Mammographic Density and Prediction of Nodal Status in Breast Cancer Patients

Abstract

!Aim: Nodal status remains one of the most important prognostic factors in breast cancer. The cellular and molecular reasons for the spread of tumor cells to the lymph nodes are not well understood and there are only few predictors in addition to tumor size and multifocality that give an insight into additional mechanisms of lymphatic spread. Aim of our study was therefore to investigate whether breast characteristics such as mammographic density (MD) add to the predictive value of the presence of lymph node metastases in patients with primary breast cancer. Methods: In this retrospective study we analyzed primary, metastasis-free breast cancer patients from one breast center for whom data on MD and staging information were available. A total of 1831 patients were included into this study. MD was assessed as percentage MD (PMD) using a semiautomated method and two readers for every patient. Multiple logistic regression analyses with nodal status as outcome were used to investigate the predictive value of PMD in addition to age, tumor size, Ki-67, estrogen receptor (ER), progesterone receptor (PR), grading, histology, and multi-focality. Results: Multifocality, tumor size, Ki-67 and grading were relevant predictors for nodal status. Adding PMD to a prediction model which included these factors did not significantly improve the prediction of nodal status (p = 0.24, likelihood ratio test). Conclusion: Nodal status could be predicted quite well with the factors multifocality, tumor size, Ki-67 and grading. PMD does not seem to play a role in the lymphatic spread of tumor cells. It could be concluded that the amount of extracellular matrix and stromal cell content of the breast which is reflected by MD does not influence the probability of malignant breast cells spreading from the primary tumor to the lymph nodes. Zusammenfassung

A preoperative prediction model for sentinel lymph node status using artificial intelligence on mammographic images and clinicopathological variables in patients with clinically node-negative breast cancer

“…In this material we observed that decreasing radiologic tumor size was associated with N0 status. Pathological tumor size is a strong predictor for SLN status and often included in prediction models, although it is a postoperative variable [10,19,20]. These and previous results indicate that mammographic tumor size could replace pathological tumor size assessed from the surgical specimen as a predictor for N0 status.…”

“…Yang et al [21] created a prediction model for ALN status using a radiomic signature on mammography (n=147) and with an AUC of 0.88 in the validation cohort, indicating a promising predictive capacity of mammographic features for N0 status. A study by Hack et al [20] evaluated mammographic density and postoperative clinicopathological variables for prediction of N0 status. No association was discovered between mammographic density and SLN status, similar to our ndings.…”

“…Prediction models for ALN status using mammographic images have previously been presented, using the presence of microcalci cations, breast density, and radiomic signatures, exclusively or in combination with clinicopathological variables, most of which were postoperatively captured [19][20][21][22]. Several other imaging modalities have been assessed for their nodal predictive value, such as contrast-enhanced computed tomography (CECT), magnetic resonance imaging (MRI) and ultrasound [23][24][25][26][27].…”

Predicting mammographic density with linear ultrasound transducers

“…The following methodology was used in several previous works [ 4 , 6 , 7 , 10 , 13 , 30 , 31 , 45 , 47 – 50 ]. Quantitative computer-based threshold density assessments were carried out by two different readers.…”

Mammographic density and prognosis in primary breast cancer patients

“…Some studies have reported that MD affects the prognosis of BC patients [16,17], and MD has been found to correlate with tumor proliferation in several subgroups [18,19]. However other studies did not show a correlation between MD and Prognosis [20e23] and further no association was found between MD and lymph node metastases [24].…”