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.

An approach to acquire axial structural information at nanoscale is demonstrated. It is based on spectral encoding of spatial frequency principle to reconstruct the structural information about the axial profile of the three-dimensional (3D) spatial frequency for each image point. This approach overcomes the fundamental limitations of current optical techniques and provides nanoscale accuracy and sensitivity in characterizing axial structures. Numerical simulation and experimental results are presented.

Accurate detection of breast malignancy from histologically normal cells (“field effect”) has significant clinical implications in a broad base of breast cancer management, such as high-risk lesion management, personalized risk assessment, breast tumor recurrence, and tumor margin management. More accurate and clinically applicable tools to detect markers characteristic of breast cancer “field effect” that are able to guide the clinical management are urgently needed. We have recently developed a novel optical microscope, spatial-domain low-coherence quantitative phase microscopy, which extracts the nanoscale structural characteristics of cell nuclei (i.e., nuclear nano-morphology markers), using standard histology slides. In this proof-of-concept study, we present the use of these highly sensitive nuclear nano-morphology markers to identify breast malignancy from histologically normal cells. We investigated the nano-morphology markers from 154 patients with a broad spectrum of breast pathology entities, including normal breast tissue, non-proliferative benign lesions, proliferative lesions (without and with atypia), “malignant-adjacent” normal tissue, and invasive carcinoma. Our results show that the nuclear nano-morphology markers of “malignant-adjacent” normal tissue can detect the presence of invasive breast carcinoma with high accuracy and do not reflect normal aging. Further, we found that a progressive change in nuclear nano-morphology markers that parallel breast cancer risk, suggesting its potential use for risk stratification. These novel nano-morphology markers that detect breast cancerous changes from nanoscale structural characteristics of histologically normal cells could potentially benefit the diagnosis, risk assessment, prognosis, prevention, and treatment of breast cancer.

The development of accurate and clinically applicable tools to assess cancer risk is essential to define candidates to undergo screening for early-stage cancers at a curable stage or provide a novel method to monitor chemoprevention treatments. With the use of our recently developed optical technology—spatial-domain low-coherence quantitative phase microscopy (SL-QPM), we have derived a novel optical biomarker characterized by structure-derived optical path length (OPL) properties from the cell nucleus on the standard histology and cytology specimens, which quantifies the nano-structural alterations within the cell nucleus at the nanoscale sensitivity, referred to as nano-morphology marker. The aim of this study is to evaluate the feasibility of the nuclear nano-morphology marker from histologically normal cells, extracted directly from the standard histology specimens, to detect early-stage carcinogenesis, assess cancer risk, and monitor the effect of chemopreventive treatment. We used a well-established mouse model of spontaneous carcinogenesis—ApcMin mice, which develop multiple intestinal adenomas (Min) due to a germline mutation in the adenomatous polyposis coli (Apc) gene. We found that the nuclear nano-morphology marker quantified by OPL detects the development of carcinogenesis from histologically normal intestinal epithelial cells, even at an early pre-adenomatous stage (six weeks). It also exhibits a good temporal correlation with the small intestine that parallels the development of carcinogenesis and cancer risk. To further assess its ability to monitor the efficacy of chemopreventive agents, we used an established chemopreventive agent, sulindac. The nuclear nano-morphology marker is reversed toward normal after a prolonged treatment. Therefore, our proof-of-concept study establishes the feasibility of the SL-QPM derived nuclear nano-morphology marker OPL as a promising, simple and clinically applicable biomarker for cancer risk assessment and evaluation of chemopreventive treatment.

We demonstrate a novel approach for the real time visualization and quantification of the 3D spatial frequencies in an image domain. Our approach is based on the spectral encoding of spatial frequency principle and permits the formation of an image as a color map in which spatially separated spectral wavelengths correspond to the dominant 3D spatial frequencies of the object. We demonstrate that our approach can visualize and analyze the dominant axial internal structure for each image point in real time and with nanoscale sensitivity to structural changes. Computer modeling and experimental results of instantaneous color visualization and quantification of 3D structures of a model system and biological samples are presented.