Raman microspectroscopy and machine learning for use in identifying radiation-induced lung toxicity

OBJECTIVE

In this work, we explore and develop a method that uses Raman spectroscopy to measure and differentiate radiation induced toxicity in murine lungs with the goal of setting the foundation for a predictive disease model.

METHODS

Analysis of Raman tissue data is achieved through a combination of techniques. We first distinguish between tissue measurements and air pockets in the lung by using group and basis restricted non-negative matrix factorization. We then analyze the tissue spectra using sparse multinomial logistic regression to discriminate between fibrotic gradings. Model validation is achieved by splitting the data into a training set containing 70% of the data and a test set with the remaining 30%; classification accuracy is used as the performance metric. We also explore several other potential classification tasks wherein the response considered is the grade of pneumonitis and fibrosis sickness.

RESULTS

A classification accuracy of 91.6% is achieved on the test set of fibrotic gradings, illustrating the ability of Raman measurements to detect differing levels of fibrotic disease among the murine lungs. It is also shown via further modeling that coarser consideration of fibrotic grading via binning (ie. 'Low', 'Medium', 'High') does not degrade performance. Finally, we consider preliminary models for pneumonitis discrimination using the same methodologies.

Multi-window sparse spectral sampling stimulated Raman scattering microscopy

Stimulated Raman scattering (SRS) is a nondestructive and rapid technique for imaging of biological and clinical specimens with label-free chemical specificity. SRS spectral imaging is typically carried out either via broadband methods, or by tuning narrowband ultrafast light sources over narrow spectral ranges thus specifically targeting vibrational frequencies. We demonstrate a multi-window sparse spectral sampling SRS (S4RS) approach where a rapidly-tunable dual-output all-fiber optical parametric oscillator is tuned into specific vibrational modes across more than 1400 cm-1 during imaging. This approach is capable of collecting SRS hyperspectral images either by scanning a full spectrum or by rapidly tuning into select target frequencies, hands-free and automatically, across the fingerprint, silent, and high wavenumber windows of the Raman spectrum. We further apply computational techniques for spectral decomposition and feature selection to identify a sparse subset of Raman frequencies capable of sample discrimination. Here we have applied this novel method to monitor spatiotemporal dynamic changes of active pharmaceutical ingredients in skin, which has particular relevance to topical drug product delivery.

FTIR, Raman and AFM characterization of the clinically valid biochemical parameters of the thrombi in acute ischemic stroke

The significance and utility of innovative imaging techniques in arterial clot analysis, which enable far more detailed and automated analysis compared to standard methods, are presented. The examination of two types of human thrombi is shown, representing the main ischemic stroke etiologies: fibrin–predominant clot of large vessel origin and red blood cells–rich clot of cardioembolic origin. The synergy effect of Fourier–transform infrared spectroscopy (FTIR), Raman spectroscopy (RS) and atomic force microscopy (AFM) techniques supported by chemometrics in comparison with reference histological staining was presented. The main advantage of such approach refers to free–label and non–destructive quantitative imaging of clinically valid, biochemical parameters in whole sample (FTIR–low resolution) and selected regions (RS–ultra–high resolution). We may include here analysis of lipid content, its distribution and total degree of unsaturation as well as analysis of protein content (mainly fibrin and hemoproteins). The AFM studies enhanced the vibrational data, showed clearly shape and thickness of clot features as well as visualized the fibrin framework. The extraordinary sensitivity of FTIR and RS imaging toward detection and discrimination of clinically valid parameters in clot confirms its applicability in assessment of thrombi origin.

Simultaneous dual-channel stimulated Raman scattering microscopy demultiplexed at distinct modulation frequencies

To increase the information per pixel in stimulated Raman scattering (SRS) microscopy as well as to correct from artifacts, it is valuable to acquire images at two different Raman shifts. We present a three-color SRS approach acquiring two perfectly registered SRS images where both pump beams are modulated at distinct frequencies while demodulating the Stokes beam. Our implementation uses two optical parametric oscillators that can be tuned to an almost arbitrary energy difference of Raman shifts, allowing investigation of fingerprint resonances simultaneously to CH-stretch vibrations.

Fingerprint Stimulated Raman Scattering Imaging Reveals Retinoid Coupling Lipid Metabolism and Survival

Retinoids play critical roles in development, immunity, and lipid metabolism, and their deficiency leads to various human disorders. Yet, tools for sensing retinoids in vivo are lacking, which limits the understanding of retinoid distribution, dynamics and functions in living organisms. Here, using hyperspectral stimulated Raman scattering microscopy, we discover a previously unknown cytoplasmic store of retinoids in Caenorahbditis elegans. Following the temporal dynamics of retinoids, we reveal that their levels are positively correlated with fat storage, and their supplementation slows down fat loss during starvation. We also discover that retinoids promote fat unsaturation in response to high-glucose stress, and improve organism survival. Together, our studies report a new method for tracking the spatiotemporal dynamics of retinoids in living organisms, and suggest the crucial roles of retinoids in maintaining metabolic homeostasis and enhancing organism fitness upon developmental and dietary stresses.

FT-IR- and Raman-based biochemical profiling of the early stage of pulmonary metastasis of breast cancer in mice

The combination of FT-IR and Raman spectroscopies allowed the biochemical profiling of lungs and definition of the spectroscopic biomarkers of the early stage of pulmonary metastasis of breast cancer.

Label-free spectroscopic characterization of live liver sinusoidal endothelial cells (LSECs) isolated from the murine liver

Imaging with the use of Raman spectroscopy enables the characterization and distinction of live cells that were freshly isolated from murine livers.

Single cell analysis in native tissue: Quantification of the retinoid content of hepatic stellate cells

Hepatic stellate cells (HSCs) are retinoid storing cells in the liver: The retinoid content of those cells changes depending on nutrition and stress level. There are also differences with regard to a HSC’s anatomical position in the liver. Up to now, retinoid levels were only accessible from bulk measurements of tissue homogenates or cell extracts. Unfortunately, they do not account for the intercellular variability. Herein, Raman spectroscopy relying on excitation by the minimally destructive wavelength 785 nm is introduced for the assessment of the retinoid state of single HSCs in freshly isolated, unprocessed murine liver lobes. A quantitative estimation of the cellular retinoid content is derived. Implications of the retinoid content on hepatic health state are reported. The Raman-based results are integrated with histological assessments of the tissue samples. This spectroscopic approach enables single cell analysis regarding an important cellular feature in unharmed tissue.

IR and Raman imaging of murine brains from control and ApoE/LDLR−/− mice with advanced atherosclerosis

IR and Raman imaging combined with chemometric analyses were used to study the biochemical profile of the murine brain tissue from control (C57BL/6J) and ApoE/LDLR^−/− mice with advanced atherosclerosis.