Our group had previously established that nanoscale three-dimensional refractive index (RI) fluctuations of a linear, dielectric, label-free medium can be sensed in the far field through spectroscopic microscopy, regardless of the diffraction limit of optical microscopy. Adopting this technique, Partial Wave Spectroscopic (PWS) Microscopy was able to sense nanoarchitectural alterations in early-stage cancers. With the success of PWS on detecting cancer from healthy clinical samples, we further investigated whether and how histological staining can enhance the performance of PWS by both finite difference time domain (FDTD) simulations and experiments.
In this investigation, the dispersion models of hematoxylin and eosin were extracted from the absorption spectra of H and E stained cells. Using these models, the effect of staining were studied via FDTD simulations of unstained versus stained samples with various nanostructures. We observed that, the spectral variance was increased and the spectral variance difference between two samples with distinct nanostructures was enhanced in stained samples by over 200%. Furthermore, we investigated with FDTD whether molecule-specific staining can be used to enhance signals from a medium composing of the desired molecule. Samples with two mixed random media were created and the desired medium was either stained or unstained. Our results showed that the difference between the nanostructures of only the desired medium was enhanced in stained samples. We concluded that, with molecule-specific staining, PWS can selectively target the nanoarchitecture of a desired molecule. Lastly, these results were validated by experiments using human buccal cells from healthy or lung cancer patients.
This study has significant impact in improving the performance of PWS on quantifying nanoarchitectural alterations during cancer.
Many of the earliest structural changes associated with neoplasia occur on the micro and nanometer scale, and thus appear histologically normal. Our group has established Inverse Spectroscopic OCT (ISOCT), a spectral based technique to extract nanoscale sensitive metrics derived from the OCT signal. Thus, there is a need to model light transport through relatively large volumes (< 50 um^3) of media with nanoscale level resolution.
Finite Difference Time Domain (FDTD) is an iterative approach which directly solves Maxwell’s equations to robustly estimate the electric and magnetic fields propagating through a sample. The sample’s refractive index for every spatial voxel and wavelength are specified upon a grid with voxel sizes on the order of λ/20, making it an ideal modelling technique for nanoscale structure analysis.
Here, we utilize the FDTD technique to validate the nanoscale sensing ability of ISOCT. The use of FDTD for OCT modelling requires three components: calculating the source beam as it propagates through the optical system, computing the sample’s scattered field using FDTD, and finally propagating the scattered field back through the optical system. The principles of Fourier optics are employed to focus this interference field through a 4f optical system and onto the detector.
Three-dimensional numerical samples are generated from a given refractive index correlation function with known parameters, and subsequent OCT images and mass density correlation function metrics are computed. We show that while the resolvability of the OCT image remains diffraction limited, spectral analysis allows nanoscale sensitive metrics to be extracted.
Structural and biological origins of light scattering in cells and tissue are still poorly understood. We demonstrate how this problem might be addressed through the use of transmission electron microscopy (TEM). For biological samples, TEM image intensity is proportional to mass-density, and thus proportional to refractive index (RI). By calculating the autocorrelation function (ACF) of TEM image intensity of a thin-section of cells, we essentially maintain the nanoscale ACF of the 3D cellular RI distribution, given that the RI distribution is statistically isotropic. Using this nanoscale 3D RI ACF, we can simulate light scattering through biological samples, and thus guiding many optical techniques to quantify specific structures. In this work, we chose to use Partial Wave Spectroscopy (PWS) microscopy as a one of the nanoscale-sensitive optical techniques. Hela cells were prepared using standard protocol to preserve nanoscale ultrastructure, and a 50-nm slice was sectioned for TEM imaging at 6 nm resolution. The ACF was calculated for chromatin, and the PWS mean sigma was calculated by summing over the power spectral density in the visible light frequency of a random medium generated to match the ACF. A 1-µm slice adjacent to the 50-nm slice was sectioned for PWS measurement to guarantee identical chromatin structure. For 33 cells, we compared the calculated PWS mean sigma from TEM and the value measured directly, and obtained a strong correlation of 0.69. This example indicates the great potential of using TEM measured RI distribution to better understand the quantification of cellular nanostructure by optical methods.
