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Fetal membranes have important mechanical and antimicrobial roles in maintaining pregnancy. However, the small thickness (<800 µm) of fetal membranes places them outside the resolution limits of most ultrasound and magnetic resonance systems. Optical imaging methods like optical coherence tomography (OCT) have the potential to fill this resolution gap. Here, OCT and machine learning methods were developed to characterize the ex vivo properties of human fetal membranes under dynamic loading. A saline inflation test was incorporated into an OCT system, and tests were performed on n = 33 and n = 32 human samples obtained from labored and C-section donors, respectively. Fetal membranes were collected in near-cervical and near-placental locations. Histology, endogenous two photon fluorescence microscopy, and second harmonic generation microscopy were used to identify sources of contrast in OCT images of fetal membranes. A convolutional neural network was trained to automatically segment fetal membrane sub-layers with high accuracy (Dice coefficients >0.8). Intact amniochorion bilayer and separated amnion and chorion were individually loaded, and the amnion layer was identified as the load-bearing layer within intact fetal membranes for both labored and C-section samples, consistent with prior work. Additionally, the rupture pressure and thickness of the amniochorion bilayer from the near-placental region were greater than those of the near-cervical region for labored samples. This location-dependent change in fetal membrane thickness was not attributable to the load-bearing amnion layer. Finally, the initial phase of the loading curve indicates that amniochorion bilayer from the near-cervical region is strain-hardened compared to the near-placental region in labored samples. Overall, these studies fill a gap in our understanding of the structural and mechanical properties of human fetal membranes at high resolution under dynamic loading events., Competing Interests: The authors declare no conflicts of interest., (© 2023 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.)

Indocyanine green (ICG) is routinely used during surgery to stain the inner limiting membrane (ILM) and provide contrast on white light surgical microscopy. While translation of optical coherence tomography (OCT) for intraoperative imaging during ophthalmic surgery has enhanced visualization, the ILM remains difficult to distinguish from underlying retinal structures and ICG does not provide additional OCT contrast. We present photothermal OCT (PT-OCT) for high-specificity detection of ICG on retinal OCT images. We demonstrate our technique by performing an ILM peel in ex vivo eyes using low ICG concentrations and laser powers. These results establish the feasibility of PT-OCT for intraoperative guidance during retinal surgery.

Photothermal OCT (PT-OCT) is an emerging molecular imaging technique that occupies a spatial imaging regime between microscopy and whole body imaging. PT-OCT would benefit from a theoretical model to optimize imaging parameters and test image processing algorithms. We propose the first analytical PT-OCT model to replicate an experimental A-scan in homogeneous and layered samples. We also propose the PT-CLEAN algorithm to reduce phase-accumulation and shadowing, two artifacts found in PT-OCT images, and demonstrate it on phantoms and in vivo mouse tumors.

Fluorescence lifetime microscopy imaging (FLIM) is an optic technique that allows a quantitative characterization of the fluorescent components of a sample. However, for an accurate interpretation of FLIM, an initial processing step is required to deconvolve the instrument response of the system from the measured fluorescence decays. In this paper, we present a novel strategy for the deconvolution of FLIM data based on a library of exponentials. Our approach searches for the scaling coefficients of the library by non-negative least squares approximations plus Thikonov/l(2) or l(1) regularization terms. The parameters of the library are given by the lower and upper bounds in the characteristic lifetimes of the exponential functions and the size of the library, where we observe that this last variable is not a limiting factor in the resulting fitting accuracy. We compare our proposal to nonlinear least squares and global non-linear least squares estimations with a multi-exponential model, and also to constrained Laguerre-base expansions, where we visualize an advantage of our proposal based on Thikonov/l(2) regularization in terms of estimation accuracy, computational time, and tuning strategy. Our validation strategy considers synthetic datasets subject to both shot and Gaussian noise and samples with different lifetime maps, and experimental FLIM data of ex-vivo atherosclerotic plaques and human breast cancer cells.

Photothermal OCT (PTOCT) provides high sensitivity to molecular targets in tissue, and occupies a spatial imaging regime that is attractive for small animal imaging. However, current implementations of PTOCT require extensive temporal sampling, resulting in slow frame rates and a large data burden that limit its in vivo utility. To address these limitations, we have implemented optical lock-in techniques for photothermal optical lock-in OCT (poli-OCT), and demonstrated the in vivo imaging capabilities of this approach. The poli-OCT signal was assessed in tissue-mimicking phantoms containing indocyanine green (ICG), an FDA approved small molecule that has not been previously imaged in vivo with PTOCT. Then, the effects of in vivo blood flow and motion artifact were assessed and attenuated, and in vivo poli-OCT was demonstrated with both ICG and gold nanorods as contrast agents. Experiments revealed that poli-OCT signals agreed with optical lock-in theory and the bio-heat equation, and the system exhibited shot noise limited performance. In phantoms containing biologically relevant concentrations of ICG (1 µg/ml), the poli-OCT signal was significantly greater than control phantoms (p<0.05), demonstrating sensitivity to small molecules. Finally, in vivo poli-OCT of ICG identified the lymphatic vessels in a mouse ear, and also identified low concentrations (200 pM) of gold nanorods in subcutaneous injections at frame rates ten times faster than previously reported. This work illustrates that future in vivo molecular imaging studies could benefit from the improved acquisition and analysis times enabled by poli-OCT.

Longitudinal monitoring techniques for preclinical models of vascular remodeling are critical to the development of new therapies for pathological conditions such as ischemia and cancer. In models of skeletal muscle ischemia in particular, there is a lack of quantitative, non-invasive and long term assessment of vessel morphology. Here, we have applied speckle variance optical coherence tomography (OCT) methods to quantitatively assess vascular remodeling and growth in a mouse model of peripheral arterial disease. This approach was validated on two different mouse strains known to have disparate rates and abilities of recovering following induction of hind limb ischemia. These results establish the potential for speckle variance OCT as a tool for quantitative, preclinical screening of pro- and anti-angiogenic therapies.

