Poster + Paper
4 April 2022 Hyperspectral imaging for in-vivo/ex-vivo tissue analysis of human brain cancer
Author Affiliations +
Conference Poster
Abstract
Accurate identification of tumor boundaries during brain cancer surgery determines the quality of life of the patient. Different intraoperative guidance tools are currently employed during the resection tumor but having several limitations. Hyperspectral imaging (HSI) is arising as a label-free and non-ionizing technique that could assist neurosurgeons during surgical procedures. In this paper, an analysis between in-vivo and ex-vivo human brain tumor samples using HSI has been performed to evaluate the correlation between both types of samples. Spectral ratios of the oxygenated and deoxygenated hemoglobin were employed to distinguish between normal tissue, tumor tissue and blood vessels. A database composed by seven in-vivo and fourteen ex-vivo hyperspectral images obtained from seven different patients diagnosed with glioblastoma Grade IV, metastatic secondary breast cancer, meningioma Grade I and II, and astrocytoma (glioma) Grade II. 44,964 pixels labeled pixels were employed in this work. The proposed method achieved discrimination between different tissue types using the proposed spectral ratio. Comparison between in-vivo and ex-vivo samples indicated that ex-vivo samples generate higher hemoglobin ratios. Moreover, vascular enhanced maps were generated using the spectral ratio, targeting real-time intraoperative surgical assistance.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Raquel Leon, Sofia H. Gelado, Himar Fabelo, Samuel Ortega, Laura Quintana, Adam Szolna, Juan F. Piñeiro, Francisco Balea-Fernandez, Jesus Morera, Bernardino Clavo, and Gustavo M. Callico "Hyperspectral imaging for in-vivo/ex-vivo tissue analysis of human brain cancer", Proc. SPIE 12034, Medical Imaging 2022: Image-Guided Procedures, Robotic Interventions, and Modeling, 1203429 (4 April 2022); https://doi.org/10.1117/12.2611420
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KEYWORDS
Tissues

Tumors

In vivo imaging

Brain

Absorbance

Blood vessels

Neuroimaging

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