Cargando…

Hyperspectral Imaging for Glioblastoma Surgery: Improving Tumor Identification Using a Deep Spectral-Spatial Approach

The primary treatment for malignant brain tumors is surgical resection. While gross total resection improves the prognosis, a supratotal resection may result in neurological deficits. On the other hand, accurate intraoperative identification of the tumor boundaries may be very difficult, resulting i...

Descripción completa

Detalles Bibliográficos
Autores principales: Manni, Francesca, van der Sommen, Fons, Fabelo, Himar, Zinger, Svitlana, Shan, Caifeng, Edström, Erik, Elmi-Terander, Adrian, Ortega, Samuel, Marrero Callicó, Gustavo, de With, Peter H. N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7730670/
https://www.ncbi.nlm.nih.gov/pubmed/33291409
http://dx.doi.org/10.3390/s20236955
_version_ 1783621737496182784
author Manni, Francesca
van der Sommen, Fons
Fabelo, Himar
Zinger, Svitlana
Shan, Caifeng
Edström, Erik
Elmi-Terander, Adrian
Ortega, Samuel
Marrero Callicó, Gustavo
de With, Peter H. N.
author_facet Manni, Francesca
van der Sommen, Fons
Fabelo, Himar
Zinger, Svitlana
Shan, Caifeng
Edström, Erik
Elmi-Terander, Adrian
Ortega, Samuel
Marrero Callicó, Gustavo
de With, Peter H. N.
author_sort Manni, Francesca
collection PubMed
description The primary treatment for malignant brain tumors is surgical resection. While gross total resection improves the prognosis, a supratotal resection may result in neurological deficits. On the other hand, accurate intraoperative identification of the tumor boundaries may be very difficult, resulting in subtotal resections. Histological examination of biopsies can be used repeatedly to help achieve gross total resection but this is not practically feasible due to the turn-around time of the tissue analysis. Therefore, intraoperative techniques to recognize tissue types are investigated to expedite the clinical workflow for tumor resection and improve outcome by aiding in the identification and removal of the malignant lesion. Hyperspectral imaging (HSI) is an optical imaging technique with the power of extracting additional information from the imaged tissue. Because HSI images cannot be visually assessed by human observers, we instead exploit artificial intelligence techniques and leverage a Convolutional Neural Network (CNN) to investigate the potential of HSI in twelve in vivo specimens. The proposed framework consists of a 3D–2D hybrid CNN-based approach to create a joint extraction of spectral and spatial information from hyperspectral images. A comparison study was conducted exploiting a 2D CNN, a 1D DNN and two conventional classification methods (SVM, and the SVM classifier combined with the 3D–2D hybrid CNN) to validate the proposed network. An overall accuracy of 80% was found when tumor, healthy tissue and blood vessels were classified, clearly outperforming the state-of-the-art approaches. These results can serve as a basis for brain tumor classification using HSI, and may open future avenues for image-guided neurosurgical applications.
format Online
Article
Text
id pubmed-7730670
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-77306702020-12-12 Hyperspectral Imaging for Glioblastoma Surgery: Improving Tumor Identification Using a Deep Spectral-Spatial Approach Manni, Francesca van der Sommen, Fons Fabelo, Himar Zinger, Svitlana Shan, Caifeng Edström, Erik Elmi-Terander, Adrian Ortega, Samuel Marrero Callicó, Gustavo de With, Peter H. N. Sensors (Basel) Article The primary treatment for malignant brain tumors is surgical resection. While gross total resection improves the prognosis, a supratotal resection may result in neurological deficits. On the other hand, accurate intraoperative identification of the tumor boundaries may be very difficult, resulting in subtotal resections. Histological examination of biopsies can be used repeatedly to help achieve gross total resection but this is