Spectroscopic optical coherence tomography for ex vivo brain tumor analysis

Marcel Lenz; Robin Krug; Christopher Dillmann; Alexandra Gerling; Nils C. Gerhardt; Hubert Welp; Kirsten Schmieder; Martin R. Hofmann

doi:10.1117/12.2252141

14 February 2017 Spectroscopic optical coherence tomography for ex vivo brain tumor analysis

Marcel Lenz, Robin Krug, Christopher Dillmann, Alexandra Gerling, Nils C. Gerhardt, Hubert Welp, Kirsten Schmieder, Martin R. Hofmann

Author Affiliations +

Proceedings Volume 10054, Advanced Biomedical and Clinical Diagnostic and Surgical Guidance Systems XV; 100540L (2017) https://doi.org/10.1117/12.2252141
Event: SPIE BiOS, 2017, San Francisco, California, United States

Abstract

For neurosurgeries precise tumor resection is essential for the subsequent recovery of the patients since nearby healthy tissue that may be harmed has a huge impact on the life quality after the surgery. However, so far no satisfying methodology has been established to assist the surgeon during surgery to distinguish between healthy and tumor tissue. Optical Coherence Tomography (OCT) potentially enables non-contact in vivo image acquisition at penetration depths of 1-2 mm with a resolution of approximately 1-15 μm. To analyze the potential of OCT for distinction between brain tumors and healthy tissue, we used a commercially available Thorlabs Callisto system to measure healthy tissue and meningioma samples ex vivo. All samples were measured with the OCT system and three dimensional datasets were generated. Afterwards they were sent to the pathology for staining with hematoxylin and eosin and then investigated with a bright field microscope to verify the tissue type. This is the actual gold standard for ex vivo analysis. The images taken by the OCT system exhibit variations in the structure for different tissue types, but these variations may not be objectively evaluated from raw OCT images. Since an automated distinction between tumor and healthy tissue would be highly desirable to guide the surgeon, we applied Spectroscopic Optical Coherence Tomography to further enhance the differences between the tissue types. Pattern recognition and machine learning algorithms were applied to classify the derived spectroscopic information. Finally, the classification results are analyzed in comparison to the histological analysis of the samples.

Citation Download Citation

Marcel Lenz, Robin Krug, Christopher Dillmann, Alexandra Gerling, Nils C. Gerhardt, Hubert Welp, Kirsten Schmieder, and Martin R. Hofmann "Spectroscopic optical coherence tomography for ex vivo brain tumor analysis", Proc. SPIE 10054, Advanced Biomedical and Clinical Diagnostic and Surgical Guidance Systems XV, 100540L (14 February 2017); https://doi.org/10.1117/12.2252141

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
7 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Optical coherence tomography

Tissues

Tumors

Spectroscopy

Surgery

Brain

Optical spectroscopy

Show All Keywords

Keywords/Phrases

Search In:

Publication Years