Optical sensor for fast and accurate lung cancer detection with tissue autofluorescence and diffuse reflectance spectroscopy
Abstract Background Cancer is a severe threat to human health, and surgery is a major method of cancer treatment. This study aimed to develop an optical sensor for fast cancer tissue. Methods The tissue autofluorescence spectrum and diffuse reflectance spectrum were obtained by using a laboratory‐de...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-01-01
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| Series: | Thoracic Cancer |
| Subjects: | |
| Online Access: | https://doi.org/10.1111/1759-7714.15476 |
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| author | Xianbei Yang Anzhi Chen Kaicheng U Sophia Meixuan Zhang Peihao Wang Zheng Li Yi Luo Yong Cui |
| author_facet | Xianbei Yang Anzhi Chen Kaicheng U Sophia Meixuan Zhang Peihao Wang Zheng Li Yi Luo Yong Cui |
| author_sort | Xianbei Yang |
| collection | DOAJ |
| description | Abstract Background Cancer is a severe threat to human health, and surgery is a major method of cancer treatment. This study aimed to develop an optical sensor for fast cancer tissue. Methods The tissue autofluorescence spectrum and diffuse reflectance spectrum were obtained by using a laboratory‐developed optical sensor system. A total of 151 lung tissue samples were used in this ex vivo study. Results Experimental results demonstrate that tissue autofluorescence spectroscopy with a 365‐nm excitation has better performance than diffuse reflectance spectroscopy, and 63 of 64 test samples (98.4% accuracy) were correctly classified with tissue autofluorescence spectroscopy and our developed data analysis method. Conclusions Our promising ex vivo study results show that the developed optical sensor system has great promise for future clinical translation for intraoperative lung cancer detection and other applications. |
| format | Article |
| id | doaj-art-9610000d08bb40a3aae49f532fb016cc |
| institution | DOAJ |
| issn | 1759-7706 1759-7714 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Thoracic Cancer |
| spelling | doaj-art-9610000d08bb40a3aae49f532fb016cc2025-08-20T02:59:14ZengWileyThoracic Cancer1759-77061759-77142025-01-01161n/an/a10.1111/1759-7714.15476Optical sensor for fast and accurate lung cancer detection with tissue autofluorescence and diffuse reflectance spectroscopyXianbei Yang0Anzhi Chen1Kaicheng U2Sophia Meixuan Zhang3Peihao Wang4Zheng Li5Yi Luo6Yong Cui7Department of Thoracic Surgery Beijing Friendship Hospital, Capital Medical University Beijing ChinaSchool of Computer Science and Technology, North China University of Technology Beijing ChinaDepartment of Computational Biology College of Agriculture and Life Sciences, Cornell University Ithaca New York USADepartment of Biological Sciences College of Agriculture and Life Sciences, Cornell University Ithaca New York USADepartment of Thoracic Surgery Beijing Friendship Hospital, Capital Medical University Beijing ChinaDepartment of Agricultural and Resource Economics College of Agriculture and Life Sciences, North Carolina State University Raleigh North Carolina USADepartment of Thoracic Surgery University‐Town Hospital of Chongqing Medical University Chongqing ChinaDepartment of Thoracic Surgery Beijing Friendship Hospital, Capital Medical University Beijing ChinaAbstract Background Cancer is a severe threat to human health, and surgery is a major method of cancer treatment. This study aimed to develop an optical sensor for fast cancer tissue. Methods The tissue autofluorescence spectrum and diffuse reflectance spectrum were obtained by using a laboratory‐developed optical sensor system. A total of 151 lung tissue samples were used in this ex vivo study. Results Experimental results demonstrate that tissue autofluorescence spectroscopy with a 365‐nm excitation has better performance than diffuse reflectance spectroscopy, and 63 of 64 test samples (98.4% accuracy) were correctly classified with tissue autofluorescence spectroscopy and our developed data analysis method. Conclusions Our promising ex vivo study results show that the developed optical sensor system has great promise for future clinical translation for intraoperative lung cancer detection and other applications.https://doi.org/10.1111/1759-7714.15476artificial intelligencediagnosislung canceroptical sensor |
| spellingShingle | Xianbei Yang Anzhi Chen Kaicheng U Sophia Meixuan Zhang Peihao Wang Zheng Li Yi Luo Yong Cui Optical sensor for fast and accurate lung cancer detection with tissue autofluorescence and diffuse reflectance spectroscopy Thoracic Cancer artificial intelligence diagnosis lung cancer optical sensor |
| title | Optical sensor for fast and accurate lung cancer detection with tissue autofluorescence and diffuse reflectance spectroscopy |
| title_full | Optical sensor for fast and accurate lung cancer detection with tissue autofluorescence and diffuse reflectance spectroscopy |
| title_fullStr | Optical sensor for fast and accurate lung cancer detection with tissue autofluorescence and diffuse reflectance spectroscopy |
| title_full_unstemmed | Optical sensor for fast and accurate lung cancer detection with tissue autofluorescence and diffuse reflectance spectroscopy |
| title_short | Optical sensor for fast and accurate lung cancer detection with tissue autofluorescence and diffuse reflectance spectroscopy |
| title_sort | optical sensor for fast and accurate lung cancer detection with tissue autofluorescence and diffuse reflectance spectroscopy |
| topic | artificial intelligence diagnosis lung cancer optical sensor |
| url | https://doi.org/10.1111/1759-7714.15476 |
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