| Citation: |
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[J]. Cancer Research on Prevention and Treatment, 2023, 50(4): 390-396. DOI: 10.3971/j.issn.1000-8578.2023.22.0762
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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.
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.
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.
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.
Competing interests: The authors declare that they have no competing interests.
| [1] |
王应霞, 赵珍, 杨梅秋, 等. 液基细胞学检测在良恶性胸腹水鉴别诊断中的应用[J]. 昆明医科大学学报, 2016, 37(4): 45-48. https://www.cnki.com.cn/Article/CJFDTOTAL-KMYX201604012.htm
Wang YX, Zhao Z, Yang MQ, et al. Application of liquid based cytology in differential diagnosis of benign and malignant hydrothorax and ascites[J]. Kunming Yi Ke Da Xue Xue Bao, 2016, 37(4): 45-48. https://www.cnki.com.cn/Article/CJFDTOTAL-KMYX201604012.htm
|
| [2] |
Osaka R, Hayashi K, Onda T, et al. Evaluation of liquid based cytology for tongue squamous cell carcinoma: Comparison with conventional cytology[J]. Bull Tokyo Dent Coll, 2019, 60(1): 29-37. doi: 10.2209/tdcpublication.2018-0015
|
| [3] |
Ito K, Kimura R, Konishi H, et al. A comparison of liquid-based and conventional cytology using data for cervical cancer screening from the Japan Cancer Society[J]. Jpn J Clin Oncol, 2020, 50(2): 138-144. doi: 10.1093/jjco/hyz161
|
| [4] |
Meng Z, Shi J, Zhu C, et al. Automated quantification of DNA aneuploidy by image cytometry as an adjunct for the cytologic diagnosis of malignant effusion[J]. Anal Cell Pathol (Amst), 2013, 36(3-4): 107-115. doi: 10.1155/2013/501284
|
| [5] |
Liu C, Huang L, Zhang X, et al. Combination of DNA ploidy analysis and miR-21 or miR-24 in screening malignant pleural effusion[J]. Interact CardioVasc Thorac Surg, 2018, 26(3): 376-381. doi: 10.1093/icvts/ivx327
|
| [6] |
许娟. 细胞DNA倍体联合肿瘤标志物检测在良恶性胸腔积液、腹水鉴别中的应用价值[J]. 检验医学与临床, 2019, 16(23): 3469-3471.
Xu J. Application value of cell DNA ploidy combined with tumor marker detection in the identification of benign and malignant hydrothorax and ascites[J]. Jian Yan Yi Xue Yu Lin Chuang, 2019, 16(23): 3469-3471.
|
| [7] |
戴翠婷. DNA图像倍体分析细胞块脱落细胞涂片在胸腔积液良恶性诊断中的应用效果对比[J]. 基层医学论坛, 2020, 24(22): 3207-3208. https://www.cnki.com.cn/Article/CJFDTOTAL-YXLT202022060.htm
Dai CT. Comparison of application effect of DNA image ploidy analysis cell block exfoliated cell smear in the diagnosis of benign and malignant pleural effusion[J]. Ji Ceng Yi Xue Lun Tan, 2020, 24(22): 3207-3208. https://www.cnki.com.cn/Article/CJFDTOTAL-YXLT202022060.htm
|
| [8] |
张素霞, 周红, 宇小婷, 等. 全自动DNA定量分析检测对恶性胸腔积液诊断的价值[J]. 中华病理学杂志, 2015, (9): 653-654.
Zhang SX, Zhou H, Yu XT, et al. The value of automatic DNA quantitative analysis in the diagnosis of malignant pleural effusion[J]. Zhonghua Bing Li Xue Za Zhi, 2015, (9): 653-654.
|
| [9] |
Benlloch S, Martí-Ciriquián JL, Galbis-Caravajal JM, et al. Cell-free DNA concentration in pleural fluid and serum: quantitative approach and potential prognostic factor in patients with cancer and pleural effusions[J]. Clin Lung Cancer, 2006, 8(2): 140-145. doi: 10.3816/CLC.2006.n.043
|
| [10] |
Zhang L, Lu L, Nogues I, et al. DeepPap: deep convolutional networks for cervical cell classification[J]. IEEE J Biomed Health Inform, 2017, 21(6): 1633-1643. doi: 10.1109/JBHI.2017.2705583
|
| [11] |
李雪, 石中月, 杨志明, 等. 人工智能辅助分析在宫颈液基薄层细胞学检查中的应用价值[J]. 首都医科大学学报, 2020, 41(3): 360-363. https://www.cnki.com.cn/Article/CJFDTOTAL-SDYD202003009.htm
Li X, Shi ZY, Yang ZM, et al. Value about artificial intelligence-assisted liquid-based thin-layer cytology for cytologycervical cancer screening[J]. Shou Du Yi Ke Da Xue Xue Bao, 2020, 41(3): 360-363. https://www.cnki.com.cn/Article/CJFDTOTAL-SDYD202003009.htm
|
| [12] |
叶美华, 陈万远, 蔡博君, 等. 基于卷积神经网络的甲状腺液基细胞学病理辅助诊断模型的研究[J]. 中华病理学杂志, 2021, 50(4): 358-362.
