Diffuse reflectance and fluorescence spectroscopy for breast conserving surgery.

Abstract

Purpose: The major challenge in breast conserving surgery is the high rates of re-excision due to positive resection margins. This study evaluates whether a combined diffuse reflectance spectroscopy (DRS) and laser induced intrinsic fluorescence spectroscopy (IFS) technique can differentiate breast tissue sample types, towards the development of an intraoperative margin assessment tool.

Methods: Breast tissue samples were collected from patients undergoing breast cancer surgery. A handheld DRS-IFS probe was used on the frozen thawed ex-vivo  breast samples to acquire spectral data. Machine learning classifiers were used to determine sensitivity, specificity, overall diagnostic accuracy, and the area under the curve (AUC) against "gold-standard" histopathology ground truth.

Results: 181 breast tissue samples from 138 patients were interrogated using DRS-IFS. All patients were female, with median age (range) of 56.8 (20-94) years The total number of spectra acquired was 18,349. Following five-fold cross validation for normal versus cancer tissue, extreme gradient boost classifier achieved a sensitivity of 84% (SD ± 13), specificity of 61% (SD ± 16), overall diagnostic accuracy of 75% (SD ± 3), and AUC of 84%.

Conclusion: The results suggests that DRS-IFS can distinguish normal breast tissue from breast cancer with high diagnostic accuracy. For DRS-IFS to be translated into the operating theatre to aid a surgeon's real-time visualisation for oncologic margin control assessment of intraoperative, the in vivo diagnostic accuracy needs to be determined.