HER2-amplified (HER2 + ) breast cancers are treated with the anti-HER2 monoclonal antibody trastuzumab. Although trastuzumab reduces production of the angiogenic factor VEGF in HER2 + tumors, the acute and sustained effects of trastuzumab on the tumor vasculature are not understood fully, particularly in trastuzumab-resistant tumors. We used mouse models of trastuzumab sensitive and trastuzumab-resistant HER2 + breast cancers to measure dynamic changes in tumor microvessel density and hemoglobin oxygenation (sO2) in vivo using quantitative hyperspectral imaging at 2, 5, 9, and 14 days after antibody treatment. Further analysis quantified the distribution of microvessels into low and high oxygenation groups, and monitored changes in these distributions with trastuzumab treatment. Gold standard immunohistochemistry was performed to validate complementary markers of tumor cell and vascular response to treatment. Trastuzumab treatment in both responsive and resistant tumors resulted in decreased sO2 5 days after initial treatment when compared to IgG-treated controls (p<0.05). Importantly, responsive tumors showed significantly higher vessel density and significantly lower sO2 than all other groups at 5 days post-treatment (p<0.05). Distribution analysis of vessel sO2 showed a significant (p<0.05) shift of highly oxygenated vessels towards lower oxygenation over the time-course in both trastuzumab-treated responsive and resistant tumors. This study suggests that longitudinal hyperspectral imaging of microvessel sO2 and density could distinguish trastuzumab-responsive from trastuzumab-resistant tumors, a finding that could be exploited in the post-neoadjuvant setting to guide post-surgical treatment decisions.

Current imaging techniques capable of tracking nanoparticles in vivo supply either a large field of view or cellular resolution, but not both. Here, we demonstrate a multimodality imaging platform of optical coherence tomography (OCT) techniques for high resolution, wide field of view in vivo imaging of nanoparticles. This platform includes the first in vivo images of nanoparticle pharmacokinetics acquired with photothermal OCT (PTOCT), along with overlaying images of microvascular and tissue morphology. Gold nanorods (51.8 ± 8.1 nm by 15.2 ± 3.3 nm) were intravenously injected into mice, and their accumulation into mammary tumors was non-invasively imaged in vivo in three dimensions over 24 hours using PTOCT. Spatial frequency analysis of PTOCT images indicated that gold nanorods reached peak distribution throughout the tumors by 16 hours, and remained well-dispersed up to 24 hours post-injection. In contrast, the overall accumulation of gold nanorods within the tumors peaked around 16 hours post-injection. The accumulation of gold nanorods within the tumors was validated post-mortem with multiphoton microscopy. This shows the utility of PTOCT as part of a powerful multimodality imaging platform for the development of nanomedicines and drug delivery technologies.

The optical redox ratio (fluorescence intensity of NADH divided by that of FAD), was acquired for a panel of breast cancer cell lines to investigate how overexpression of human epidermal growth factor receptor 2 (HER2) affects tumor cell metabolism, and how tumor metabolism may be altered in response to clinically used HER2-targeted therapies. Confocal fluorescence microscopy was used to acquire NADH and FAD auto-fluorescent images. The optical redox ratio was highest in cells overexpressing HER2 and lowest in triple negative breast cancer (TNBC) cells, which lack HER2, progesterone receptor, and estrogen receptor (ER). The redox ratio in ER-positive/HER2-negative cells was higher than what was seen in TNBC cells, but lower than that in HER2 overexpressing cells. Importantly, inhibition of HER2 using trastuzumab significantly reduced the redox ratio in HER2 overexpressing cells. Furthermore, the combinatorial inhibition of HER2 and ER decreased the redox ratio in ER+/HER2+ breast cancer cells to a greater extent than inhibition of either receptor alone. Interestingly, trastuzumab had little impact upon the redox ratio in a cell line selected for acquired resistance to trastuzumab. Taken together, these data indicate that the optical redox ratio measures changes in tumor metabolism that reflect the oncogenic effects of HER2 activity within the cell, as well as the response of the cell to therapeutic inhibition of HER2. Therefore, optical redox imaging holds the promise of measuring response and resistance to receptor-targeted breast cancer therapies in real time, which could potentially impact clinical decisions and improve patient outcome., (2011 Optical Society of America)

We explored the use of diffuse reflectance spectroscopy in the ultraviolet-visible (UV-VIS) spectrum for the diagnosis of epithelial precancers and cancers in vivo. A physical model (Monte Carlo inverse model) and an empirical model (principal component analysis, (PCA)) based approach were compared for extracting diagnostic features from diffuse reflectance spectra measured in vivo from the dimethylbenz[alpha]anthracene-treated hamster cheek pouch model of oral carcinogenesis. These diagnostic features were input into a support vector machine algorithm to classify each tissue sample as normal (n=10) or neoplastic (dysplasia to carcinoma, n=10) and cross-validated using a leave one out method. There was a statistically significant decrease in the absorption and reduced scattering coefficient at 460 nm in neoplastic compared to normal tissues, and these two features provided 90% classification accuracy. The first two principal components extracted from PCA provided a classification accuracy of 95%. The first principal component was highly correlated with the wavelength-averaged reduced scattering coefficient. Although both methods show similar classification accuracy, the physical model provides insight into the physiological and structural features that discriminate between normal and neoplastic tissues and does not require a priori, a representative set of spectral data from which to derive the principal components.