AI Cytomorphology Combined with DNA-image Cytometry for Identifying Benign and Malignant Pleural Effusion and Ascites
Objective To explore the diagnostic value of artificial intelligence (AI) cytology combined with DNA-image cytometry (DNA-ICM) auxiliary diagnostic system for the identification of benign and malignant pleural effusion and ascites. Methods Liquid-based cytology technology (LCT), DNA-ICM, AI, and AI...
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| Format: | Article |
| Language: | zho |
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Magazine House of Cancer Research on Prevention and Treatment
2023-04-01
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| Series: | Zhongliu Fangzhi Yanjiu |
| Subjects: | |
| Online Access: | http://www.zlfzyj.com/EN/10.3971/j.issn.1000-8578.2023.22.0762 |
| _version_ | 1827950642260344832 |
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| author | JIANG Yang YU Huizhi GAO Ya SHEN Yu MAO Min LIU Chongmei |
| author_facet | JIANG Yang YU Huizhi GAO Ya SHEN Yu MAO Min LIU Chongmei |
| author_sort | JIANG Yang |
| collection | DOAJ |
| description | Objective To explore the diagnostic value of artificial intelligence (AI) cytology combined with DNA-image cytometry (DNA-ICM) auxiliary diagnostic system for the identification of benign and malignant pleural effusion and ascites. Methods Liquid-based cytology technology (LCT), DNA-ICM, AI, and AI combined with DNA-ICM were used to identify benign and malignant pleural effusion and ascites specimens in 360 cases, and their sensitivity, specificity, accuracy, Kappa value, Youden index and AUC were statistically analyzed. Results The sensitivity, specificity, and accuracy of AI combined with DNA-ICM in detecting benign and malignant pleural effusion and ascites were 95.23%, 94.12%, and 94.44%, respectively, which were higher than those of the three other separate detection methods (all P < 0.05). The kappa values of LCT, DNA-ICM, and AI were 0.646, 0.642, and 0.586; their Youden index values were 0.693, 0.687, and 0.676, and their AUC values were 0.846, 0.843, and 0.838, respectively. The Kappa value of AI combined with DNA-ICM was 0.869, the Youden index was 0.893, and AUC was 0.947, which were all higher than those of the three detection methods alone. Conclusion Among the three separate detection methods, LCT has the highest reliability, authenticity, and diagnostic value, and it can be used as a common method for the clinical identification of benign and malignant pleural effusion and ascites. The diagnostic performance of AI combined with DNA-ICM auxiliary diagnosis system in identifying benign and malignant pleural effusion and ascites is better than those of the three separate detection methods and can be used as a reliable method for the clinical identification of benign and malignant pleural effusion and ascites. |
| first_indexed | 2024-04-09T13:29:54Z |
| format | Article |
| id | doaj.art-baec98e84d124b77b5b752a5d4dec0f3 |
| institution | Directory Open Access Journal |
| issn | 1000-8578 |
| language | zho |
| last_indexed | 2024-04-09T13:29:54Z |
| publishDate | 2023-04-01 |
| publisher | Magazine House of Cancer Research on Prevention and Treatment |
| record_format | Article |
| series | Zhongliu Fangzhi Yanjiu |
| spelling | doaj.art-baec98e84d124b77b5b752a5d4dec0f32023-05-10T04:57:52ZzhoMagazine House of Cancer Research on Prevention and TreatmentZhongliu Fangzhi Yanjiu1000-85782023-04-0150439039610.3971/j.issn.1000-8578.2023.22.07628578.2023.22.0762AI Cytomorphology Combined with DNA-image Cytometry for Identifying Benign and Malignant Pleural Effusion and AscitesJIANG Yang0YU Huizhi1GAO Ya2SHEN Yu3MAO Min4LIU Chongmei5Department of Pathology, Yueyang People's Hospital, Hu'nan Normal University, Yueyang 414000, ChinaDepartment of Oncology, Yueyang People's Hospital, Hu'nan Normal University, Yueyang 414000, ChinaDepartment of Pathology, Yueyang People's Hospital, Hu'nan Normal University, Yueyang 414000, ChinaDepartment of Pathology, Yueyang People's Hospital, Hu'nan Normal University, Yueyang 414000, ChinaDepartment of Pathology, Yueyang People's Hospital, Hu'nan Normal University, Yueyang 414000, ChinaDepartment of Pathology, Yueyang People's Hospital, Hu'nan Normal University, Yueyang 414000, ChinaObjective To explore the diagnostic value of artificial intelligence (AI) cytology combined with DNA-image cytometry (DNA-ICM) auxiliary diagnostic system for the identification of benign and malignant pleural effusion and ascites. Methods Liquid-based cytology technology (LCT), DNA-ICM, AI, and AI combined with DNA-ICM were used to identify benign and malignant pleural effusion and ascites specimens in 360 cases, and their sensitivity, specificity, accuracy, Kappa value, Youden index and AUC were statistically analyzed. Results The sensitivity, specificity, and accuracy of AI combined with DNA-ICM in detecting benign and malignant pleural effusion and ascites were 95.23%, 94.12%, and 94.44%, respectively, which were higher than those of the three other separate detection methods (all P < 0.05). The kappa values of LCT, DNA-ICM, and AI were 0.646, 0.642, and 0.586; their Youden index values were 0.693, 0.687, and 0.676, and their AUC values were 0.846, 0.843, and 0.838, respectively. The Kappa value of AI combined with DNA-ICM was 0.869, the Youden index was 0.893, and AUC was 0.947, which were all higher than those of the three detection methods alone. Conclusion Among the three separate detection methods, LCT has the highest reliability, authenticity, and diagnostic value, and it can be used as a common method for the clinical identification of benign and malignant pleural effusion and ascites. The diagnostic performance of AI combined with DNA-ICM auxiliary diagnosis system in identifying benign and malignant pleural effusion and ascites is better than those of the three separate detection methods and can be used as a reliable method for the clinical identification of benign and malignant pleural effusion and ascites.http://www.zlfzyj.com/EN/10.3971/j.issn.1000-8578.2023.22.0762artificial intelligenceliquid-based cytologydna quantitative analysispleural and ascites effusiondiagnostic value |
| spellingShingle | JIANG Yang YU Huizhi GAO Ya SHEN Yu MAO Min LIU Chongmei AI Cytomorphology Combined with DNA-image Cytometry for Identifying Benign and Malignant Pleural Effusion and Ascites Zhongliu Fangzhi Yanjiu artificial intelligence liquid-based cytology dna quantitative analysis pleural and ascites effusion diagnostic value |
| title | AI Cytomorphology Combined with DNA-image Cytometry for Identifying Benign and Malignant Pleural Effusion and Ascites |
| title_full | AI Cytomorphology Combined with DNA-image Cytometry for Identifying Benign and Malignant Pleural Effusion and Ascites |
| title_fullStr | AI Cytomorphology Combined with DNA-image Cytometry for Identifying Benign and Malignant Pleural Effusion and Ascites |
| title_full_unstemmed | AI Cytomorphology Combined with DNA-image Cytometry for Identifying Benign and Malignant Pleural Effusion and Ascites |
| title_short | AI Cytomorphology Combined with DNA-image Cytometry for Identifying Benign and Malignant Pleural Effusion and Ascites |
| title_sort | ai cytomorphology combined with dna image cytometry for identifying benign and malignant pleural effusion and ascites |
| topic | artificial intelligence liquid-based cytology dna quantitative analysis pleural and ascites effusion diagnostic value |
| url | http://www.zlfzyj.com/EN/10.3971/j.issn.1000-8578.2023.22.0762 |
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