΔSUVmax_FLT1-FLT2 between pCR and no-pCR patient groups (Wilcoxon 1-sided P = 0.050). The area under the curve for ΔSUVmax in the prediction of pCR was 0.68 (90% confidence interval, 0.50–0.83; Delong 1-sided P = 0.05), with slightly better predictive value for percentage mean SUV (P = 0.02) and similar prediction for peak SUV (P = 0.04). There was a weak correlation with pretherapy SUVmax and Ki-67 (r = 0.29, P = 0.04), but the correlation between SUVmax and Ki-67 after completion of NAC was stronger (r = 0.68, P < 0.0001). Conclusion 18F-FLT PET imaging of breast cancer after 1 cycle of NAC weakly predicted pCR in the setting of variable NAC regimens. Posttherapy 18F-FLT uptake correlated with Ki-67 on surgical specimens. These results suggest some efficacy of 18F-FLT as an indicator of early therapeutic response of breast cancer to NAC and support future multicenter studies to test 18F-FLT PET in a more uniformly treated patient population.

We report here our studies of nuclear staining for the progesterone and estrogen receptors (PRA, PRB, ERalpha) and cell proliferation (MIB1) in the breast terminal duct lobular unit epithelium of 26 naturally cycling premenopausal women and 30 pregnant women (median 8.1 weeks gestation). Square root transformations of the PRA, PRB and ERalpha values, and a logarithmic transformation of the MIB1 values, were made to achieve more normal distributions of the values. PRA expression decreased from a mean of 17.8% of epithelial cells in cycling subjects to 6.2% in pregnant subjects (P = 0.013). MIB1 expression increased from 1.7% in cycling subjects to 16.0% in pregnant subjects (P < 0.001). PRB and ERalpha expression was slightly lower in pregnant subjects but the differences were not statistically significant. Sixteen of the non-pregnant subjects were nulliparous and ten were parous so that we had limited power to detect changes associated with parity. PRA was statistically significantly lower in parous women than in nulliparous women (32.2% in nulliparous women vs. 10.2%; P = 0.014). PRB (23.5 vs. 12.9%), ERalpha (14.4 vs. 8.6%) and MIB1 (2.2 vs. 1.2%) were also lower in parous women, but the differences were not statistically significant. The marked decreases in PRA in pregnancy and in parous women has also been found in the rat. A reduction in PRA expression may be a useful marker of the reduction in risk with pregnancy and may be of use in evaluating the effect of any chemoprevention regimen aimed at mimicking pregnancy. Short-term changes in PRA expression while the chemoprevention is being administered may be a more useful marker.

Dynamic contrast-enhanced (DCE) MRI provides both morphological and functional information regarding breast tumor response to neoadjuvant chemotherapy (NAC). The purpose of this retrospective study is to test if prediction models combining multiple MRI features outperform models with single features. Four features were quantitatively calculated in each MRI exam: functional tumor volume, longest diameter, sphericity, and contralateral background parenchymal enhancement. Logistic regression analysis was used to study the relationship between MRI variables and pathologic complete response (pCR). Predictive performance was estimated using the area under the receiver operating characteristic curve (AUC). The full cohort was stratified by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status (positive or negative). A total of 384 patients (median age: 49 y/o) were included. Results showed analysis with combined features achieved higher AUCs than analysis with any feature alone. AUCs estimated for the combined versus highest AUCs among single features were 0.81 (95% confidence interval [CI]: 0.76, 0.86) versus 0.79 (95% CI: 0.73, 0.85) in the full cohort, 0.83 (95% CI: 0.77, 0.92) versus 0.73 (95% CI: 0.61, 0.84) in HR-positive/HER2-negative, 0.88 (95% CI: 0.79, 0.97) versus 0.78 (95% CI: 0.63, 0.89) in HR-positive/HER2-positive, 0.83 (95% CI not available) versus 0.75 (95% CI: 0.46, 0.81) in HR-negative/HER2-positive, and 0.82 (95% CI: 0.74, 0.91) versus 0.75 (95% CI: 0.64, 0.83) in triple negatives. Multi-feature MRI analysis improved pCR prediction over analysis of any individual feature that we examined. Additionally, the improvements in prediction were more notable when analysis was conducted according to cancer subtype.