Background: Barrett's esophagus (BE) affects up to 12 million Americans and confers an increased risk for development of esophageal adenocarcinoma (EAC). EAC is often fatal unless detected early. Given the high prevalence, high cost of surveillance and relatively low risk of most affected individuals, identification of high-risk patients for additional scrutiny, regular surveillance, or ablative therapy is crucial. The exploration of "field effect" by probing uninvolved esophageal mucosa to predict the risk of EAC has the potential as an improved surveillance and prevention strategy. In this study, we evaluate the ability of nuclear nano-architecture markers from normal squamous esophagus and gastric cardia to detect the "field effect" of esophageal dysplasia and EAC, and their response to endoscopic therapy. Methods: Patients with normal esophagus, gastroesophageal reflux, BE and EAC were eligible for enrollment. We performed endoscopic cytology brushings of the gastric cardia, ~1-2 cm below the gastroesophageal junction, and of the normal squamous esophageal mucosa at ~20 cm from the incisors and standard cytology slides were made using Thinprep method. Optical analysis was performed on the cell nuclei of cytologically normal-appearing epithelial cells. Results: The study cohort consisted of 128 patients. The nuclear nano-architecture markers detected the presence of esophageal dysplasia and EAC with statistical significance. The field effect does not exhibit a spatial dependence. These markers reverted toward normal in response to endoscopic therapy. Conclusions: Optical analysis of gastric cardia and upper squamous esophagus represents a potentially viable method to improve risk stratification and ease of surveillance of patients with Barrett's esophagus and to monitor the efficacy of ablative therapy.

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.

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.