Ye MH, Chen WY, Cai BJ, et al. A convolutional neural network based model for assisting pathological diagnoses on thyroid liquid-based cytology[J]. Zhonghua Bing Li Xue Za Zhi, 2021, 50(4): 358-362.
|
| [13] |
胡长爱, 杨大干, 叶章辉, 等. 基于智能数据和机器学习的尿液检验结果解释性报告[J]. 中华检验医学杂志, 2021, 44(6): 524-531. https://cpfd.cnki.com.cn/Article/CPFDTOTAL-ZJKX201910001101.htm
Yang CA, Yang DG, Ye ZH, et al. Interpreting report of urinalysis based on intelligent data and machine learning[J]. Zhonghua Jian Yan Yi Xue Za Zhi, 2021, 44(6): 524-531. https://cpfd.cnki.com.cn/Article/CPFDTOTAL-ZJKX201910001101.htm
|
| [14] |
Das N, Hussain E, Mahanta LB. Automated classification of cells into multiple classes in epithelial tissue of oral squamous cell carcinoma using transfer learning and convolutional neural network[J]. Neural Netw, 2020, 128: 47-60. doi: 10.1016/j.neunet.2020.05.003
|
| [15] |
Zhang H, Li W, Zhang H. An Image Recognition Framework for Oral Cancer Cells[J]. J Healthc Eng, 2021, 2021: 2449128.
|
| [16] |
Xie X, Fu CC, Lv L, et al. Deep convolutional neural network-based classification of cancer cells on cytological pleural effusion images[J]. Mod Pathol, 2022, 35(5): 609-614.
|
| [17] |
中国恶性胸腔积液诊断与治疗专家共识组. 恶性胸腔积液诊断与治疗专家共识[J]. 中华内科杂志, 2014, 53(3): 252-256. https://www.cnki.com.cn/Article/CJFDTOTAL-SYNK201408009.htm
Chinese expert consensus group on diagnosis and treatment of malignant pleural effusion. Expert consensus on diagnosis and treatment of malignant pleural effusion[J]. Zhonghua Nei Ke Za Zhi, 2014, 53(3): 252-256. https://www.cnki.com.cn/Article/CJFDTOTAL-SYNK201408009.htm
|
| [18] |
Jakhar D, Kaur I. Artificial intelligence, machine learning and deep learning: definitions and differences[J]. Clin Exp Dermatol, 2020, 45(1): 131-132.
|
| [19] |
Wang S, Li D, Wang J, et al. A Comparative Study of Liquid-Based Cytology and DNA Image Cytometry in the Diagnosis of Serous Effusion[J]. Technol Cancer Res Treat, 2020, 19: 1533033820942298.
|
| [20] |
Rossi ED, Bizzarro T, Schmitt F, et al. The role of liquid‐based cytology and ancillary techniques in pleural and pericardic effusions: an institutional experience[J]. Cancer Cytopathol, 2015, 123(4): 258-266.
|
| [21] |
郭宇妮. 多抗体检测、细胞DNA定量分析在肺癌诊疗中的应用研究[D]. 温州医科大学, 2015.
Guo YN. The detection of Lung cancer makers and the apply of DNA body in the judge of disease nature[D]. Wenzhou Medical University, 2015.
|
| [22] |
Liang Y, Yin Z, Liu H, et al. Weakly Supervised Deep Nuclei Segmentation with Sparsely Annotated Bounding Boxes for DNA Image Cytometry[J]. IEEE/ACM Transact Comput Biol Bioinform, 2021, PP.
|
| [23] |
钱同, 樊昱彤, 金玉, 等. 液基细胞学、肿瘤标志物SP70联合检测对肺腺癌转移胸腔积液的诊断价值[J]. 临床与病理杂志, 2020, 40(10): 2529-2533. https://www.cnki.com.cn/Article/CJFDTOTAL-WYSB202010004.htm
Qian T, Fan YT, Jin Y, et al. Value of tumor marker SP70 detection combined with liquid based cytology in diagnosing lung adenocarcinoma in pleural effusion[J]. Lin Chuang Yu Bing Li Za Zhi, 2020, 40(10): 2529-2533. https://www.cnki.com.cn/Article/CJFDTOTAL-WYSB202010004.htm
|
| [24] |
LeCun Y, Bengio Y, Hinton G. Deep learning[J]. Nature, 2015, 521(7553): 436-444.
