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Received:June 02, 2023 Published Online:November 20, 2023
Received:June 02, 2023 Published Online:November 20, 2023
中文摘要: 目的 研究人工智能（AI）系统与甲状腺影像报告和数据系统（TI-RADS）在甲状腺肿瘤良恶性诊断中的价值。方法 构建AI系统，并回顾性分析2020年1月至2021年12月徐州市中心医院行甲状腺外科手术的患者共500例，收集患者基本信息、手术信息、AI分级指标、TI-RADS分级、术后病理情况，比较AI及TI-RADS预测甲状腺癌的准确率。结果 500例患者中，甲状腺癌390例，良性结节110例。AI预测甲状腺癌准确率为88.5%，预测良性肿瘤准确率为87.3%，总体准确率为88.2%。TI-RADS预测甲状腺癌准确率为80.3%，预测良性肿瘤准确率为80.9%，总体预测准确率为80.4%。AI系统对恶性、总体预测准确率均高于TI-RADS组，差异有统计学意义（P＜0.05）。AI系统对乳头状癌的预测准确率高于TI-RADS（89.9% vs 81.2%， χ2=10.525，P＜0.05），对滤泡状癌、髓样癌、未分化癌的预测准确率与TI-RADS差异无统计学意义（P＞0.05）。结论 AI系统与TI-RADS在甲状腺癌的诊断中有着重要的价值，AI系统比TI-RADS具有更高的准确率，并且在甲状腺癌不同亚型中有着类似的结果。
中文关键词: 甲状腺癌 人工智能 甲状腺影像报告和数据系统 乳头状癌 超声检查
Abstract:Objective To study the value of artificial intelligence (AI) systems and Thyroid Imaging Reporting and Data System (TI-RADS) in the diagnosis of benign and malignant thyroid tumors. Methods An AI system was developed, and a retrospective analysis was conducted on 500 patients who underwent thyroid surgery at Xuzhou Central Hospital from January 2020 to December 2021. Patient demographics, surgical information, AI grading indicators, TI-RADS classifications, and postoperative pathological findings were collected. The accuracy of AI and TI-RADS in predicting thyroid cancer was compared. Results Among the 500 patients, 390 were diagnosed with thyroid cancer and 110 were benign nodules. The AI achieved an accuracy of 88.5% in predicting thyroid cancer and 87.3% in predicting benign tumors, with an overall accuracy of 88.2%. The TI-RADS had a predictive accuracy of 80.3% for thyroid cancer and 80.9% for benign tumors, with an overall predictive accuracy of 80.4%. The AI group had higher accuracy rates for malignancy and overall prediction compared to the TI-RADS group (P＜0.05). The AI system had a higher accuracy rate for predicting papillary carcinoma compared to the TI-RADS (89.9% vs 81.2%, χ2=10.525，P＜0.05), while no statistically significant differences were found in predicting follicular carcinoma, medullary carcinoma, and undifferentiated carcinoma compared to TI-RADS (P＞0.05). Conclusion Both the AI system and TI-RADS have significant value in the diagnosis of thyroid cancer. The AI system demonstrates higher accuracy compared to the TI-RADS grading system, and similar results are observed in different subtypes of thyroid cancer.
keywords: Thyroid cancer Artificial intelligence Thyroid Imaging Reporting and Data System Papillary carcinoma Ultrasonic examination
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基金项目:徐州医科大学附属医院科技发展基金（XYFY2020045）
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