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SPECIAL TOPIC — Celebrating the 100th Anniversary of Physics Discipline of Northwest University
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SPECIAL TOPIC—Celebrating the 100th Anniversary of Physics Discipline of Northwest University |
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Assessing pathological features of breast cancer via the multimodal information of multiphoton and Raman imaging |
Bing-Ran Gao(高冰然)1, Xi-Wen Chen(陈希文)2, Bao-Ping Zhang(张宝萍)1, Ivan A. Bratchenko3, Jian-Xin Chen(陈建新)2, Shuang Wang(王爽)1, and Si-Yuan Xu(许思源)1,† |
1 Institute of Photonics and Photon-Technology, Northwest University, Xi'an 710127, China; 2 Key Laboratory of Opto-Electronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou 350007, China; 3 Laser and Biotechnical Systems Department, Samara National Research University, Samara 443086, Russia |
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Abstract For unveiling the pathological evolution of breast cancer, nonlinear multiphoton microscopic (MPM) and confocal Raman microspectral imaging (CRMI) techniques were both utilized to address the structural and constitutional characteristics of healthy (H), ductal carcinoma in situ (DCIS), and invasive ductal carcinoma (IDC) tissues. MPM-based techniques, including two-photon excited fluorescence (TPEF) and second harmonic generation (SHG), visualized label-free and the fine structure of breast tissue. Meanwhile, CRMI not only presented the chemical images of investigated samples with the K-mean cluster analysis method (KCA), but also pictured the distribution of components in the scanned area through univariate imaging. MPM images illustrated that the cancer cells first arranged around the basement membrane of the duct, then proliferated to fill the lumens of the duct, and finally broke through the basement membrane to infiltrate into the stroma. Although the Raman imaging failed to visualize the cell structure with high resolution, it explained spectroscopically the gradual increase of nucleic acid and protein components inside the ducts as cancer cells proliferated, and displayed the distribution pattern of each biological component during the evolution of breast cancer. Thus, the combination of MPM and CRMI provided new insights into the on-site pathological diagnosis of malignant breast cancer, also ensured technical support for the development of multimodal optical imaging techniques for precise histopathological analysis.
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Received: 17 May 2023
Revised: 21 July 2023
Accepted manuscript online: 26 July 2023
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Fund: Project supported by the National Natural Science Foundation of China (Grant No. 61911530695) and the Key Research and Development Project of Shaanxi Province of China (Grant No. 2023-YBSF-671). |
Corresponding Authors:
Si-Yuan Xu
E-mail: xusy@nwu.edu.cn
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Cite this article:
Bing-Ran Gao(高冰然), Xi-Wen Chen(陈希文), Bao-Ping Zhang(张宝萍), Ivan A. Bratchenko, Jian-Xin Chen(陈建新), Shuang Wang(王爽), and Si-Yuan Xu(许思源) Assessing pathological features of breast cancer via the multimodal information of multiphoton and Raman imaging 2023 Chin. Phys. B 32 118703
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[1] Schie I W, Stiebing C and Jürgen P 2021 J. Biomed. Opt. 26 080601 [2] Pallua J D, Brunner A, Zelger B, Schirmer M and Haybaeck J 2020 Pathol. Res. Pract. 216 153040 [3] Xiao X, Song H, Wang Z J and Wang L 2014 Chin. Phys. B 23 074101 [4] Miwa S, Yamamoto N, Hayashi K, Takeuchi A and Tsuchiya H 2020 Int. J. Clin. Oncol. 25 2158 [5] Stewart S, Priore R J, Nelson M P and Treado P J 2012 Annu. Rev. Anal. Chem. 5 337 [6] Shen Y, Hu F and Min W 2019 Annu. Rev. Biophys. 48 347 [7] Yang C, Ma Z, Xu F, Zhao L, Li F and He B 2011 Nat. Photonics 5 1 [9] Wu Y, Fu F, Lian Y, Chen J, Wang C, Nie Y, Zheng L and Zhuo S 2015 Laser Med. Sci. 30 1109 [10] Chen X, Nadiarynkh O, Plotnikov S and Campagnola P J 2012 Nat. Protoc. 7 654 [11] Wang H and Evans C L 2016 In imaging in Dermatology (Boston:Academic Press) pp. 103-117 [12] Xu S, Chen X, Ning T, Huang X, Chen J, Zhang B and Wang S 2022 J. Phys. D 55 465401 [13] Ackerman D and Simon M C 2014 Trends Cell Biol. 24 472 [14] Song D, Chen Y and Li J 2021 J. Biophotonics 14 e202000456 [15] Song D, Qin J, Chen Y, Wang H, Ning T, Wang S and Li J 2021 J. Raman Spectrosc. 52 1428 [16] Schie I W, Placzek F, Knorr F, Cordero E and Leitgeb R A 2021 Sci. Rep. 11 9951 [17] Wu Y, Fu F, Lian Y, Nie Y, Zhuo S, Wang C and Chen J 2015 J. Biomed. Opt. 20 096007 [18] Lazaro-Pacheco D, Shaaban A M, Rehman S and Rehman I 2020 Appl. Spectrosc. Rev. 55 439 [19] Wang H, Li J, Qin J, Li J, Chen Y, Song D, Zeng H and Wang S 2022 J. Photochem. Photobio. B 226 112366 [20] Rehman S, Movasaghi Z, Tucker A T, Joel S P and Rehman I U 2007 J. Raman Spectrosc. 38 1345 [21] Stone N, Kendall C, Smith J, Crow P and Barr H 2004 Faraday Discuss 126 141 [22] Ning T, Li H, Chen Y, Zhang B and Wang S 2021 Vib. Spectrosc. 115 103260 [23] Song D, Chen T, Wang S, Chen S, Li H, Yu F, Zhang J and Zhang Z 2020 Analyst 145 626 [24] Qiu J, Jiang W, Yang Y, Feng C, Chen Z, Guan G, Zhuo S and Chen J 2015 Scanning 37 17 [25] Provenzano P P, Eliceiri K W, Campbell J M, Inman D R, White J G and Keely P J 2006 BMC Med. 4 38 [26] Bhattacharjee T, Fontana L C, Raniero L and Ferreira-Strixino J 2018 J. Raman Spectrosc. 49 786 [27] Hedegaard M, Matthus C, Hassing S, Krafft C, Diem M and Jürgen P 2011 Theor. Chem. Acc. 130 1249 |
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