Pathology evaluation of sentinel lymph nodes in breast cancer: protocol recommendations and rationale

Sentinel lymph nodes (SLN) are more likely to contain metastatic breast carcinoma than non-SLNs. The limited number of SLNs compared with an axillary dissection has prompted more comprehensive lymph node analysis increasing detection of micrometastases. National data show that many women previously classified node negative are now classified minimally node positive. As a result, our nodal classification and cancer staging have evolved to recognize the continuum of nodal tumor burden rather than a simplistic dichotomous stratification. It is quite clear that the more sections we evaluate from SLNs the more metastases we identify; however, it is impractical to expect the practicing pathologist to mount, stain, and microscopically examine every section through the SLN paraffin blocks. Despite recommendations from the College of American Pathologists and the American Society of Clinical Oncology, heterogeneity in the approach to SLN evaluation exists. What is needed is adherence to a standardized evaluation protocol. The most important aspect of the sentinel node examination is careful attention to slicing the SLN no thicker than 2.0 mm and correct embedding of the slices to assure we identify all macrometastases larger than 2.0 mm. A single section from blocks prepared in this manner will identify all macrometastases present but smaller metastases will be missed. The prognostic significance of these missed micrometastases is still being evaluated as we await SLN outcome studies. In the context of the new molecular classification of breast cancer, subgroups may be identified where detection of micrometastases has clinical significance. It is critical that both clinicians and pathologists understand there is a random component to micrometastasis distribution within the three-dimensional paraffin tissue blocks. If we ultimately adopt more comprehensive microscopic evaluation of SLNs, the candidate sampling strategies need to be carefully considered in the context of statistically valid sampling strategies.