not practically feasible due to the turn-around time of the tissue analysis. Therefore, intraoperative techniques to recognize tissue types are investigated to expedite the clinical workflow for tumor resection and improve outcome by aiding in the identification and removal of the malignant lesion. Hyperspectral imaging (HSI) is an optical imaging technique with the power of extracting additional information from the imaged tissue. Because HSI images cannot be visually assessed by human observers, we instead exploit artificial intelligence techniques and leverage a Convolutional Neural Network (CNN) to investigate the potential of HSI in twelve in vivo specimens. The proposed framework consists of a 3D–2D hybrid CNN-based approach to create a joint extraction of spectral and spatial information from hyperspectral images. A comparison study was conducted exploiting a 2D CNN, a 1D DNN and two conventional classification methods (SVM, and the SVM classifier combined with the 3D–2D hybrid CNN) to validate the proposed network. An overall accuracy of 80% was found when tumor, healthy tissue and blood vessels were classified, clearly outperforming the state-of-the-art approaches. These results can serve as a basis for brain tumor classification using HSI, and may open future avenues for image-guided neurosurgical applications. MDPI 2020-12-05 /pmc/articles/PMC7730670/ /pubmed/33291409 http://dx.doi.org/10.3390/s20236955 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Manni, Francesca
van der Sommen, Fons
Fabelo, Himar
Zinger, Svitlana
Shan, Caifeng
Edström, Erik
Elmi-Terander, Adrian
Ortega, Samuel
Marrero Callicó, Gustavo
de With, Peter H. N.
Hyperspectral Imaging for Glioblastoma Surgery: Improving Tumor Identification Using a Deep Spectral-Spatial Approach
title Hyperspectral Imaging for Glioblastoma Surgery: Improving Tumor Identification Using a Deep Spectral-Spatial Approach
title_full Hyperspectral Imaging for Glioblastoma Surgery: Improving Tumor Identification Using a Deep Spectral-Spatial Approach
title_fullStr Hyperspectral Imaging for Glioblastoma Surgery: Improving Tumor Identification Using a Deep Spectral-Spatial Approach
title_full_unstemmed Hyperspectral Imaging for Glioblastoma Surgery: Improving Tumor Identification Using a Deep Spectral-Spatial Approach
title_short Hyperspectral Imaging for Glioblastoma Surgery: Improving Tumor Identification Using a Deep Spectral-Spatial Approach
title_sort hyperspectral imaging for glioblastoma surgery: improving tumor identification using a deep spectral-spatial approach
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7730670/
https://www.ncbi.nlm.nih.gov/pubmed/33291409
http://dx.doi.org/10.3390/s20236955
work_keys_str_mv AT mannifrancesca hyperspectralimagingforglioblastomasurgeryimprovingtumoridentificationusingadeepspectralspatialapproach
AT vandersommenfons hyperspectralimagingforglioblastomasurgeryimprovingtumoridentificationusingadeepspectralspatialapproach
AT fabelohimar hyperspectralimagingforglioblastomasurgeryimprovingtumoridentificationusingadeepspectralspatialapproach
AT zingersvitlana hyperspectralimagingforglioblastomasurgeryimprovingtumoridentificationusingadeepspectralspatialapproach
AT shancaifeng hyperspectralimagingforglioblastomasurgeryimprovingtumoridentificationusingadeepspectralspatialapproach
AT edstromerik hyperspectralimagingforglioblastomasurgeryimprovingtumoridentificationusingadeepspectralspatialapproach
AT elmiteranderadrian hyperspectralimagingforglioblastomasurgeryimprovingtumoridentificationusingadeepspectralspatialapproach
AT ortegasamuel hyperspectralimagingforglioblastomasurgeryimprovingtumoridentificationusingadeepspectralspatialapproach
AT marrerocallicogustavo hyperspectralimagingforglioblastomasurgeryimprovingtumoridentificationusingadeepspectralspatialapproach
AT dewithpeterhn hyperspectralimagingforglioblastomasurgeryimprovingtumoridentificationusingadeepspectralspatialapproach