Method for coregistration of optical measurements of breast tissue with histopathology : the importance of accounting for tissue deformations

For the validation of optical diagnostic technologies, experimental results need to be benchmarked against the gold standard. Currently, the gold standard for tissue characterization is assessment of hematoxylin and eosin (H&E)-stained sections by a pathologist. When processing tissue into H&E sections, the shape of the tissue deforms with respect to the initial shape when it was optically measured. We demonstrate the importance of accounting for these tissue deformations when correlating optical measurement with routinely acquired histopathology. We propose a method to register the tissue in the H&E sections to the optical measurements, which corrects for these tissue deformations. We compare the registered H&E sections to H&E sections that were registered with an algorithm that does not account for tissue deformations by evaluating both the shape and the composition of the tissue and using microcomputer tomography data as an independent measure. The proposed method, which did account for tissue deformations, was more accurate than the method that did not account for tissue deformations. These results emphasize the need for a registration method that accounts for tissue deformations, such as the method presented in this study, which can aid in validating optical techniques for clinical use. (C) The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License

Comparison of Varying Tissue Freezing Methods on Murine Colonic Tissue

Histology often requires a tissue specimen to be embedded so that it may be sectioned, stained, and mounted on a microscope slide for viewing. One common method of tissue embedding for rapid histology is freezing, since freezing allows tissue to be stored without the need for fixing. Frozen tissue is often embedded in a medium such as Optimal Cutting Temperature (OCT) compound so that it can be sectioned using a cryostat. However, factors such as ice-crystal formation during the freezing process can cause damage to the tissue. As such, the protocol used to freeze the tissue can affect the quality of the slides. The purpose of this project is to compare different freezing methods and examine their strengths and weaknesses when applied to murine colonic tissue. Murine colonic tissue was frozen using two snap-freezing methods, piezoelectric freezing, and two different cold storage methods, each with their own three to four variations. Transverse sections were made in a cryostat, which were mounted on slides and stained using a hematoxylin and eosin (H&E) staining protocol. The sections were then imaged using a light microscope. A blind test was conducted to rate the image quality and inter-rater agreement was calculated using Fleiss’s Kappa. Paraffin embedding obtained the highest score, while OCT embedding inside a -80°C freezer received the second highest score

Software for full-color 3D reconstruction of the biological tissues internal structure

A software for processing sets of full-color images of biological tissue histological sections is developed. We used histological sections obtained by the method of high-precision layer-by-layer grinding of frozen biological tissues. The software allows restoring the image of the tissue for an arbitrary cross-section of the tissue sample. Thus, our method is designed to create a full-color 3D reconstruction of the biological tissue structure. The resolution of 3D reconstruction is determined by the quality of the initial histological sections. The newly developed technology available to us provides a resolution of up to 5 - 10 {\mu}m in three dimensions.Comment: 11 pages, 8 figure

Digital synthesis of histological stains using micro-structured and multiplexed virtual staining of label-free tissue

Histological staining is a vital step used to diagnose various diseases and has been used for more than a century to provide contrast to tissue sections, rendering the tissue constituents visible for microscopic analysis by medical experts. However, this process is time-consuming, labor-intensive, expensive and destructive to the specimen. Recently, the ability to virtually-stain unlabeled tissue sections, entirely avoiding the histochemical staining step, has been demonstrated using tissue-stain specific deep neural networks. Here, we present a new deep learning-based framework which generates virtually-stained images using label-free tissue, where different stains are merged following a micro-structure map defined by the user. This approach uses a single deep neural network that receives two different sources of information at its input: (1) autofluorescence images of the label-free tissue sample, and (2) a digital staining matrix which represents the desired microscopic map of different stains to be virtually generated at the same tissue section. This digital staining matrix is also used to virtually blend existing stains, digitally synthesizing new histological stains. We trained and blindly tested this virtual-staining network using unlabeled kidney tissue sections to generate micro-structured combinations of Hematoxylin and Eosin (H&E), Jones silver stain, and Masson's Trichrome stain. Using a single network, this approach multiplexes virtual staining of label-free tissue with multiple types of stains and paves the way for synthesizing new digital histological stains that can be created on the same tissue cross-section, which is currently not feasible with standard histochemical staining methods.Comment: 19 pages, 5 figures, 2 table

Measuring the electrical impedance of mouse brain tissue

We report on an experimental method to measure conductivity of cortical tissue. We use a pair of 5mm diameter Ag/AgCl electrodes in a Perspex sandwich device that can be brought to a distance of 400 microns apart. The apparatus is brought to uniform temperature before use. Electrical impedance of a sample is measured across the frequency range 20 Hz-2.0 MHz with an Agilent 4980A four-point impedance monitor in a shielded room. The equipment has been used to measure the conductivity of mature mouse brain cortex in vitro. Slices 400 microns in thickness are prepared on a vibratome. Slices are bathed in artificial cerebrospinal fluid (ACSF) to keep them alive. Slices are removed from the ACSF and sections of cortical tissue approximately 2 mm times 2 mm are cut with a razor blade. The sections are photographed through a calibrated microscope to allow identification of their cross-sectional areas. Excess ACSF is removed from the sample and the sections places between the electrodes. The impedance is measured across the frequency range and electrical conductivity calculated. Results show two regions of dispersion. A low frequency region is evident below approximately 10 kHz, and a high frequency dispersion above this. Results at the higher frequencies show a good fit to the Cole-Cole model of impedance of biological tissue; this model consists of resistive and non-linear capacitive elements. Physically, these elements are likely to arise due to membrane polarization and migration of ions both intra- and extra-cellularly.http://www.iupab2014.org/assets/IUPAB/NewFolder/iupab-abstracts.pd