Abstract
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.
Highlights
Optical biopsy has the potential to revolutionize medical diagnostics by quantifying interactions of light with tissue
We evaluated the ability of the convolutional neural networks (CNNs) to identify fibrotic insets placed at varying depths in the myocardium, volume fractions of myocardial and fibrotic tissues, and permutated arrangements of these tissues
We introduced a system for evaluating fibrosis in cardiac tissue using tissue constructs, Light-scattering spectroscopy (LSS), and customized CNNs
Summary
Optical biopsy has the potential to revolutionize medical diagnostics by quantifying interactions of light with tissue. An optical biopsy eliminates many of the limitations of a conventional biopsy based on tissue excision. These limitations include tissue damage, infections, pain, and delayed analysis. An optical biopsy is often based on imaging modalities such as multi-photon microscopy, optical coherence tomography, and fiber-optics confocal microscopy (FCM) [1,2,3]. These modalities differ in their technical complexity, cost, and suitability for use in the various clinical environments, including the operating room. These different approaches provide various imaging depths and spatiotemporal resolutions which may limit their clinical applications
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