Theranostics 2021; 11(15):7222-7234. doi:10.7150/thno.59244 This issue

Research Paper

Label-free imaging of human brain tissue at subcellular resolution for potential rapid intra-operative assessment of glioma surgery

Defu Chen1,2#, David W. Nauen3#, Hyeon-Cheol Park1, Dawei Li1, Wu Yuan1, Ang Li1, Honghua Guan1, Carmen Kut1, Kaisorn L. Chaichana4, Chetan Bettegowda5, Alfredo Quiñones-Hinojosa4✉, Xingde Li1✉

1. Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA.
2. Institute of Engineering Medicine, Beijing Institute of Technology, Beijing 100081, China.
3. Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA.
4. Department of Neurologic Surgery, Mayo Clinic, Jacksonville, FL 32224, USA.
5. Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA.
#Equal contributions to this work.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions.
Citation:
Chen D, Nauen DW, Park HC, Li D, Yuan W, Li A, Guan H, Kut C, Chaichana KL, Bettegowda C, Quiñones-Hinojosa A, Li X. Label-free imaging of human brain tissue at subcellular resolution for potential rapid intra-operative assessment of glioma surgery. Theranostics 2021; 11(15):7222-7234. doi:10.7150/thno.59244. Available from https://www.thno.org/v11p7222.htm

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Abstract

Graphic abstract

Background: Frozen section and smear preparation are the current standard for intraoperative histopathology during cancer surgery. However, these methods are time-consuming and subject to limited sampling. Multiphoton microscopy (MPM) is a high-resolution non-destructive imaging technique capable of optical sectioning in real time with subcellular resolution. In this report, we systematically investigated the feasibility and translation potential of MPM for rapid histopathological assessment of label- and processing-free surgical specimens.

Methods: We employed a customized MPM platform to capture architectural and cytological features of biological tissues based on two-photon excited NADH and FAD autofluorescence and second harmonic generation from collagen. Infiltrating glioma, an aggressive disease that requires subcellular resolution for definitive characterization during surgery, was chosen as an example for this validation study. MPM images were collected from resected brain specimens of 19 patients and correlated with histopathology. Deep learning was introduced to assist with image feature recognition.

Results: MPM robustly captures diagnostic features of glioma including increased cellularity, cellular and nuclear pleomorphism, microvascular proliferation, necrosis, and collagen deposition. Preliminary application of deep learning to MPM images achieves high accuracy in distinguishing gray from white matter and cancer from non-cancer. We also demonstrate the ability to obtain such images from intact brain tissue with a multiphoton endomicroscope for intraoperative application.

Conclusion: Multiphoton imaging correlates well with histopathology and is a promising tool for characterization of cancer and delineation of infiltration within seconds during brain surgery.

Keywords: multiphoton microscopy (MPM), two-photon excited fluorescence (TPF), glioma, multiphoton endomicroscope, histopathology