This PDF file contains the front matter associated with SPIE Proceedings Volume 11944, including the Title Page, Copyright information, Table of Contents, and Conference Committee listings.

In this retrospective study, we evaluated imaging data from 65 breast cancer patients that were obtained one to three days before the initiation of neoadjuvant chemotherapy (NAC). Imaging was performed with a dynamic optical tomography breast imaging system (DOTBIS) over the course of a breath hold. From this imaging data, we extracted time-dependent signal traces of the total hemoglobin in the whole volume of the tumor-bearing breast. The inflection point and the slope at the steepest part of the curve were calculated for both the ascending (patient holds her breath) and descending slopes (patient releases her breath and starts breathing normally again). Our results show statistically significant differences in vascular changes between patients with a pathologic complete response (pCR) and non-pCR patients. This suggests that differences in the tumor-bearing breasts of these two patient groups exist even before treatment is started.

This work evaluates changes in features of 3D breast images generated by a so-called dynamic optical tomographic imaging system (DOTBIS) during neoadjuvant chemotherapy (NAC). Images from 23 breast cancer patients were analyzes and correlated with respect to treatment outcome and status of hormone receptors and human epidermal growth factor receptors. Our data shows that the ratio of the mean value of deoxy-hemoglobin (ctHHb_N) at two weeks after the first treatment compared to baseline was statistically significantly lower in patients that achieve a pathologic complete response (pCR) (0.77 ± 0.22) as compared to patients with a non-pCR (1.14 ± 0.24, P < .005). These observations indicate that early changes in DOTBIS images can potentially be used to predict breast cancer response to NAC and may allow a better way to customize therapy to HR+/HER2- patients in order to optimize treatment.

In this work we will discuss novel tools for label-free subcellular dynamic imaging. We will explore dynamics using two orthogonal modalities: First, we will look at dynamic information derived from refractive index fluctuations using an emerging 3D quantitative phase imaging methods called quantitative oblique back illumination microscopy (qOBM). Next, we will look at dynamic information derived from the excitation coefficient of endogenous biomolecules in cells using multi-spectral deep-UV microscopy. Dynamics at multiple time-scales will be explored and their unique attributes and applications in biomedicine will be discussed.

Hypofractionated stereotactic body radiotherapy treatments (SBRT) have improved patient treatment outcomes. Extensive studies were performed investigating how vascular changes during treatment affect its efficacy. Unfortunately, histology is unable to perform non-invasive longitudinal assessments by directly measuring blood perfusion. Here, we present a novel preclinical theranostic μCT-guided irradiator/Fluorescence Molecular Imager, designed to perform a fast, non-invasive, and longitudinal assessment of tumor vascular response (TVR) to targeted radiotherapy. Our technique allows rapid assessment of spatiotemporal differences in indocyanine green (ICG) kinetics in tumors using principal component (PC) analysis, before and after tumor irradiation. Results show that changes were observed in the normalized first and second PC feature pixel values (p=0.0559, 0.0432 paired t-test). Moreover, we implemented a fast PC-based classification algorithm that yields spatially-resolved TVR maps. Our first-of-its-kind theranostic system, allowing automated assessment of TVR to SBRT, will be used to better understand the role of tumor perfusion in metastasis and tumor control.

Glioblastoma is the most malignant and common high-grade brain tumor with a 14-month overall survival length. According to recent World Health Organization Central Nervous System tumor classification (2021), the diagnosis of glioblastoma requires extensive molecular genetic tests in addition to the traditional histopathological analysis of Formalin- Fixed Paraffin-Embedded (FFPE) tissues. Time-consuming and expensive molecular tests as well as the need for clinical neuropathology expertise are the challenges in the diagnosis of glioblastoma. Hence, an automated and rapid analytical detection technique for identifying brain tumors from healthy tissues is needed to aid pathologists in achieving an errorfree diagnosis of glioblastoma in clinics. Here, we report on our clinical test results of Raman spectroscopy and machine learning-based glioblastoma identification methodology for a cohort of 20 glioblastoma and 18 white matter tissue samples. We used Raman spectroscopy to distinguish FFPE glioblastoma and white matter tissues applying our previously reported protocols about optimized FFPE sample preparation and Raman measurement parameters. One may analyze the composition and identify the subtype of brain tumors using Raman spectroscopy since this technique yields detailed molecule-specific information from tissues. We measured and classified the Raman spectra of neoplastic and non-neoplastic tissue sections using machine learning classifiers including support vector machine and random forest with 86.6% and 83.3% accuracies, respectively. These proof-of-concept results demonstrate that this technique might be eventually used in the clinics to assist pathologists once validated with a larger and more diverse glioblastoma cohort and improved detection accuracies.

Multispectral fluorescence imaging (MSFI) is a powerful imaging modality for tissue analysis and diagnostic imaging. By illuminating with distinct wavelengths of light, intrinsic biological fluorophores and labeled markers can be measured, providing information about tissue metabolism and function. MSFI has shown promise in the scope of gastrointestinal (GI) cancers such as colon and gastric cancers. Before MSFI can be used as an endoscopic diagnostic tool there requires extensive characterization of tissue properties to identify biomarker variations that occur with the onset of disease. A robust, whole organ imaging instrument to characterize autofluorescence properties would greatly inform the development of diagnostic imaging platforms. This paper reviews the design and validation of a multispectral fluorescence imaging system for characterizing whole organ tissue fluorescence and reflectance properties. We present a detailed discussion on design considerations and demonstrate excellent performance suitable to detect tissue autofluorescence.

