Hyperspectral imaging for colon cancer classification in surgical specimens: towards optical biopsy during image-guided surgery

Francesca Manni; Roger Fonollà; Fons van der Sommen; Svitlana Zinger; Caifeng Shan; Esther Kho; Susan G. Brouwer de Koning; Theo J.M. Ruers; Peter H.N. de With

doi:10.1109/EMBC44109.2020.9176543

Hyperspectral imaging for colon cancer classification in surgical specimens: towards optical biopsy during image-guided surgery

Francesca Manni, Roger Fonollà, Fons van der Sommen, Svitlana Zinger, Caifeng Shan, Esther Kho, Susan G. Brouwer de Koning, Theo J.M. Ruers, Peter H.N. de With

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

2 Citations (Scopus)

Abstract

The main curative treatment for localized colon cancer is surgical resection. However when tumor residuals are left positive margins are found during the histological examinations and additional treatment is needed to inhibit recurrence. Hyperspectral imaging (HSI) can offer non-invasive surgical guidance with the potential of optimizing the surgical effectiveness. In this paper we investigate the capability of HSI for automated colon cancer detection in six ex-vivo specimens employing a spectral-spatial patch-based classification approach. The results demonstrate the feasibility in assessing the benign and malignant boundaries of the lesion with a sensitivity of 0.88 and specificity of 0.78. The results are compared with the state-of-the-art deep learning based approaches. The method with a new hybrid CNN outperforms the state-of the-art approaches (0.74 vs. 0.82 AUC). This study paves the way for further investigation towards improving surgical outcomes with HSI.

Original language	English
Title of host publication	42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publication	Enabling Innovative Technologies for Global Healthcare, EMBC 2020
Publisher	IEEE EMBS
Pages	1169-1173
Number of pages	5
ISBN (Electronic)	978-1-7281-1990-8
DOIs	https://doi.org/10.1109/EMBC44109.2020.9176543
Publication status	Published - 27 Aug 2020

Publication series

Name	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume	2020-July
ISSN (Print)	1557-170X

Keywords

hyperspectral imaging
colon cancer
image-guided surgery
3D-2D CNN
Neoplasm Recurrence, Local/diagnostic imaging
Biopsy
Colonic Neoplasms/diagnostic imaging
Humans
Surgery, Computer-Assisted

UN SDGs

This output contributes to the following Sustainable Development Goal(s)

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Manni, F., Fonollà, R., van der Sommen, F., Zinger, S., Shan, C., Kho, E., Brouwer de Koning, S. G., Ruers, T. J. M., & de With, P. H. N. (2020). Hyperspectral imaging for colon cancer classification in surgical specimens: towards optical biopsy during image-guided surgery. In 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society: Enabling Innovative Technologies for Global Healthcare, EMBC 2020 (pp. 1169-1173). [9176543] (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 2020-July). IEEE EMBS. https://doi.org/10.1109/EMBC44109.2020.9176543

Manni, Francesca ; Fonollà, Roger ; van der Sommen, Fons ; Zinger, Svitlana ; Shan, Caifeng ; Kho, Esther ; Brouwer de Koning, Susan G. ; Ruers, Theo J.M. ; de With, Peter H.N. / Hyperspectral imaging for colon cancer classification in surgical specimens: towards optical biopsy during image-guided surgery. 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society: Enabling Innovative Technologies for Global Healthcare, EMBC 2020. IEEE EMBS, 2020. pp. 1169-1173 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

@inproceedings{cbb6418de0474c78b2c49f815eee4b68,

title = "Hyperspectral imaging for colon cancer classification in surgical specimens: towards optical biopsy during image-guided surgery",

abstract = "The main curative treatment for localized colon cancer is surgical resection. However when tumor residuals are left positive margins are found during the histological examinations and additional treatment is needed to inhibit recurrence. Hyperspectral imaging (HSI) can offer non-invasive surgical guidance with the potential of optimizing the surgical effectiveness. In this paper we investigate the capability of HSI for automated colon cancer detection in six ex-vivo specimens employing a spectral-spatial patch-based classification approach. The results demonstrate the feasibility in assessing the benign and malignant boundaries of the lesion with a sensitivity of 0.88 and specificity of 0.78. The results are compared with the state-of-the-art deep learning based approaches. The method with a new hybrid CNN outperforms the state-of the-art approaches (0.74 vs. 0.82 AUC). This study paves the way for further investigation towards improving surgical outcomes with HSI.",

keywords = "hyperspectral imaging, colon cancer, image-guided surgery, 3D-2D CNN, Neoplasm Recurrence, Local/diagnostic imaging, Biopsy, Colonic Neoplasms/diagnostic imaging, Humans, Surgery, Computer-Assisted",

