Multimodal, label-free histopathology for improving the diagnosis of Hirschsprung disease

Marcos A. Soares de Oliveira; Laura A. Galganski; Che-Wei Chang; Christopher D. Pivetti; Karen E. Matsukuma; Bo Zhang; Alexandro Lopez; Payam Saadai; James W. Chan

doi:10.1117/12.2545174

20 February 2020 Multimodal, label-free histopathology for improving the diagnosis of Hirschsprung disease

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

Author Affiliations +

Proceedings Volume 11251, Label-free Biomedical Imaging and Sensing (LBIS) 2020; 112511F (2020) https://doi.org/10.1117/12.2545174
Event: SPIE BiOS, 2020, San Francisco, California, United States

Abstract

Hirschsprung disease (HD) is a congenital disorder in the distal intestine and is characterized by the absence of nerve ganglion cells (aganglionosis). HD affects newborns by causing severe constipation. Surgical management is needed and consists of the accurate identification and removal of the aganglionic segment and the reconstruction of the intestinal tract. The gold standard for the definitive diagnosis of the aganglionic segment is the histologic evaluation of rectal biopsies through stained sections. However, it is a time-consuming procedure, and recognized factors for inaccurate diagnoses have been commonly reported. In recent years there has been much interest in the use of optical techniques to improve diagnostics in health care. Here, for improving the identification of ganglion cells, we propose an ex-vivo study to evaluate a combination of label-free optical modalities: second harmonic generation (SHG); two-photon autofluorescence; and Raman spectroscopy. SHG and autofluorescence images have been used to locate regions of interest in the tissue for Raman analysis, which acquires a molecular fingerprint of the ganglion cells, without needing any stains or labels. Multivariate statistical analyses of the Raman spectral data have been used for objective identification of the ganglion cells in the tissue samples with high accuracy.

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Citation Download Citation

Marcos A. Soares de Oliveira, Laura A. Galganski, Che-Wei Chang, Christopher D. Pivetti, Karen E. Matsukuma, Bo Zhang, Alexandro Lopez, Payam Saadai, and James W. Chan "Multimodal, label-free histopathology for improving the diagnosis of Hirschsprung disease", Proc. SPIE 11251, Label-free Biomedical Imaging and Sensing (LBIS) 2020, 112511F (20 February 2020); https://doi.org/10.1117/12.2545174

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