Detection of changes on and below the surface in epithelium mucosal tissue structure using scattered light

Ezgi Taslidere

doi:10.17918/00008032

The aim of this work is to answer the question of whether it is possible to detect changes on and below the surface in epithelium tissue structure using light reflected from the tissue over an area (2-D scan) illuminated by an optical sensor (fiber) emitting light at either one wavelength or with white light. Towards that end we model the 2-D reflected scans using a Stochastic Decomposition Method (SDM). The emphasis in this work is on the novelty of the proposed model and its theoretical pinning and foundation. The model is biologically motivated by the stochastic textural nature of the tissue. We model the textural content (which relates to tissue morphology) that manifests itself in the 2-D scans. Unlike previous works that analyze the scattered signal at one spot at various wavelengths, our method statistically analyzes 2-D scans of light scattering data over an area, and extracts from the data features (SDM parameters) that change with changes in the tissue morphology. The examination of an area rather than a spot not only leads to a more reliable calculation of the extracted parameters using single techniques (e.g. nuclear size distribution), but it also leads to the computation of additional information embedded in the spatial texture that our decomposition technique arrives at by modeling the hidden correlations that are obtained only by interrogating a wide sample area. To the best of our knowledge, this is the first attempt at modeling the scattered light over an area using a stochastic decomposition model that allows for the assessment of correlation and textural characteristics that otherwise could not be revealed when the analysis of the scattering signal is a function of wavelength or angle. We also come up with a segmentation technique to raise a flag on the fly when a transition occurs between different mucosal architectures on the surface. The segmentation is based on a novel difference metric for detecting an abrupt change in the parameters extracted from SDM. This has a great potential to enhance the endoscopist's ability to locate and identify abnormal mucosal architectures and help the endoscopist's decision making for when and where to take biopsies. Finally, this work presents a meaningful comparison between existing point spectroscopy methods and our method on tissue phantom data as well as in vitro biological tissues and shows scenarios where the two methods are complimentary and other scenarios where our method will be able to detect changes in tissue morphology whereas point spectroscopy will not. The method is tested on simulation, tissue phantom data and animal tissue data collected from rat and rabbit colons in-vitro and shows great promise.

Detection of changes on and below the surface in epithelium mucosal tissue structure using scattered light

Files and links (1)

Abstract

Metrics

Details

Detection of changes on and below the surface in epithelium mucosal tissue structure using scattered light

Files and links (1)

Abstract

Metrics

Details

Drexel University Social media