author = "Francesca Manni and Roger Fonoll{\`a} and {van der Sommen}, Fons and Svitlana Zinger and Caifeng Shan and Esther Kho and {Brouwer de Koning}, {Susan G.} and Ruers, {Theo J.M.} and {de With}, {Peter H.N.}",

year = "2020",

month = aug,

day = "27",

doi = "10.1109/EMBC44109.2020.9176543",

language = "English",

series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",

publisher = "IEEE EMBS",

pages = "1169--1173",

booktitle = "42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society",

}

Manni, F , Fonollà, R , van der Sommen, F , Zinger, S, Shan, C, Kho, E, Brouwer de Koning, SG, Ruers, TJM & de With, PHN 2020, Hyperspectral imaging for colon cancer classification in surgical specimens: towards optical biopsy during image-guided surgery. in 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society: Enabling Innovative Technologies for Global Healthcare, EMBC 2020., 9176543, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, vol. 2020-July, IEEE EMBS, pp. 1169-1173. https://doi.org/10.1109/EMBC44109.2020.9176543

Hyperspectral imaging for colon cancer classification in surgical specimens: towards optical biopsy during image-guided surgery. / Manni, Francesca ; Fonollà, Roger ; van der Sommen, Fons ; Zinger, Svitlana; Shan, Caifeng; Kho, Esther; Brouwer de Koning, Susan G.; Ruers, Theo J.M.; de With, Peter H.N.

42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society: Enabling Innovative Technologies for Global Healthcare, EMBC 2020. IEEE EMBS, 2020. p. 1169-1173 9176543 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 2020-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Hyperspectral imaging for colon cancer classification in surgical specimens: towards optical biopsy during image-guided surgery

AU - Manni, Francesca

AU - Fonollà, Roger

AU - van der Sommen, Fons

AU - Zinger, Svitlana

AU - Shan, Caifeng

AU - Kho, Esther

AU - Brouwer de Koning, Susan G.

AU - Ruers, Theo J.M.

AU - de With, Peter H.N.

PY - 2020/8/27

Y1 - 2020/8/27

N2 - The main curative treatment for localized colon cancer is surgical resection. However when tumor residuals are left positive margins are found during the histological examinations and additional treatment is needed to inhibit recurrence. Hyperspectral imaging (HSI) can offer non-invasive surgical guidance with the potential of optimizing the surgical effectiveness. In this paper we investigate the capability of HSI for automated colon cancer detection in six ex-vivo specimens employing a spectral-spatial patch-based classification approach. The results demonstrate the feasibility in assessing the benign and malignant boundaries of the lesion with a sensitivity of 0.88 and specificity of 0.78. The results are compared with the state-of-the-art deep learning based approaches. The method with a new hybrid CNN outperforms the state-of the-art approaches (0.74 vs. 0.82 AUC). This study paves the way for further investigation towards improving surgical outcomes with HSI.

AB - The main curative treatment for localized colon cancer is surgical resection. However when tumor residuals are left positive margins are found during the histological examinations and additional treatment is needed to inhibit recurrence. Hyperspectral imaging (HSI) can offer non-invasive surgical guidance with the potential of optimizing the surgical effectiveness. In this paper we investigate the capability of HSI for automated colon cancer detection in six ex-vivo specimens employing a spectral-spatial patch-based classification approach. The results demonstrate the feasibility in assessing the benign and malignant boundaries of the lesion with a sensitivity of 0.88 and specificity of 0.78. The results are compared with the state-of-the-art deep learning based approaches. The method with a new hybrid CNN outperforms the state-of the-art approaches (0.74 vs. 0.82 AUC). This study paves the way for further investigation towards improving surgical outcomes with HSI.

KW - hyperspectral imaging

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KW - image-guided surgery

KW - 3D-2D CNN

KW - Neoplasm Recurrence, Local/diagnostic imaging

KW - Biopsy

KW - Colonic Neoplasms/diagnostic imaging

KW - Humans

KW - Surgery, Computer-Assisted

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DO - 10.1109/EMBC44109.2020.9176543

M3 - Conference contribution

C2 - 33018195

T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

SP - 1169

EP - 1173

BT - 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society

PB - IEEE EMBS

ER -

Manni F , Fonollà R , van der Sommen F , Zinger S, Shan C, Kho E et al. Hyperspectral imaging for colon cancer classification in surgical specimens: towards optical biopsy during image-guided surgery. In 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society: Enabling Innovative Technologies for Global Healthcare, EMBC 2020. IEEE EMBS. 2020. p. 1169-1173. 9176543. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). https://doi.org/10.1109/EMBC44109.2020.9176543

Hyperspectral imaging for colon cancer classification in surgical specimens: towards optical biopsy during image-guided surgery

Abstract

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Keywords

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