Label-free multiphoton excitation imaging as a promising diagnostic tool for breast cancer

Matsui, Takahiro; Iwasa, Akio; Mimura, Masafumi; Taniguchi, Seiji; Sudo, Takao; Uchida, Yutaka; Kikuta, Junichi; Morizono, Hidetomo; Horii, Rie; Motoyama, Yuichi; Morii, Eiichi; Ohno, Shinji; Kiyota, Yasujiro; Ishii, Masaru

doi:https://doi.org/10.1111/cas.15428

Label-free multiphoton excitation imaging as a promising diagnostic tool for breast cancer

Matsui, Takahiro; Iwasa, Akio; Mimura, Masafumi et al.

Cancer Science, 2022, 113(8), 2916-2925

Number of Access:1,684（2025-07-18 12:27 Counts）

Identifier to cite or link to this item: https://hdl.handle.net/11094/93154

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Title	Label-free multiphoton excitation imaging as a promising diagnostic tool for breast cancer
Creator	NRID 1000050747037 1000050747037 ORCID 0000-0002-6753-1688 0000-0002-6753-1688 researchmap permalink takahiromatsui takahiromatsui Scopus Author ID 35176152500 35176152500 CreatorName Matsui, Takahiro
	CreatorName Iwasa, Akio
	CreatorName Mimura, Masafumi
	NRID 1000050836252 1000050836252 CreatorName Taniguchi, Seiji
	NRID 1000080631184 1000080631184 researchmap permalink kik kik Scopus Author ID 36497716100 36497716100 CreatorName Sudo, Takao
	NRID 1000050833787 1000050833787 researchmap permalink YutakaUchida YutakaUchida Scopus Author ID 56967526600 56967526600 CreatorName Uchida, Yutaka
	NRID 1000060710069 1000060710069 researchmap permalink jkikuta jkikuta Scopus Author ID 36637603800 36637603800 CreatorName Kikuta, Junichi
	CreatorName Morizono, Hidetomo
	NRID 1000020446272 1000020446272 CreatorName Horii, Rie
	CreatorName Motoyama, Yuichi
	NRID 1000010283772 1000010283772 ORCID 0000-0001-8490-3650 0000-0001-8490-3650 researchmap permalink read0046454 read0046454 Scopus Author ID 7003914326 7003914326 CreatorName Morii, Eiichi
	NRID 1000050203881 1000050203881 CreatorName Ohno, Shinji
	CreatorName Kiyota, Yasujiro
	NRID 1000010324758 1000010324758 researchmap permalink read0076684 read0076684 Scopus Author ID 35074093500 35074093500 CreatorName Ishii, Masaru
Subject	artificial intelligence
	breast cancer
	multiphoton excitation microscopy
	rapid diagnosis
	surgical margin
Description	This is the pre-peer reviewed version of the following article:Matsui T., Iwasa A., Mimura M., et al. Label-free multiphoton excitation imaging as a promising diagnostic tool for breast cancer. Cancer Science 113, 2916 (2022), which has been published in final form at https://doi.org/10.1111/cas.15428. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
Abstract	Histopathological diagnosis is the ultimate method of attaining the final diagnosis; however, the observation range is limited to the two-dimensional plane, and it requires thin slicing of the tissue, which limits diagnostic information. To seek solutions for these problems, we proposed a novel imaging-based histopathological examination. We used the multiphoton excitation microscopy (MPM) technique to establish a method for visualizing unfixed/unstained human breast tissues. Under near-infrared ray excitation, fresh human breast tissues emitted fluorescent signals with three major peaks, which enabled visualizing the breast tissue morphology without any fixation or dye staining. Our study using human breast tissue samples from 32 patients indicated that experienced pathologists can estimate normal or cancerous lesions using only these MPM images with a kappa coefficient of 1.0. Moreover, we developed an image classification algorithm with artificial intelligence that enabled us to automatically define cancer cells in small areas with a high sensitivity of ≥0.942. Taken together, label-free MPM imaging is a promising method for the real-time automatic diagnosis of breast cancer.
Publisher	John Wiley and Sons Inc
Source Title	Cancer Science
Volume (Issue)	113(8)
Page	2916-2925
Date of Issued	2022-08-01
Language	English
Handle URL	https://hdl.handle.net/11094/93154
PISSN	13479032
eISSN	13497006
Relation.isIdenticalTo	DOI (Publisher Version) https://doi.org/10.1111/cas.15428
Access Rights	open access
CopyRight	This article is licensed under a Creative Commons Attribution 4.0 International License.
oaire:version	Version of Record
Category	学術雑誌論文 Journal Article

