The aim of this study was to identify independent risk factors for thyroid cancer, establish an ultrasonographic multimodality diagnostic model for thyroid nodules, and explore the diagnostic value of the model. From November 2011 to February 2015, 307 patients with a total of 367 thyroid nodules underwent conventional ultrasound, contrast-enhanced ultrasound (CEUS), and ultrasound elastography examinations before surgery. A binary logistic regression analysis was performed to identify independent risk factors for thyroid cancer and to establish a multimodality diagnostic model for thyroid nodules. The diagnostic performance of conventional ultrasound, CEUS, ultrasound elastography, and the multimodality diagnostic model was assessed and compared. The following seven independent risk factors were included in the logistic regression models: age, irregular shape, hypoechoic pattern, marked hypoechoic pattern, irregular blood flow distribution, heterogeneous enhancement, and an elastic score of 3/4. The multimodality diagnostic model had a diagnostic accuracy of 86.9%, with a sensitivity of 93.5% and a specificity of 77.3%. The multimodality diagnostic model improved the diagnostic accuracy compared with that of conventional ultrasound, CEUS, and ultrasound elastography. Independent risk factors for thyroid cancer included age, irregular shape, hypoechoic pattern, marked hypoechoic pattern, irregular blood flow distribution, heterogeneous enhancement, and an elastic score of 3/4. The multimodality diagnostic model was demonstrated to be effective in the diagnosis of thyroid nodules.

中文翻译：

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甲状腺结节的超声多模态诊断模型

本研究旨在识别甲状腺癌的独立危险因素，建立甲状腺结节超声多模态诊断模型，并探讨该模型的诊断价值。2011年11月至2015年2月，307例患者共367个甲状腺结节在术前接受了常规超声、对比增强超声（CEUS）和超声弹性成像检查。进行二元逻辑回归分析以确定甲状腺癌的独立危险因素并建立甲状腺结节的多模态诊断模型。对常规超声、CEUS、超声弹性成像和多模态诊断模型的诊断性能进行了评估和比较。Logistic 回归模型中包括以下七个独立的危险因素：年龄、不规则形状，低回声模式，明显低回声模式，不规则血流分布，不均匀增强，弹性评分为3/4。多模态诊断模型的诊断准确率为86.9%，敏感性为93.5%，特异性为77.3%。与常规超声、CEUS 和超声弹性成像相比，多模态诊断模型提高了诊断准确性。甲状腺癌的独立危险因素包括年龄、不规则形状、低回声模式、显着低回声模式、不规则血流分布、不均匀增强和 3/4 的弹性评分。多模态诊断模型被证明在甲状腺结节的诊断中是有效的。异质性增强，弹性评分为 3/4。多模态诊断模型的诊断准确率为86.9%，敏感性为93.5%，特异性为77.3%。与常规超声、CEUS 和超声弹性成像相比，多模态诊断模型提高了诊断准确性。甲状腺癌的独立危险因素包括年龄、不规则形状、低回声模式、显着低回声模式、不规则血流分布、不均匀增强和 3/4 的弹性评分。多模态诊断模型被证明在甲状腺结节的诊断中是有效的。异质性增强，弹性评分为 3/4。多模态诊断模型的诊断准确率为86.9%，敏感性为93.5%，特异性为77.3%。与常规超声、CEUS 和超声弹性成像相比，多模态诊断模型提高了诊断准确性。甲状腺癌的独立危险因素包括年龄、不规则形状、低回声模式、显着低回声模式、不规则血流分布、不均匀增强和 3/4 的弹性评分。多模态诊断模型被证明在甲状腺结节的诊断中是有效的。与常规超声、CEUS 和超声弹性成像相比，多模态诊断模型提高了诊断准确性。甲状腺癌的独立危险因素包括年龄、不规则形状、低回声模式、显着低回声模式、不规则血流分布、不均匀增强和 3/4 的弹性评分。多模态诊断模型被证明在甲状腺结节的诊断中是有效的。与常规超声、CEUS 和超声弹性成像相比，多模态诊断模型提高了诊断准确性。甲状腺癌的独立危险因素包括年龄、不规则形状、低回声模式、显着低回声模式、不规则血流分布、不均匀增强和 3/4 的弹性评分。多模态诊断模型被证明在甲状腺结节的诊断中是有效的。