人工智能辅助评分系统联合超声弹性成像诊断甲状腺结节良恶性的价值

Value of artificial intelligence assisted scoring system combined with ultrasound elastography in the diagnosis of benign and malignant thyroid nodules

  • 摘要:
      目的  分析人工智能辅助评分系统联合超声弹性成像在甲状腺结节良恶性诊断中的应用价值。
      方法  纳入甲状腺结节患者414例(共543个结节),分别使用甲状腺人工智能辅助评分系统和超声弹性成像技术对甲状腺结节进行分析,记录人工智能评分(AIAS)、应变率比值(SR)。对甲状腺良恶性结节的AIAS和SR进行二元Logistic回归分析,计算联合诊断预测因子。绘制受试者工作特征(ROC)曲线,分析AIAS、SR和两者联合诊断对甲状腺结节良恶性的价值。
      结果  543个结节中,病理检查结果证实恶性病变339个(62.43%),良性病变204个(37.57%)。良性结节的AIAS、SR和联合预测因子均低于恶性结节,差异有统计学意义(P < 0.05)。联合诊断的曲线下面积(AUC)高于AIAS和SR,差异有统计学意义(P < 0.05)。
      结论  人工智能辅助评分系统和超声弹性成像在单独诊断甲状腺结节良恶性中均具有一定的局限性,两者联合应用对甲状腺结节性质的诊断价值更高。

     

    Abstract:
      Objective  To analyze the value of artificial intelligence assisted scoring system combined with ultrasound elastography in the diagnosis of benign and malignant thyroid nodules.
      Methods  Totally 414 patients with 543 thyroid nodules were enrolled in the study. The thyroid nodules were analyzed by artificial intelligence scoring system and ultrasound elastography, and the artificial intelligence assisted score (AIAS) and ratio of strain rate (SR) were recorded. Binary Logistic regression analysis was performed on AIAS and SR of benign and malignant thyroid nodules to calculate the combined diagnostic predictors. The receiver operating characteristic (ROC) curve was drawn to analyze the value of AIAS, SR and their combination in the diagnosis of benign and malignant thyroid nodules.
      Results  Of the 543 nodules, 339 nodules (62.43%) were malignant and 204 nodules (37.57%) were benign. The AIAS, SR and combined predictors of benign nodules were significantly lower than those of malignant nodules (P < 0.05). Area under curve (AUC) of combined diagnosis was significantly higher than that of AIAS and SR (P < 0.05).
      Conclusion  Both artificial intelligence assisted scoring system and ultrasound elastography have certain limitations in the diagnosis of benign and malignant thyroid nodules, but the combination of the two methods is more valuable in the diagnosis of nature of thyroid nodules.

     

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