|
| [25] |
Williams BJ, Bottoms D, Treanor D. Future-proofing pathology: the case for clinical adoption of digital pathology[J]. J Clin Pathol, 2017, 70(12): 1010-1018.
|
| [26] |
马艳春, 刘永坚, 解庆, 等. 自动图像标注技术综述[J]. 计算机研究与发展, 2020, 57(11): 2348-2374. https://www.cnki.com.cn/Article/CJFDTOTAL-JFYZ202011009.htm
Ma YC, Liu YJ, Xie Q, et al. ReView of Automatic Image Annotation Technology[J]. Ji Suan Ji Yan Jiu Yu Fa Zhan, 2020, 57(11): 2348-2374. https://www.cnki.com.cn/Article/CJFDTOTAL-JFYZ202011009.htm
|
| [27] |
Ehteshami Bejnordi B, Mullooly M, Pfeiffer RM, et al. Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsies[J]. Mod Pathol, 2018, 31(10): 1502-1512.
|
| [28] |
朱孝辉, 李晓鸣, 张文丽, 等. 人工智能辅助诊断在宫颈液基薄层细胞学中的应用[J]. 中华病理学杂志, 2021, 50(4): 333-338. https://cdmd.cnki.com.cn/Article/CDMD-10089-1022720333.htm
Zhu XH, Li XM, Zhang WL, et al. Application of artificial intelligence-assisted diagnosis for cervical liquid‐based thin‐layer cytology[J]. Zhonghua Bing Li Xue Za Zhi, 2021, 50(4): 333-338. https://cdmd.cnki.com.cn/Article/CDMD-10089-1022720333.htm
|
| [29] |
Sanyal P, Barui S, Deb P, et al. Performance of a convolutional neural network in screening liquid based cervical cytology smears[J]. J Cytol, 2019, 36(3): 146-151.
|
| [30] |
Li Y, Tian S, Huang Y, et al. Driverless artificial intelligence framework for the identification of malignant pleural effusion[J]. Transl Oncol, 2021, 14(1): 100896.
|
| [31] |
Su F, Sun Y, Hu Y, et al. Development and validation of a deep learning system for ascites cytopathology interpretation[J]. Gastric Cancer, 2020, 23(6): 1041-1050.
|
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| [4] | ZHANG Yanling, WU Qiuliang, JIANG Xiaoli, KE Guonv, ZHAO Weiqi, TAN Cuiting. Diagnostic Analysis of Liquid-base Cytology of 268 Cases of Endometrium[J]. Cancer Research on Prevention and Treatment, 2013, 40(11): 1074-1078. DOI: 10.3971/j.issn.1000-8578.2013.11.014 |
| [5] | YANG Yan, WU Xufeng, ZHANG Dunlan. Significance of DNA Quantitative Cytology and High-risk HPV-DNA Test in ASCUS Triage Diagnosis[J]. Cancer Research on Prevention and Treatment, 2013, 40(07): 671-674. DOI: 10.3971/j.issn.1000-8578.2013.07.010 |
| [6] | FAN Guo-yu, WU Xiao-kui, LI Chun-guo. Diagnosis Value of Tumor Markers for Malignant Pleural Effusions[J]. Cancer Research on Prevention and Treatment, 2011, 38(04): 434-436. DOI: 10.3971/j.issn.1000-8578.2011.04.018 |
| [7] | Yu Fangzhi, . The Values of CYFRA in Pleural Effusion[J]. Cancer Research on Prevention and Treatment, 1997, 24(3): 152-154. |
| [8] | Chen Guoquan, . The Diagnostic Value of the Carbohydrate Antigen CA50 on the Malignant Tumors[J]. Cancer Research on Prevention and Treatment, 1995, 22(6): 357-358. |
| [9] | zhan wanyu, . Intrapleural and intraabdomin injection of Lentinan (macle in China) for malignant pleural effusion and ascites-An clinical report of 16 cases[J]. Cancer Research on Prevention and Treatment, 1994, 21(6): 370-371. |
| [10] | Yang Shan-zhon. DIAGNOSTIC VALUE OF ASSAY CA-50 COMBINED WITH DIAMINEOXIDASE IN MALIGNANT AND BENIGN EFFUSION[J]. Cancer Research on Prevention and Treatment, 1994, 21(1): 43-45. |
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