Definitive diagnosis of malignancy is often challenging due to limited availability of human cell or tissue samples and morphological similarity with certain benign conditions. Our recently developed novel technology-spatial-domain low-coherence quantitative phase microscopy (SL-QPM)-overcomes the technical difficulties and enables us to obtain quantitative information about cell nuclear architectural characteristics with nanoscale sensitivity. We explore its ability to improve the identification of malignancy, especially in cytopathologically non-cancerous-appearing cells. We perform proof-of-concept experiments with an animal model of colorectal carcinogenesis-APC(Min) mouse model and human cytology specimens of colorectal cancer. We show the ability of in situ nanoscale nuclear architectural characteristics in identifying cancerous cells, especially in those labeled as "indeterminate or normal" by expert cytopathologists. Our approach is based on the quantitative analysis of the cell nucleus on the original cytology slides without additional processing, which can be readily applied in a conventional clinical setting. Our simple and practical optical microscopy technique may lead to the development of novel methods for early detection of cancer.

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A microscopy technique, spatial-domain low-coherence quantitative phase microscopy (SL-QPM) is proposed for speckle-free, quantitative phase imaging of subcellular structures with subnanometer sensitivity. We quantified, for the first time to our knowledge, the refractive index of the cell nuclei on original unmodified histology specimens. We demonstrate that the refractive index of cell nucleus is highly sensitive in detecting cancer, especially in histologically normal-appearing cells from cancer patients. Because this technique is sensitive and does not require special sample processing, it can be disseminated to all clinical settings.

Abstract:Three-dimensional optical tomographic imaging plays an important role in biomedical research and clinical applications. We introduce spectral tomographic imaging (STI) via spectral encoding of spatial frequency principle that not only has the capability for visualizing the three-dimensional object at sub-micron resolution but also providing spatially-resolved quantitative characterization of its structure with nanoscale accuracy for any volume of interest within the object. The theoretical basis and the proof-of-concept numerical simulations are presented to demonstrate the feasibility of spectral tomographic imaging.

We present depth-resolved spatial-domain low-coherence quantitative phase microscopy, a simple approach that utilizes coherence gating to construct a depth-resolved structural feature vector quantifying sub-resolution axial structural changes at different optical depths within the sample. We show that this feature vector is independent of sample thickness variation, and identifies nanoscale structural changes in clinically prepared samples. We present numerical simulations and experimental validation to demonstrate the feasibility of the approach. We also perform experiments using unstained cells to investigate the nanoscale structural changes in regulated cell proliferation through cell cycle and chromatin decondensation induced by histone acetylation.