Light scattering measured with spatial frequency domain imaging can predict stromal versus epithelial proportions in surgically resected breast tissue

Abstract. This study aims to determine if light scatter parameters measured with spatial frequency domain imaging (SFDI) can accurately predict stromal, epithelial, and adipose fractions in freshly resected, unstained human breast specimens. An explicit model was developed to predict stromal, epithelial, and adipose fractions as a function of light scattering parameters, which was validated against a quantitative analysis of digitized histology slides for N  =  31 specimens using leave-one-out cross-fold validation. Specimen mean stromal, epithelial, and adipose volume fractions predicted from light scattering parameters strongly correlated with those calculated from digitized histology slides (r  =  0.90, 0.77, and 0.91, respectively, p-value <1  ×  10  −  6). Additionally, the ratio of predicted epithelium to stroma classified malignant specimens with a sensitivity and specificity of 90% and 81%, respectively, and also classified all pixels in malignant lesions with 63% and 79%, at a threshold of 1. All specimens and pixels were classified as malignant, benign, or fat with 84% and 75% accuracy, respectively. These findings demonstrate how light scattering parameters acquired with SFDI can be used to accurately predict and spatially map stromal, epithelial, and adipose proportions in fresh unstained, human breast tissue, and suggest that these estimations could provide diagnostic value.

[1]  M Fitzmaurice,et al.  Endoscopic detection of dysplasia in patients with Barrett's esophagus using light-scattering spectroscopy. , 2000, Gastroenterology.

[2]  Ara Darzi,et al.  Diagnostic Accuracy of Intraoperative Techniques for Margin Assessment in Breast Cancer Surgery: A Meta-analysis , 2017, Annals of surgery.

[3]  Lawrence D. True,et al.  Light-sheet microscopy for slide-free non-destructive pathology of large clinical specimens , 2017, Nature Biomedical Engineering.

[4]  Stephanie A. Kennedy,et al.  Rapid noninvasive optical imaging of tissue composition in breast tumor margins. , 2009, American journal of surgery.

[5]  J. Schmitt,et al.  Optical scattering properties of soft tissue: a discrete particle model. , 1998, Applied optics.

[6]  Vadim Backman,et al.  Nonscalar elastic light scattering from continuous random media in the Born approximation. , 2009, Optics letters.

[7]  Chi Zhang,et al.  Fast label-free multilayered histology-like imaging of human breast cancer by photoacoustic microscopy , 2017, Science Advances.

[8]  Ji Yi,et al.  Structural length-scale sensitivities of reflectance measurements in continuous random media under the Born approximation. , 2012, Optics letters.

[9]  Sylvain Gioux,et al.  Ultrafast optical property map generation using lookup tables. , 2016, Journal of biomedical optics.

[10]  Nathan D. Shemonski,et al.  Real-time Imaging of the Resection Bed Using a Handheld Probe to Reduce Incidence of Microscopic Positive Margins in Cancer Surgery. , 2015, Cancer research.

[11]  Scott C Davis,et al.  Topical dual-stain difference imaging for rapid intra-operative tumor identification in fresh specimens. , 2013, Optics letters.

[12]  Venkataramanan Krishnaswamy,et al.  Scatter Spectroscopic Imaging Distinguishes between Breast Pathologies in Tissues Relevant to Surgical Margin Assessment , 2012, Clinical Cancer Research.

[13]  Zachary T. Harmany,et al.  Microscopy with ultraviolet surface excitation for rapid slide-free histology , 2017, Nature Biomedical Engineering.

[14]  Venkataramanan Krishnaswamy,et al.  Structured light scatteroscopy , 2014, Journal of biomedical optics.

[15]  Anthony J. Durkin,et al.  Modulated imaging: quantitative analysis and tomography of turbid media in the spatial-frequency domain. , 2005, Optics letters.

[16]  Tianheng Wang,et al.  Optical scattering coefficient estimated by optical coherence tomography correlates with collagen content in ovarian tissue. , 2011, Journal of biomedical optics.

[17]  B. Pogue,et al.  Wide‐field color imaging of scatter‐based tissue contrast using both high spatial frequency illumination and cross‐polarization gating , 2018, Journal of biophotonics.

[18]  C. Depeursinge,et al.  Monte Carlo study of diffuse reflectance at source–detector separations close to one transport mean free path , 1999 .

