Diagnostic power of diffuse reflectance spectroscopy for targeted detection of breast lesions with microcalcifications

• Published in: Proceedings of the National Academy of Sciences - PNAS Vol. 110; no. 2; pp. 471 - 476
• Main Authors: Soares, Jaqueline S., Barman, Ishan, Dingari, Narahara Chari, Volynskaya, Zoya, Liu, Wendy, Klein, Nina, Plecha, Donna, Dasari, Ramachandra R., Fitzmaurice, Maryann
• Format: Journal Article
• Language: English
• Published: United States National Academy of Sciences 08.01.2013; National Acad Sciences
• Subjects: Adult; Aged; Algorithms; Biological Sciences; Biopsies; Biopsy; Biopsy, Needle - methods; Breast cancer; Breast Neoplasms - diagnosis; Breast Neoplasms - pathology; Calcinosis - diagnosis; Calcinosis - pathology; Correlation analysis; Female; Humans; Lesions; Medical diagnosis; Middle Aged; Needle biopsies; Ohio; Optical reflection; Principal Component Analysis; Radiography; Raman scattering; Raman spectroscopy; Spectral reflectance; Spectroscopy; Spectrum Analysis - methods; Tissues; Ultraviolet reflection; Ohio
• ISSN: 0027-8424; 1091-6490
• DOI: 10.1073/pnas.1215473110

Microcalcifications geographically target the location of abnormalities within the breast and are of critical importance in breast cancer diagnosis. However, despite stereotactic guidance, core needle biopsy fails to retrieve microcalcifications in up to 15% of patients. Here, we introduce an approach based on diffuse reflectance spectroscopy for detection of microcalcifications that focuses on variations in optical absorption stemming from the calcified clusters and the associated cross-linking molecules. In this study, diffuse reflectance spectra are acquired ex vivo from 203 sites in fresh biopsy tissue cores from 23 patients undergoing stereotactic breast needle biopsies. By correlating the spectra with the corresponding radiographic and histologie assessment, we have developed a support vector machine-derived decision algorithm, which shows high diagnostic power (positive predictive value and negative predictive value of 97% and 88%, respectively) for diagnosis of lesions with microcalcifications. We further show that these results are robust and not due to any spurious correlations. We attribute our findings to the presence of proteins (such as elastin), and desmosine and isodesmosine cross-linkers in the microcalcifications. It is important to note that the performance of the diffuse reflectance decision algorithm is comparable to one derived from the corresponding Raman spectra, and the considerably higher intensity of the reflectance signal enables the detection of the targeted lesions in a fraction of the spectral acquisition time. Our findings create a unique landscape for spectroscopic validation of breast core needle biopsy for detection of microcalcifications that can substantially improve the likelihood of an adequate, diagnostic biopsy in the first attempt.