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Label-free brain tumor imaging using Raman-based methods

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Abstract

Introduction

Label-free Raman-based imaging techniques create the possibility of bringing chemical and histologic data into the operation room. Relying on the intrinsic biochemical properties of tissues to generate image contrast and optical tissue sectioning, Raman-based imaging methods can be used to detect microscopic tumor infiltration and diagnose brain tumor subtypes.

Methods

Here, we review the application of three Raman-based imaging methods to neurosurgical oncology: Raman spectroscopy, coherent anti-Stokes Raman scattering (CARS) microscopy, and stimulated Raman histology (SRH).

Results

Raman spectroscopy allows for chemical characterization of tissue and can differentiate normal and tumor-infiltrated tissue based on variations in macromolecule content, both ex vivo and in vivo. To improve signal-to-noise ratio compared to conventional Raman spectroscopy, a second pulsed excitation laser can be used to coherently drive the vibrational frequency of specific Raman active chemical bonds (i.e. symmetric stretching of –CH2 bonds). Coherent Raman imaging, including CARS and stimulated Raman scattering microscopy, has been shown to detect microscopic brain tumor infiltration in fresh brain tumor specimens with submicron image resolution. Advances in fiber-laser technology have allowed for the development of intraoperative SRH as well as artificial intelligence algorithms to facilitate interpretation of SRH images. With molecular diagnostics becoming an essential part of brain tumor classification, preliminary studies have demonstrated that Raman-based methods can be used to diagnose glioma molecular classes intraoperatively.

Conclusions

These results demonstrate how label-free Raman-based imaging methods can be used to improve the management of brain tumor patients by detecting tumor infiltration, guiding tumor biopsy/resection, and providing images for histopathologic and molecular diagnosis.

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Fig. 1

Figure and Caption adapted from Figs. 1 and 3 from [7]

Fig. 2

Figure and Caption adapted from Fig. 4 from [26]

Fig. 3

Figure and Caption adapted from Fig. 2 from [8]

Fig. 4

Figure and Caption adapted from Fig. 3 from [8]

Fig. 5

Figure and Caption adapted from Figs. 1 and 3 from [9]

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Authors and Affiliations

  1. University of Michigan, Ann Arbor, USA

    Todd Hollon

  2. New York University, New York, NY, USA

    Daniel A. Orringer

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  1. Todd Hollon
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  2. Daniel A. Orringer
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Correspondence to Daniel A. Orringer.

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Dr. Orringer is a shareholder in Invenio Imaging, Inc.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Hollon, T., Orringer, D.A. Label-free brain tumor imaging using Raman-based methods. J Neurooncol 151, 393–402 (2021). https://doi.org/10.1007/s11060-019-03380-z

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