[19]  Angela A. Eick,et al.  Mechanisms of light scattering from biological cells relevant to noninvasive optical-tissue diagnostics. , 1998, Applied optics.

[20]  M. Takeda,et al.  Total-circumference intraoperative frozen section analysis reduces margin-positive rate in breast-conservation surgery. , 2010, Japanese journal of clinical oncology.

[21]  A. Ruifrok,et al.  Quantification of histochemical staining by color deconvolution. , 2001, Analytical and quantitative cytology and histology.

[22]  Venkataramanan Krishnaswamy,et al.  Sub-diffusive scattering parameter maps recovered using wide-field high-frequency structured light imaging. , 2014, Biomedical optics express.

[23]  Johannes E. Schindelin,et al.  Fiji: an open-source platform for biological-image analysis , 2012, Nature Methods.

[24]  G. Zonios,et al.  Diffuse reflectance spectroscopy of human adenomatous colon polyps in vivo. , 1999, Applied optics.

[25]  Michael S. Feld,et al.  Imaging human epithelial properties with polarized light-scattering spectroscopy , 2001, Nature Medicine.

[26]  Nimmi Ramanujam,et al.  Correlation of breast tissue histology and optical signatures to improve margin assessment techniques , 2016, Journal of biomedical optics.

[27]  Christian Depeursinge,et al.  Physical interpretation of the phase function related parameter γ studied with a fractal distribution of spherical scatterers. , 2010, Optics express.

[28]  R. Pleijhuis,et al.  Obtaining Adequate Surgical Margins in Breast-Conserving Therapy for Patients with Early-Stage Breast Cancer: Current Modalities and Future Directions , 2009, Annals of Surgical Oncology.

[29]  R. Chuttani,et al.  Light scattering spectroscopy identifies the malignant potential of pancreatic cysts during endoscopy , 2017, Nature Biomedical Engineering.

[30]  Brian W Pogue,et al.  Wide-field quantitative imaging of tissue microstructure using sub-diffuse spatial frequency domain imaging. , 2016, Optica.

[31]  Anthony J. Durkin,et al.  Quantitation and mapping of tissue optical properties using modulated imaging. , 2009, Journal of biomedical optics.

[32]  James G. Fujimoto,et al.  Assessment of breast pathologies using nonlinear microscopy , 2014, Proceedings of the National Academy of Sciences.

[33]  Bernard Choi,et al.  Visible spatial frequency domain imaging with a digital light microprojector , 2013, Journal of biomedical optics.

[34]  I J Bigio,et al.  Spectroscopic diagnosis of bladder cancer with elastic light scattering , 1995, Lasers in surgery and medicine.

[35]  Xin Wang,et al.  Phase contrast microscopy analysis of breast tissue: differences in benign vs. malignant epithelium and stroma. , 2009, Analytical and quantitative cytology and histology.

[36]  Philip Wijesinghe,et al.  Wide-field optical coherence micro-elastography for intraoperative assessment of human breast cancer margins. , 2016, Biomedical optics express.

[37]  P Jack Hoopes,et al.  Monochromatic subdiffusive spatial frequency domain imaging provides in-situ sensitivity to intratumoral morphological heterogeneity in a murine model. , 2017, Journal of biophotonics.

[38]  Venkataramanan Krishnaswamy,et al.  Spectral discrimination of breast pathologies in situ using spatial frequency domain imaging , 2013, Breast Cancer Research.

[39]  Brian W Pogue,et al.  Approximation of Mie scattering parameters in near-infrared tomography of normal breast tissue in vivo. , 2005, Journal of biomedical optics.

[40]  Irving J Bigio,et al.  Wavelength-dependent backscattering measurements for quantitative real-time monitoring of apoptosis in living cells. , 2009, Journal of biomedical optics.

[41]  M. Sughayer,et al.  Reliability of frozen section in breast sentinel lymph node examination , 2014, Breast Cancer.

[42]  R R Alfano,et al.  Fractal mechanisms of light scattering in biological tissue and cells. , 2005, Optics letters.

[43]  James V. Little,et al.  Detection of Head and Neck Cancer in Surgical Specimens Using Quantitative Hyperspectral Imaging , 2017, Clinical Cancer Research.