Diagnosing Hirschsprung disease by detecting intestinal ganglion cells using label-free hyperspectral microscopy

Marcos A. Soares de Oliveira, Laura Galganski, Sarah Stokes, Che Wei Chang, Christopher D. Pivetti, Bo Zhang, Karen Matsukuma, Payam Saadai, James W. Chan

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Hirschsprung disease (HD) is a congenital disorder in the distal colon that is characterized by the absence of nerve ganglion cells in the diseased tissue. The primary treatment for HD is surgical intervention with resection of the aganglionic bowel. The accurate identification of the aganglionic segment depends on the histologic evaluation of multiple biopsies to determine the absence of ganglion cells in the tissue, which can be a time-consuming procedure. We investigate the feasibility of using a combination of label-free optical modalities, second harmonic generation (SHG); two-photon excitation autofluorescence (2PAF); and Raman spectroscopy (RS), to accurately locate and identify ganglion cells in murine intestinal tissue without the use of exogenous labels or dyes. We show that the image contrast provided by SHG and 2PAF signals allows for the visualization of the overall tissue morphology and localization of regions that may contain ganglion cells, while RS provides detailed multiplexed molecular information that can be used to accurately identify specific ganglion cells. Support vector machine, principal component analysis and linear discriminant analysis classification models were applied to the hyperspectral Raman data and showed that ganglion cells can be identified with a classification accuracy higher than 95%. Our findings suggest that a near real-time intraoperative histology method can be developed using these three optical modalities together that can aid pathologists and surgeons in rapid, accurate identification of ganglion cells to guide surgical decisions with minimal human intervention.

Original languageEnglish (US)
Article number1398
JournalScientific reports
Volume11
Issue number1
DOIs
StatePublished - Dec 2021

ASJC Scopus subject areas

  • General

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