Resource Type	journal article
Local Type	Journal Article
DCMI Type	Text
DCTERMS.bibliographicCitation	Cancer Science. 2022, 113(8), p. 2916-2925
DC.title	Label-free multiphoton excitation imaging as a promising diagnostic tool for breast cancer
DC.creator	Matsui, Takahiro
	Iwasa, Akio
	Mimura, Masafumi
	Taniguchi, Seiji
	Sudo, Takao
	Uchida, Yutaka
	Kikuta, Junichi
	Morizono, Hidetomo
	Horii, Rie
	Motoyama, Yuichi
	Morii, Eiichi
	Ohno, Shinji
	Kiyota, Yasujiro
	Ishii, Masaru
DC.publisher	John Wiley and Sons Inc
DC.language' scheme='DCTERMS.RFC1766	English
DC.type' scheme='DCTERMS.DCMIType	Text
DCTERMS.issued' scheme='DCTERMS.W3CDTF	2022-08-01
DC.identifier	https://doi.org/10.1111/cas.15428
DC.subject	artificial intelligence
	breast cancer
	multiphoton excitation microscopy
	rapid diagnosis
	surgical margin
DC.description	This is the pre-peer reviewed version of the following article:Matsui T., Iwasa A., Mimura M., et al. Label-free multiphoton excitation imaging as a promising diagnostic tool for breast cancer. Cancer Science 113, 2916 (2022), which has been published in final form at https://doi.org/10.1111/cas.15428. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
DCTERMS.abstract	Histopathological diagnosis is the ultimate method of attaining the final diagnosis; however, the observation range is limited to the two-dimensional plane, and it requires thin slicing of the tissue, which limits diagnostic information. To seek solutions for these problems, we proposed a novel imaging-based histopathological examination. We used the multiphoton excitation microscopy (MPM) technique to establish a method for visualizing unfixed/unstained human breast tissues. Under near-infrared ray excitation, fresh human breast tissues emitted fluorescent signals with three major peaks, which enabled visualizing the breast tissue morphology without any fixation or dye staining. Our study using human breast tissue samples from 32 patients indicated that experienced pathologists can estimate normal or cancerous lesions using only these MPM images with a kappa coefficient of 1.0. Moreover, we developed an image classification algorithm with artificial intelligence that enabled us to automatically define cancer cells in small areas with a high sensitivity of ≥0.942. Taken together, label-free MPM imaging is a promising method for the real-time automatic diagnosis of breast cancer.
DC.rights	This article is licensed under a Creative Commons Attribution 4.0 International License.
DC.format	93154
citation_title	Label-free multiphoton excitation imaging as a promising diagnostic tool for breast cancer
citation_author	Matsui, Takahiro
	Iwasa, Akio
	Mimura, Masafumi
	Taniguchi, Seiji
	Sudo, Takao
	Uchida, Yutaka
	Kikuta, Junichi
	Morizono, Hidetomo
	Horii, Rie
	Motoyama, Yuichi
	Morii, Eiichi
	Ohno, Shinji
	Kiyota, Yasujiro
	Ishii, Masaru
citation_publisher	John Wiley and Sons Inc
citation_language	English
citation_date	2022-08-01
citation_journal_title	Cancer Science
citation_volume	113
citation_issue	8
citation_firstpage	2916
citation_lastpage	2925
citation_doi	https://doi.org/10.1111/cas.15428
citation_public_url	https://hdl.handle.net/11094/93154

Label-free multiphoton excitation imaging as a promising diagnostic tool for breast cancer

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