Rajan K. Bista

Quantification of nanoscale nuclear refractive index changes during the cell cycle

Intrigued by our recent finding that the nuclear refractive index is significantly increased in malignant cells and histologically normal cells in clinical histology specimens derived from cancer patients, we sought to identify potential biological mechanisms underlying the observed phenomena. The cell cycle is an ordered series of events that describes the intervals of cell growth, DNA replication, and mitosis that precede cell division. Since abnormal cell cycles and increased proliferation are characteristic of many human cancer cells, we hypothesized that the observed increase in nuclear refractive index could be related to an abundance or accumulation of cells derived from cancer patients at a specific point or phase(s) of the cell cycle. Here we show that changes in nuclear refractive index of fixed cells are seen as synchronized populations of cells that proceed through the cell cycle, and that increased nuclear refractive index is strongly correlated with increased DNA content. We therefore propose that an abundance of cells undergoing DNA replication and mitosis may explain the increase in nuclear refractive index observed in both malignant and histologically normal cells from cancer patients. Our findings suggest that nuclear refractive index may be a novel physical parameter for early cancer detection and risk stratification.

Nuclear nano-morphology markers of histologically normal cells detect the “field effect” of breast cancer

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.

Tomographic imaging via spectral encoding of spatial frequency.

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.

Investigation of depth-resolved nanoscale structural changes in regulated cell proliferation and chromatin decondensation

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.

Spectral encoding of spatial frequency approach for characterization of nanoscale structures

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.

Real-time quantitative visualization of 3D structural information

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.

Correction of stain variations in nuclear refractive index of clinical histology specimens

For any technique to be adopted into a clinical setting, it is imperative that it seamlessly integrates with well-established clinical diagnostic workflow. We recently developed an optical microscopy technique-spatial-domain low-coherence quantitative phase microscopy (SL-QPM) that can extract the refractive index of the cell nucleus from the standard histology specimens on glass slides prepared via standard clinical protocols. This technique has shown great potential in detecting cancer with a better sensitivity than conventional pathology. A major hurdle in the clinical translation of this technique is the intrinsic variation among staining agents used in histology specimens, which limits the accuracy of refractive index measurements of clinical samples. In this paper, we present a simple and easily generalizable method to remove the effect of variations in staining levels on nuclear refractive index obtained with SL-QPM. We illustrate the efficacy of our correction method by applying it to variously stained histology samples from animal model and clinical specimens.

An insight into statistical refractive index properties of cell internal structure via low-coherence statistical amplitude microscopy.

Refractive index properties, especially at the nanoscale, have shown great potential in cancer diagnosis and screening. Due to the intrinsic complexity and weak refractive index fluctuation, the reconstruction of internal structures of a biological cell has been challenging. In this paper, we propose a simple and practical approach to derive the statistical properties of internal refractive index fluctuations within a biological cell with a new optical microscopy method – Low-coherence Statistical Amplitude Microscopy (SAM). We validated the capability of SAM to characterize the statistical properties of cell internal structures, which is described by numerical models of one-dimensional Gaussian random field. We demonstrated the potential of SAM in cancer detection with an animal model of intestinal carcinogenesis – multiple intestinal neoplasia mouse model. We showed that SAM-derived statistical properties of cell nuclear structures could detect the subtle changes that are otherwise undetectable by conventional cytopathology.

Spectral contrast imaging microscopy

We introduce a new technique, spectral contrast imaging microscopy (SCIM), for super-resolution microscopic imaging. Based on a novel contrast mechanism that encodes each local spatial frequency with a corresponding optical wavelength, SCIM provides a real-time high-resolution spectral contrast microscopic image with superior contrast. We show that two microscopic objects, separated by a distance smaller than the diffraction limit of the optical system, can be spatially resolved in the SCIM image as different colors. Results with numerical simulation and experiments using a high-resolution United States Air Force target are presented. The ability of SCIM for imaging biological cells is also demonstrated.

Using optical markers of nondysplastic rectal epithelial cells to identify patients with ulcerative colitis-associated neoplasia†

Background: Current surveillance guidelines for patients with long‐standing ulcerative colitis (UC) recommend repeated colonoscopy with random biopsies, which is time‐consuming, discomforting, and expensive. A less invasive strategy is to identify neoplasia by analyzing biomarkers from the more accessible rectum to predict the need for a full colonoscopy. The goal of this pilot study was to evaluate whether optical markers of rectal mucosa derived from a novel optical technique, partial‐wave spectroscopic microscopy (PWS), could identify UC patients with high‐grade dysplasia (HGD) or cancer (CA) present anywhere in their colon. Methods: Banked frozen nondysplastic mucosal rectal biopsies were used from 28 UC patients (15 without dysplasia and 13 with concurrent HGD or CA). The specimen slides were made using a touch prep method and underwent PWS analysis. We divided the patients into two groups: 13 as a training set and an independent 15 as a validation set. Results: We identified six optical markers, ranked by measuring the information gain with respect to the outcome of cancer. The most effective markers were selected by maximizing the cross‐validated training accuracy of a Naive Bayes classifier. The optimal classifier was applied to the validation data yielding 100% sensitivity and 75% specificity. Conclusions: Our results indicate that the PWS‐derived optical markers can accurately predict UC patients with HGD/CA through assessment of rectal epithelial cells. By aiming for high sensitivity, our approach could potentially simplify the surveillance of UC patients and improve overall resource utilization by identifying patients with HGD/CA who should proceed with colonoscopy.