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Optical Methods for Diabetic Foot Ulcer Screening
Published in Andrey V. Dunaev, Valery V. Tuchin, Biomedical Photonics for Diabetes Research, 2023
Robert Bartlett, Gennadi Saiko, Alexandre Yu. Douplik
Biomedical hyperspectral imaging (HSI) aims to record the spectrum for each pixel of the image and extract the concentration of tissue chromophores. In this sense, HSI is the natural extension of color (RGB) imaging and biospectroscopy (a single-point measurement). Spectrum at each pixel as a function of a wavelength (λ, nm) can be considered a spectroscopic input, which can be decomposed and spectral signatures can be found.
Molecular Vibrational Imaging by Coherent Raman Scattering
Published in Shoogo Ueno, Bioimaging, 2020
Yasuyuki Ozeki, Hideaki Kano, Naoki Fukutake
Hyperspectral CARS/SRS imaging refers to the acquisition of images in which each pixel contains the information of the vibrational spectrum, i.e., the CARS/SRS signal as a function of vibrational frequency. Hyperspectral imaging enables the discrimination of different molecules with a subtle difference in the vibrational spectrum and allows for a detailed analysis of biological samples. This is in contrast to the basic implementation of CARS microscopy and SRS microscopy described in Section 3.3, where images reflect only a specific vibrational mode at a single frequency that is determined by the frequency difference between pump and Stokes pulses. In this subsection, vibrational spectroscopic imaging using hyperspectral CARS microscopy is described.
Voltage-Sensitive Dye and Intrinsic Signal Optical Imaging
Published in Yu Chen, Babak Kateb, Neurophotonics and Brain Mapping, 2017
Vassiliy Tsytsarev, Reha S. Erzurumlu
One of the optical imaging modalities, potentially applicable not only for VSDi but also for IOS, is hyperspectral imaging, which is defined as the highly effective combination acquisition of spectral information from the different points of the sample (Studer et al., 2012). The application of this method is becoming popular with the availability of an increasing panel of fluorescent dyes with wide emission spectrum (Studer et al., 2012).
Retinal imaging biomarkers of neurodegenerative diseases
Published in Clinical and Experimental Optometry, 2022
Eirini Christinaki, Hana Kulenovic, Xavier Hadoux, Nicole Baldassini, Jan Van Eijgen, Lies De Groef, Ingeborg Stalmans, Peter van Wijngaarden
Hyperspectral imaging provides detailed information on the wavelengths of light reflected from the retina. Molecular and structural changes that influence the spectral composition of this reflected light may therefore be detected using hyperspectral imaging. In vitro and preclinical studies have suggested that low-order, soluble amyloid-beta oligomers cause Rayleigh scattering of light and thus a distinct reflectance pattern that can be captured with a hyperspectral camera.38,77–79 The use of retinal hyperspectral imaging for the detection of AD has been explored in three clinical studies. Overall, these have shown that retinal hyperspectral imaging can be used to differentiate people with AD from controls. In one study spectral differences were most pronounced in the early stages of the disease, in people with MCI (MMSE ≥22).80 Another study utilised a machine learning approach to analyse the hyperspectral images of the retina and calculate a hyperspectral score. This approach distinguished people with MCI and high brain amyloid-beta levels, measured using PET imaging, from control participants with low brain amyloid-beta levels.20 Finally, a study of people with clinically probable AD and control subjects indicated that a combinatorial approach with retinal hyperspectral imaging and OCT can increase the accuracy of a hyperspectral imaging-based classification model for the detection of AD.70 Larger replication studies are needed, as are studies to characterise the quantitative association between retinal imaging measure and brain levels of amyloid-beta.
Short-term oral administration of non-porous and mesoporous silica did not induce local or systemic toxicity in mice
Published in Nanotoxicology, 2020
Joan Cabellos, Irene Gimeno-Benito, Julia Catalán, Hanna K. Lindberg, Gerard Vales, Elisabet Fernandez-Rosas, Radu Ghemis, Keld A. Jensen, Rambabu Atluri, Socorro Vázquez-Campos, Gemma Janer
Beyond local toxicity, one of the main concerns of insoluble nanoparticle exposure is the potential systemic absorption and consequent long-term accumulation. Hyperspectral imaging is a relatively new technique to assess the presence and distribution of nanomaterials in biological samples in a label-free manner, allowing minimal interference with the sample integrity, which permits its assessment with other methods later. Several studies using an hyperspectral image system have been performed to detect different type of metallic, metal oxides, and even organic NPs in a variety of tissues (Ilves et al. 2014; Husain et al. 2013; Talamini et al. 2017; Holian et al. 2019). In some studies, inductively coupled plasma mass spectrometry (ICP-MS) has been used to confirm the results of hyperspectral data (Talamini et al. 2017). In this case, measuring silicon via ICP-MS would be challenging due to the ubiquitous presence of silica in labware and the analytical equipment and the natural-occurring silicon background in tissues (Aureli et al. 2020).
Biological impact of nanodiamond particles – label free, high-resolution methods for nanotoxicity assessment
Published in Nanotoxicology, 2019
Dipesh Khanal, Fan Zhang, Yang Song, Herman Hau, Archana Gautam, Seiji Yamaguchi, Jamie Uertz, Stewart Mills, Alexey Kondyurin, Jonathan C. Knowles, George Georgiou, Iqbal Ramzan, Weidong Cai, Kee Woei Ng, Wojciech Chrzanowski
3D holotomography, dark field hyperspectral imaging and SEM showed that NDs were readily internalized by cells and were distributed within entire cell structure. 3D images of cells treated with NDs for 2, 4 and 7 days showed the presence of substantial amount of NDs within cells (Figure 5(a–e) & Figure S2(a,b); black stain; black and white arrows). The amount of ND within cells dropped with the time of exposure. Hyperspectral imaging confirmed the same trend (Figure S3). At days 2 and 4, a substantial amount of NDs were found to persist within cell structure (Figure S3(b), white arrows). At day 7, the amount of intracellular NDs was reduced (Figure S3(d), white arrows).