Label-free quantitative evaluation of breast tissue using Spatial Light Interference Microscopy (SLIM)

Abstract

Breast cancer is the most common type of cancer among women worldwide. The standard histopathology of breast tissue, the primary means of disease diagnosis, involves manual microscopic examination of stained tissue by a pathologist. Because this method relies on qualitative information, it can result in inter-observer variation. Furthermore, for difficult cases the pathologist often needs additional markers of malignancy to help in making a diagnosis, a need that can potentially be met by novel microscopy methods. We present a quantitative method for label-free breast tissue evaluation using Spatial Light Interference Microscopy (SLIM). By extracting tissue markers of malignancy based on the nanostructure revealed by the optical path-length, our method provides an objective, label-free and potentially automatable method for breast histopathology. We demonstrated our method by imaging a tissue microarray consisting of 68 different subjects −34 with malignant and 34 with benign tissues. Three-fold cross validation results showed a sensitivity of 94% and specificity of 85% for detecting cancer. Our disease signatures represent intrinsic physical attributes of the sample, independent of staining quality, facilitating classification through machine learning packages since our images do not vary from scan to scan or instrument to instrument.

Variational Hilbert Quantitative Phase Imaging

“…www.nature.com/scientificreports/ -in cell/tissue biology: ODT (stem cells) 17 , SLIM 14 , Hilbert phase microscopy HPM 18 , transport of intensity equation 19 , Fourier ptychography 20 , quadriwave lateral shearing interferometry QLSI 21,22 , gradient light interference microscopy GLIM 23 , Hilbert-Huang phase microscopy H2PM 24 , flow cytometry 25 ; -in cancer diagnosis: DHM 26 , SLIM 27 , diffraction phase microscopy DPM 28,29 , to name only a representative number of approaches.…”

Imaging Collagen Properties in the Uterosacral Ligaments of Women With Pelvic Organ Prolapse Using Spatial Light Interference Microscopy (SLIM)

“…QPI measures the optical pathlength (OPL) map associated with a sample as an intrinsic contrast mechanism, and, as a result, transparent biospecimens, such as cells and tissues, can be clearly visualized without concerns regarding exogenous staining. In the past decade, this label-free imaging field has quickly expanded and shown remarkable performance in many fields of research, such as cell biology [7][8][9][10], neuroscience [11,12], immunology [13], and more recently, clinical studies [14][15][16][17][18]. Since the OPL is essentially the product of refractive index difference and local thickness, the pixel values of a QPI image are not subject to settings of the instrument (e.g., camera exposure time and illumination intensity), nor the staining intensity.…”

Tissue spatial correlation as cancer marker

“…[12][13][14][15][16][17][18][19][20][21][22][23][24] By generating contrast, label-free QPI lends itself much more readily to automated image analysis than bright-field microscopy, since stain variation is no longer an issue. 13 In addition to the advantages of label-free imaging, the contrast mechanism in QPI provides access to additional markers of disease, which are of value to histopathology. 14,25 In particular, since QPI systems employ interferometric measurements, they are sensitive to subwavelength fluctuations in OPD in both space and time.…”