Diagnosis of breast cancer using fluorescence and diffuse reflectance spectroscopy: a Monte-Carlo-model-based approach

Abstract

We explore the use of Monte-Carlo-model-based approaches for the analysis of fluorescence and diffuse reflectance spectra measured ex vivo from breast tissues. These models are used to extract the absorption, scattering, and fluorescence properties of malignant and nonmalignant tissues and to diagnose breast cancer based on these intrinsic tissue properties. Absorption and scattering properties, including β-carotene concentration, total hemoglobin concentration, hemoglobin saturation, and the mean reduced scattering coefficient are derived from diffuse reflectance spectra using a previously developed Monte Carlo model of diffuse reflectance. A Monte Carlo model of fluorescence described in an earlier manuscript was employed to retrieve the intrinsic fluorescence spectra. The intrinsic fluorescence spectra were decomposed into several contributing components, which we attribute to endogenous fluorophores that may present in breast tissues including collagen, NADH, and retinol/ vitamin A. The model-based approaches removes any dependency on the instrument and probe geometry. The relative fluorescence contributions of individual fluorescing components, as well as β-carotene concentration, hemoglobin saturation, and the mean reduced scattering coefficient display statistically significant differences between malignant and adipose breast tissues. The hemoglobin saturation and the reduced scattering coefficient display statistically significant differences between malignant and fibrous/benign breast tissues. A linear support vector machine classification using (1) fluorescence properties alone, (2) absorption and scattering properties alone, and (3) the combination of all tissue properties achieves comparable classification accuracies of 81 to 84% in sensitivity and 75 to 89% in specificity for discriminating malignant from nonmalignant breast tissues, suggesting each set of tissue properties are diagnostically useful for the discrimination of breast malignancy.

Highly Accurate Detection of Cancer In Situ with Intraoperative, Label-Free, Multimodal Optical Spectroscopy

“…IFS detects endogenous fluorophores, including enzymes, metabolic cofactors, amino acids, porphyrins, and structural proteins. IFS has been used to detect bronchopulmonary cancer (19), epithelial precancerous tissue (20), laryngeal cancer (21), and breast cancer (22). DRS provides information from tissue absorbers, including oxygenated and deoxygenated hemoglobin, lipids, water, cytochromes, and melanin (23)(24)(25).…”

Diagnosis of breast cancer using diffuse optical spectroscopy from 500 to 1600 nm: comparison of classification methods

“…7,8 Over the last decade, new tools have been developed to classify breast tissue and assess breast tissue margins based on optical spectroscopy techniques. [9][10][11][12][13][14][15][16][17][18][19][20][21][22] Bigio et al performed in vivo elastic scattering spectroscopy measurements between 350 and 750 nm to discriminate between 13 malignant and 59 nonmalignant breast tissue samples by applying artificial neural network (ANN) and hierarchical cluster analysis on the spectra yielding sensitivity-specificity of 69%-85% and 67%-79%, respectively. 9 This study also showed that the spectral features between 400 and 500 nm in adipose tissue are mainly dominated by β-carotene light absorption, however optical properties were not derived from the measured spectra.…”

Modified Wiener estimation of diffuse reflectance spectra from RGB values by the synthesis of new colors for tissue measurements

“…1,2 Diffuse reflectance spectra have been used to estimate the optical properties of tissues, 3 which can be correlated with several important biophysical and biochemical parameters, such as hemoglobin information, 2 tissue oxygenation, 2 and average nuclei size 4 in tissues for disease diagnoses. Nonetheless, one significant disadvantage of traditional diffuse reflectance spectroscopy is slow data acquisition when diffuse reflectance spectra at multiple locations are required due to the employment of fiber-optic probes, which can only perform optical measurements point by point.…”