Towards Intraoperative Quantification of Atrial Fibrosis Using Light-Scattering Spectroscopy and Convolutional Neural Networks

Light-scattering spectroscopy (LSS) is an established optical approach for characterization of biological tissues. Here, we investigated the capabilities of LSS and convolutional neural networks (CNNs) to quantitatively characterize the composition and arrangement of cardiac tissues. We assembled tissue constructs from fixed myocardium and the aortic wall with a thickness similar to that of the atrial free wall. The aortic sections represented fibrotic tissue. Depth, volume fraction, and arrangement of these fibrotic insets were varied. We gathered spectra with wavelengths from 500–1100 nm from the constructs at multiple locations relative to a light source. We used single and combinations of two spectra for training of CNNs. With independently measured spectra, we assessed the accuracy of the CNNs for the classification of tissue constructs from single spectra and combined spectra. Combined spectra, including the spectra from fibers distal from the illumination fiber, typically yielded the highest accuracy. The maximal classification accuracy of the depth detection, volume fraction, and permutated arrangements was (mean ± standard deviation (stddev)) 88.97 ± 2.49%, 76.33 ± 1.51%, and 84.25 ± 1.88%, respectively. Our studies demonstrate the reliability of quantitative characterization of tissue composition and arrangements using a combination of LSS and CNNs. The potential clinical applications of the developed approach include intraoperative quantification and mapping of atrial fibrosis, as well as the assessment of ablation lesions.

Formation of laterally ordered arrays of noble metal nanocavities for SERS substrates by using interference photolithography

Using laterally ordered arrays of noble metal nanocavities as SERS substrates has been examined theoretically and experimentally. Simulation of the distribution of the electric field at the surface of nanostructures (nanocavities) has been carried out. The simulation results showed that cavities can be formed not only in a metal layer but in semiconductor or dielectric layers and then covered with a layer of a plasmon-supporting metal (silver or gold) 20…100-nm thick. In our work, chalcogenide glass has been used as a relief-forming layer. This paper presents the results of development and optimization of processes providing formation of SERS substrates as two-dimensional arrays of noble metal nanocavities by using interference photolithography based on a two-layer chalcogenide photoresist. Prototypes of SERS substrates were made as substrates with different spatial frequencies (from 1200 to 800 mm -1 ) and depths of nanocavities (from 250 up to 500 nm). It was shown that the use of such nanocavities with the sizes larger than 500 nm enables to efficiently analyze the structure of macromolecules by using surface- enhanced Raman light scattering spectroscopy, since these macromolecules completely overlap with the regions of enhanced electric field inside the nanocavities. Technology of interference lithography based on two-layer chalcogenide photoresists makes it possible to form effective SERS substrates in the form of laterally ordered arrays of nanocavities with specified morphological characteristics (spatial frequency, nanocavity sizes, composition and thickness of a conformal metal coating) for detecting high-molecular compounds.

EXPRESS: Monitoring the Refractive Index of Tissue Models Using Light Scattering Spectroscopy

In this work, we report the application of Raman microspectroscopy for analysis of the refractive index of a range of tissue phantoms. Using both a custom-developed setup with visible laser source and a commercial micro-spectrometer with near infrared laser, we measured the Raman spectra of gelatin hydrogels at various concentrations. By building a calibration curve from measured refractometry data and Raman scattering intensity for different vibrational modes of the hydrogel, we were able to predict the refractive indices of the gels from their Raman spectra. This work highlights the importance of a correlative approach through Brillouin-Raman microspectroscopy for the mechano-chemical analysis of biologically relevant samples.