牛奇林, 陈路, 段惠予, 汤晓敏, 杨丽, 马诚诚, 谢宗玉, 高之振, 陈建方. 基于乳腺X线摄影的诺莫图预测可疑钙化的恶性风险[J]. 蚌埠医学院学报, 2023, 48(8): 1085-1089. DOI: 10.13898/j.cnki.issn.1000-2200.2023.08.016
    引用本文: 牛奇林, 陈路, 段惠予, 汤晓敏, 杨丽, 马诚诚, 谢宗玉, 高之振, 陈建方. 基于乳腺X线摄影的诺莫图预测可疑钙化的恶性风险[J]. 蚌埠医学院学报, 2023, 48(8): 1085-1089. DOI: 10.13898/j.cnki.issn.1000-2200.2023.08.016
    NIU Qi-lin, CHEN Lu, DUAN Hui-yu, TANG Xiao-min, YANG Li, MA Cheng-cheng, XIE Zong-yu, GAO Zhi-zhen, CHEN Jian-fang. A mammography-based nomogram for predicting the risk of malignancy in suspicious calcifications[J]. Journal of Bengbu Medical College, 2023, 48(8): 1085-1089. DOI: 10.13898/j.cnki.issn.1000-2200.2023.08.016
    Citation: NIU Qi-lin, CHEN Lu, DUAN Hui-yu, TANG Xiao-min, YANG Li, MA Cheng-cheng, XIE Zong-yu, GAO Zhi-zhen, CHEN Jian-fang. A mammography-based nomogram for predicting the risk of malignancy in suspicious calcifications[J]. Journal of Bengbu Medical College, 2023, 48(8): 1085-1089. DOI: 10.13898/j.cnki.issn.1000-2200.2023.08.016

    基于乳腺X线摄影的诺莫图预测可疑钙化的恶性风险

    A mammography-based nomogram for predicting the risk of malignancy in suspicious calcifications

    • 摘要:
      目的绘制预测乳腺可疑钙化恶性风险的诺莫图用于指导临床决策。
      方法回顾性分析经乳腺X线摄影发现的乳腺微钙化且行影像引导下定位病人178例资料。所有钙化都由乳腺放射学家根据第5版BI-RADS进行分类。采用单因素和多因素logistic回归分析钙化影像特征及病人临床特征的关系。在多变量logistic回归分析的基础上, 绘制诺莫图预测恶性肿瘤风险, 并采用ROC曲线分析模型的诊断效果。
      结果178例表现为微钙化的病人中可疑钙化有114例, 可疑钙化组中, < 50岁组与≥ 50岁组、无定形/粗糙不均质钙化与细小多形性/细线样或细分枝状钙化、钙化分布中区域性/团簇状与呈线样/段样分布的钙化, 恶性率差异均有统计学意义(P < 0.01)。年龄≥ 50岁、钙化类型为细小多形性/细线样或细分枝状、钙化分布为线段样是恶性病变的独立危险因素, 基于这3个因素建立了预测诺莫图, 曲线下面积为0.747(95%CI: 0.658~0.836)。
      结论在乳腺癌的早期诊断中, 乳腺微钙化病变的影像引导定位活检具有一定价值。可疑微钙化的形态学描述子分类是必需的, 结合可疑微钙化的形态学和分布描述符的诺莫图可准确的预测恶性风险。

       

      Abstract:
      ObjectiveTo establish a nomogram to predict the risk of malignancy of suspicious calcifications in the breast for guiding clinical decision making.
      MethodsA total of 178 patients with breast microcalcifications detected by mammography and localized with image guidance was retrospectively analyzed.All calcifications were classified by a breast radiologist according to the fifth edition of BI-RADS.Univariate and multivariate logistic regression were used to analyze the relationship between the imaging features of calcifications and the clinical features of patients.Based on multivariate logistic regression analysis, a nomogram was developed to predict the risk of malignancy, and the corresponding diagnostic efficiency of the model was evaluated using ROC curves.
      ResultsAmong the 178 patients with microcalcification, 114 were suspected of calcification.In the suspected calcification group, there were statistically significant differences in malignancy rates among the < 50 years old and ≥50 years old groups(P < 0.01), amorphous/coarse heterogeneous calcification and fine pleomorphic/fine linear or subdivided dendritic calcification, regional/clustered calcification and linear/segmental calcification in the distribution of calcification(P < 0.01).Age≥50 years old, calcification type of fine pleomorphism/fine line or fine branch, and calcification distribution of line segment were independent risk factors of malignant lesions.Based on these three factors, a predictive nomogram was established, and the corresponding area under the curve was 0.747 (95%CI: 0.658-0.836).
      ConclusionsIn early diagnosis of breast cancer, image-guided localized biopsy of breast microcalcifications has certain value.Morphological descriptors of suspicious microcalcifications are required for subclassification, and a nomogram combining morphology and distribution descriptors of suspicious microcalcifications can accurately predict the risk of malignancy.

       

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