Objective

To develop an intraoperative method for margin status evaluation during breast conservation therapy (BCT) using an automated analysis of imprint cytology specimens.

Study Design

Imprint cytology samples were prospectively taken from 47 patients undergoing either BCT or breast reduction surgery. Touch preparations from BCT patients were taken on cut sections through the tumor to generate positive margin controls. For breast reduction patients, slide imprints were taken at cuts through the center of excised tissue. Analysis results from the presented technique were compared against standard pathologic diagnosis. Slides were stained with cytokeratin and Hoechst, imaged with an automated fluorescent microscope, and analyzed with a fast algorithm to automate discrimination between epithelial cells and noncellular debris.

Results

The accuracy of the automated analysis was 95% for identifying invasive cancers compared against final pathologic diagnosis. The overall sensitivity was 87% while specificity was 100% (no false positives). This is comparable to the best reported results from manual examination of intraoperative imprint cytology slides while reducing the need for direct input from a cytopathologist.

Conclusion

This work demonstrates a proof of concept for developing a highly accurate and automated system for the intraoperative evaluation of margin status to guide surgical decisions and lower positive margin rates.

Background

Breast conservation therapy is the standard treatment for breast cancer; however, 20–50% of operations have a positive margin leading to secondary procedures. The standard of care to evaluate surgical margins is based on permanent section. Imprint cytology (touch prep) has been used to evaluate surgical samples, but conventional techniques require an experienced cytopathologist for correct interpretation. An automated image screening process has been developed to discern cancer cells from normal epithelial cells. This technique is based on cellularity of the imprint specimen and does not require expertise in cytopathology.

Methods

A rapid immunofluorescent staining technique coupled with automated microscopy was used to classify specimens as cancer vs. noncancer based on the density of epithelial cells captured on touch prep of tumor cross-sections. The results of the automated analysis vs. a manual screen of ten 20× fields were compared to the pathology interpretation on permanent section.

Results

A total of 34 consecutive cases were analyzed: 10 normal cases, and 24 cancer cases. The cross-section specimens for invasive cancer were correctly classified in at least 65% of the cases by using manual microscopy and at least 83% by using automated microscopy. The manual and automated microscopy correlated well for measurements of epithelial cell density (R2 = 0.64); however, the automated microscopy was more accurate.

Conclusions

This preliminary study using an automated system for intraoperative interpretation does not require a cytopathologist and shows that rapid, low-resolution imaging can correctly identify cancer cells for invasive carcinoma in surgical specimens. Therefore, automated determination of cellularity in touch prep is a promising technique for future margin interpretation of breast conservation therapy.