In this work, we present a rapid scanning approach to fluorescence-detected two-dimensional electronic spectroscopy (FD-2DES). Our approach combines phase modulation with digital lock-in detection. Using phasemodulation each of the four pulses used to excite the sample is tagged with a specific radio-frequency. The resulting fluorescence signal is thus modulated at different linear combinations of these frequencies. Digital lock-in detection is used to retrieve complex linear and non-linear spectroscopic signals in a single measurement. The approach allows simultaneous tracking of interferometric time delays, correction of spectral phase distortions, and also enables accurate phasing of the data. We report the simultaneously acquired linear fluorescence excitation spectrum, rephasing, non-rephasing, and absorptive FD-2DES spectra of the laser dye IR-140 in DMSO.

Oxygenation and blood flow are important biomarkers of tissue health and they play a vital role in diagnosis and monitoring of diseases in both clinical and basic science research. Diffuse optical instruments offer effective solutions for continuous monitoring of oxygen and blood flow because they are non-invasive, portable and use non-ionizing light. Traditionally, this requires use of two complementary instruments, Diffuse Optical Spectroscopy (DOS) for measuring oxygenation from tissue absorption coefficient (𝜇𝑎) and reduced scattering coefficient (μs′) and Diffuse Correlation Spectroscopy (DCS) for measuring blood flow index (F). These hybrid DOS and DCS instruments use collocated sources leading to issues like partial volume effects, increased cost, and size. Here, we propose a novel technique - Frequency Domain Diffuse Correlation Spectroscopy (FD-DCS) to overcome these issues. FD-DCS extends and generalizes DCS measurements to the frequency domain, measures a frequency dependent intensity autocorrelation function, which is fit to a frequency domain solution to the correlation diffusion equation for simultaneous estimation of static and dynamic tissue optical properties. We present experiment results validating the technique in tissue simulating liquid phantoms (intralipid + India ink + water) using a new prototype instrument. Specifically, we compare tissue optical properties of phantoms of different absorption and scattering coefficients measured with FD-DCS and commercial FD-DOS. Our results show successful estimation of 𝜇𝑎, 𝜇𝑠 and 𝐹 with minimal errors.

We present a new frequency-domain near-infrared spectroscopy method for extracting deep tissue information in heterogeneous tissues by interfering multiple intensity-modulated light sources. This method of structured interrogation (SI) can alter the spatial distribution of depth sensitivity, and therefore target different depths in the tissue. We found through analytical theory and a simulation study that SI has enhanced sensitivity to dynamic changes in deeper tissues and reduced sensitivity to superficial layers compared to multi-distance (MD) measurements. We also demonstrate that SI phase-only measurements are sufficient to accurately estimate optical properties.

The intracellular environment is crowded with diverse biomacrolecules (~80-400 mg/ml), likely affecting various biological processes such as protein folding, binding of small molecules, enzymatic activity, and pathological protein aggregation. As a model we have been using solutions of Ficoll, a highly branched polysaccharide, to mimic the environment. Besides its biomedical applications (e.g. blood separation), it has been used as a macromolecular crowder in studies of protein folding and stability, cell volume signaling, tissue engineering, and nanotransport. In this study, our goal is to identify and assess Raman spectral signatures associated with Ficoll molecules and Ficoll-Ficoll interactions for future investigations of crowding effects. In addition to the Raman peaks of water (~1640 cm^-1 and ~3200 cm^-1) and dissolved O₂ (~1556 cm-1) and N2 (~2331 cm-1) we identified a distinct Raman peak (~2900 cm^-1) in the 1500-3500 cm^-1 wavenumber range, which is associated with Ficoll and CH and CH₂ stretching modes. As the Ficoll concentration increases, the intensity of the Ficoll Raman peaks increases while the intensity of the water Raman peaks decreases, the latter likely due to reduction of water content. Further, we have applied the intensity correlation analysis (ICA) method to assess systematic changes of Raman spectra with Ficoll concentration (up to 1000 mg/ml). ICA indicates an overall linear trend over the full wavenumber range, but also shows closed loops that can be attributed to slight changes of the profiles of certain peaks. The results demonstrate ICA as a potential insightful tool for identifying Ficoll in chemical analysis of crowded biological samples.

Cancer remains among the leading causes of death in the United States. Early detection, classification and understanding of malignant cell proliferation and metastasis mechanisms are crucial for effective treatment. Current malignant cell studies largely rely on either invasive imaging techniques or invasive research protocols that hinder both speed and accuracy of cancer research. Here we are reporting successful imaging of cancer metastasis processes on a cellular level using Brillouin microspectroscopic imaging. In this research we are specifically presenting results of a non-invasive interrogation of elastic properties of 4T1 murine fibroblast cells in a spheroid model acquired with our custom-built confocal Brillouin microspectrometer. Spatial map of elastic properties was recorded for both interior and exterior regions of the 4T1 cell spheroid. We observed lower stiffness of cancer cells compared to cells from internal regions. In addition we observed the difference in stiffness values between cells exposed to challenging and normal environmental conditions. Our findings correlate well with prior published data, acquired with conventional biomechanical assessment techniques.

Time-response thermography after the application of a mild cold shock is considered a valuable diagnostic tool for breast tumor identification. The concept of this work is to estimate the depth of a malignant tumor based on the time-varying thermographic images after the applied cold shock. Specifically, the heat diffusion model is considered and a thorough numerical analysis reveals the significant temperature variation dependence to a malignant tumor existence. Then, the time-varying curves are approximated utilizing the powerful generalized pencil-of-function method, which leads to the robust extraction of the thermal time constant. The sensitivity of the latter is exceptional considering the detection of the tumor, while the deviation from the peak value provides a strong indication in terms of the tumor’s depth.