Optical microscopy is the staple technique in the examination of microscale material structure in basic science and applied research. Of particular importance to biology and medical research is the visualization and analysis of the weakly scattering biological cells and tissues. However, the resolution of optical microscopy is limited to ≥200 nm due to the fundamental diffraction limit of light. We review one distinct form of the spectroscopic microscopy (SM) method, which is founded in the analysis of the second-order spectral statistic of a wavelength-dependent bright-field far-zone reflected-light microscope image. This technique offers clear advantages for biomedical research by alleviating two notorious challenges of the optical evaluation of biomaterials: the diffraction limit of light and the lack of sensitivity to biological, optically transparent structures. Addressing the first issue, it has been shown that the spectroscopic content of a bright-field microscope image quantifies structural composition of samples at arbitrarily small length scales, limited by the signal-to-noise ratio of the detector, without necessarily resolving them. Addressing the second issue, SM utilizes a reference arm, sample arm interference scheme, which allows us to elevate the weak scattering signal from biomaterials above the instrument noise floor.
Combining finite-difference time-domain (FDTD) methods and modeling of optical microscopy modalities, we previously developed an open-source software package called Angora, which is essentially a “microscope in a computer.” However, the samples being simulated were limited to nondispersive media. Since media dispersions are common in biological samples (such as cells with staining and metallic biomarkers), we have further developed a module in Angora to simulate samples having complicated dispersion properties, thereby allowing the synthesis of microscope images of most biological samples. We first describe a method to integrate media dispersion into FDTD, and we validate the corresponding Angora dispersion module by applying Mie theory, as well as by experimentally imaging gold microspheres. Then, we demonstrate how Angora can facilitate the development of optical imaging techniques with a case study.
Di Zhang, Taylor Graff, Susan Crawford, Hariharan Subramanian, Sebastian Thompson, Justin Derbas, Radha Lyengar, Hemant Roy, Charles Brendler, Vadim Backman
Prostate Cancer (PC) is the second leading cause of cancer deaths in American men. While prostate specific antigen (PSA) test has been widely used for screening PC, >60% of the PSA detected cancers are indolent, leading to unnecessary clinical interventions. An alternative approach, active surveillance (AS), also suffer from high expense, discomfort and complications associated with repeat biopsies (every 1-3 years), limiting its acceptance. Hence, a technique that can differentiate indolent from aggressive PC would attenuate the harms from over-treatment. Combining microscopy with spectroscopy, our group has developed partial wave spectroscopic (PWS) microscopy, which can quantify intracellular nanoscale organizations (e.g. chromatin structures) that are not accessible by conventional microscopy. PWS microscopy has previously been shown to predict the risk of cancer in seven different organs (N ~ 800 patients). Herein we use PWS measurement of label-free histologically-normal prostatic epithelium to distinguish indolent from aggressive PC and predict PC risk. Our results from 38 men with low-grade PC indicated that there is a significant increase in progressors compared to non-progressors (p=0.002, effect size=110%, AUC=0.80, sensitivity=88% and specificity=72%), while the baseline clinical characteristics were not significantly different. We further improved the diagnostic power by performing nuclei-specific measurements using an automated system that separates in real-time the cell nuclei from the remaining prostate epithelium. In the long term, we envision that the PWS based prognostication can be coupled with AS without any change to the current procedure to mitigate the harms caused by over-treatment.
The spectrum registered by a reflected-light bright-field spectroscopic microscope (SM) can quantify the microscopically indiscernible, deeply subdiffractional length scales within samples such as biological cells and tissues. Nevertheless, quantification of biological specimens via any optical measures most often reveals ambiguous information about the specific structural properties within the studied samples. Thus, optical quantification remains nonintuitive to users from the diverse fields of technique application. In this work, we demonstrate that the SM signal can be analyzed to reconstruct explicit physical measures of internal structure within label-free, weakly scattering samples: characteristic length scale and the amplitude of spatial refractive-index (RI) fluctuations. We present and validate the reconstruction algorithm via finite-difference time-domain solutions of Maxwell’s equations on an example of exponential spatial correlation of RI. We apply the validated algorithm to experimentally measure structural properties within isolated cells from two genetic variants of HT29 colon cancer cell line as well as within a prostate tissue biopsy section. The presented methodology can lead to the development of novel biophotonics techniques that create two-dimensional maps of explicit structural properties within biomaterials: the characteristic size of macromolecular complexes and the variance of local mass density.
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