When accurate preoperative staging of the axilla is needed in patients with newly diagnosed invasive breast cancer, CNB is more sensitive than FNAB.

IntroductionApparent diffusion coefficient (ADC) values are increasingly reported in breast MRI. As there is no standardized method for ADC measurements, we evaluated the effect of the size of region of interest (ROI) to diagnostic utility and correlation to prognostic markers of breast cancer.MethodsThis prospective study was approved by the Institutional Ethics Board; the need for written informed consent for the retrospective analyses of the breast MRIs was waived by the Chair of the Hospital District. We compared diagnostic accuracy of ADC measurements from whole-lesion ROIs (WL-ROIs) to small subregions (S-ROIs) showing the most restricted diffusion and evaluated correlations with prognostic factors in 112 consecutive patients (mean age 56.2±11.6 years, 137 lesions) who underwent 3.0-T breast MRI.ResultsIntra- and interobserver reproducibility were substantial (κ = 0.616–0.784; Intra-Class Correlation 0.589–0.831). In receiver operating characteristics analysis, differentiation between malignant and benign lesions was excellent (area under curve 0.957–0.962, cut-off ADC values for WL-ROIs: 0.87×10−3 mm2s-1; S-ROIs: 0.69×10−3 mm2s-1, P<0.001). WL-ROIs/S-ROIs achieved sensitivities of 95.7%/91.3%, specificities of 89.5%/94.7%, and overall accuracies of 89.8%/94.2%. In S-ROIs, lower ADC values correlated with presence of axillary metastases (P = 0.03), high histological grade (P = 0.006), and worsened Nottingham Prognostic Index Score (P<0.05). In both ROIs, ADC values correlated with progesterone receptors and advanced stage (P<0.01), but not with HER2, estrogen receptors, or Ki-67.ConclusionsADC values assist in breast tumor characterization. Small ROIs were more accurate than whole-lesion ROIs and more frequently associated with prognostic factors. Cut-off values differed significantly depending on measurement procedure, which should be recognized when comparing results from the literature. Instead of using a whole lesion covering ROI, a small ROI could be advocated in diffusion-weighted imaging.

Increased uptake of glucose, a general hallmark of malignant tumors, leads to an accumulation of intermediate metabolites of glycolysis. We investigated whether the high supply of these intermediates promotes their flow into UDP-sugars, and consequently into hyaluronan, a tumor-promoting matrix molecule. We quantified UDP-N-Acetylglucosamine (UDP-GlcNAc) and UDP-glucuronic acid (UDP-GlcUA) in human breast cancer biopsies, the levels of enzymes contributing to their synthesis, and their association with the hyaluronan accumulation in the tumor. The content of UDP-GlcUA was 4 times, and that of UDP-GlcNAc 12 times higher in the tumors as compared to normal glandular tissue obtained from breast reductions. The surge of UDP-GlcNAc correlated with an elevated mRNA expression of glutamine-fructose-6-phosphate aminotransferase 2 (GFAT2), one of the key enzymes in the biosynthesis of UDP-GlcNAc, and the expression of GFAT1 was also elevated. The contents of both UDP-sugars strongly correlated with tumor hyaluronan levels. Interestingly, hyaluronan content did not correlate with the mRNA levels of the hyaluronan synthases (HAS1-3), thus emphasizing the role of the UDP-sugar substrates of these enzymes. The UDP-sugars showed a trend to higher levels in ductal vs. lobular cancer subtypes. The results reveal for the first time a dramatic increase of UDP-sugars in breast cancer, and suggest that their high supply drives the accumulation of hyaluronan, a known promoter of breast cancer and other malignancies. In general, the study shows how the disturbed glucose metabolism typical for malignant tumors can influence cancer microenvironment through UDP-sugars and hyaluronan.

• Percentile mammographic breast density was associated with patient prognosis. • Very low density proved to be an independent poor prognostic factor. • Only patients with densities <10% displayed this difference in survival. • Mammographic breast density was inversely associated with histological tumour grade.