胸腺上皮性肿瘤CT特征与风险度及病理分型的相关性研究

    Study on the correlation between CT features and risk degree, pathological classification of thymus epithelial tumors

    • 摘要:
      目的 探讨胸腺上皮性肿瘤(TETs) CT影像特征与病理分型及风险分类的相关性。
      方法 回顾性分析经病理证实为TETs的术前临床及影像资料,比较TETs一般资料及CT特征与病理分型及风险分类的相关性,二元logisitic回归分析高风险TETs的独立危险因素,绘制预测TETs病人高风险的列线图,采用ROC曲线验证列线图模型的准确性。
      结果 年龄、胸痛、外缘、钙化、分隔、强化幅度、心包膜增厚、纵隔淋巴结转移、周围脂肪浸润在不同病理分型间存在差异(P < 0.05)。胸痛、形态、外缘、密度、坏死/囊变、钙化、动脉期CT值、静脉期CT值、强化幅度、心包膜增厚、胸膜增厚、纵隔淋巴结转移、周围脂肪浸润、包绕纵隔结构及侵犯周围血管在低风险组及高风险组间差异有统计学意义(P < 0.05)。胸痛、外缘及心包膜增厚是高风险TETs的独立危险因素,ROC分析列线图模型AUC为0.818(95%CI: 0.712~0.897,P < 0.01)。
      结论 结合临床及CT特征在一定程度上可预测TETs病理分型,由胸痛、外缘及心包膜增厚三个因素构建的列线图模型对TETs高风险病人的预测效能较好。

       

      Abstract:
      Objective To explore the correlation between CT features and pathological types, risk classification of thymus epithelial tumors(TETs).
      Methods The preoperative clinical and imaging data of patients with TETs proved by pathology were retrospectively analyzed, and the correlation between general data and CT features of TETs and pathological classification, risk classification were compared.Binary logisitic regression was used to analyze the independent risk factors of high-risk TETs, and a nomogram was drawn to predict the high risk of TETs patients.ROC curve was used to verify the accuracy of the nomogram model.
      Results The differences of the age, chest pain, peripheral margin, calcification, separation, enhancement amplitude, pericardium thickening, mediastinal lymph node enlargement, surrounding fat infiltration and surrounding mediastinal structure among different pathological types were statistically significnat(P < 0.05).The differences of the chest pain, morphology, outer margin, density, necrosis/cystic change, calcification, arterial CT value, venous CT value, enhancement amplitude, pericardial thickening, pleural thickening, mediastinal lymph node metastasis, peripheral fat infiltration, encircling mediastinal structure and invasion of peripheral blood vessels between the low and high risk groups were were statistically significnat(P < 0.05).The chest pain, outer margin and pericardial thickening were the independent risk factors of high risk TETs, and the AUC of the ROC curve for nomogram model was 0.818(95%CI: 0.712-0.897, P < 0.01).
      Conclusions Combined with clinical and CT features, the pathological classification of TETs can be predicted to a certain extent, and the nomogram model constructed by chest pain, peripheral margin and pericardial thickening has better predictive efficacy in patients with high risk of TETs.

       

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