| 摘要: |
| 目的 探讨基于临床资料和超声图像特征构建乳腺非肿块型病变(NML)恶性风险预测模型的价值。方法 选取2020年1月至2023年2月在我院治疗的NML患者78例78个病灶,分析良恶性NML患者临床资料、超声特性差异,构建预测恶性NML的风险模型。结果 78例患者中,恶性36例,良性42例；恶性病变中以浸润性癌为主,良性病变中以纤维囊性乳腺病为主；恶性病变患者年龄≥50岁比例为63.89%,高于良性病变患者(P＜0.05)；恶性病变患者有哺乳史比例为19.44%,低于良性病变患者(P＜0.05)；恶性病变患者有乳腺癌家族史比例为44.44%,高于良性病变患者(P＜0.05)；恶性病变患者CEA＞2.1 ng/ml比例为58.33%,高于良性病变患者(P＜0.05)；恶性病变患者CA15-3＞18.7 U/ml比例为63.89%,高于良性病变患者(P＜0.05)；恶性病变患者miR-194＞1.60比例为72.22%,高于良性病变患者(P＜0.05)；恶性病变患者有结构扭曲、血流信号Ⅱ～Ⅲ、有后方回声衰减、有微钙化比例分别为44.44%、41.67%、52.78%和66.67%,高于良性病变患者(P＜0.05)；Logistic回归分析显示：乳腺癌家族史、结构扭曲、血流信号、后方回声衰减、、CEA、CA15-3和miR-194是NML恶性的影响因素(P＜0.05)；方程预测恶性NML的ROC曲线下面积为0.846(95%CI：0.762～0.930),P＜0.05,灵敏性和特异性分别为73.50%和77.30%。结论 基于临床资料和超声图像特征构建预测恶性NML模型有一定的应用价值,值得临床进一步研究。 |
| 关键词: 乳腺非肿块型病变 良性 恶性 预测价值 超声 |
| DOI： |
| 投稿时间：2024-01-09修订日期：2024-04-18 |
| 基金项目:湖北省卫生健康委员会联合课题编号：WJ2019H179 |
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| The predictive value of ultrasound image feature construction for malignant breast non mass lesions |
| shengrong,wuyiping |
| () |
| Abstract: |
| Objective: To explore the value of constructing a malignant risk prediction model for non mass breast lesions (NML) based on clinical data and ultrasound image features. Methods: 78 lesions from 78 patients with NML who were treated in our hospital from January 2020 to February 2023 were selected to analyze the clinical data and ultrasound characteristics differences between benign and malignant NML patients, and to construct a risk model for predicting malignant NML. Results: Among the 78 patients, 36 were malignant and 42 were benign. Malignant lesions are mainly infiltrating carcinoma, while benign lesions are mainly fibrocystic breast disease. The proportion of malignant disease patients aged ≥ 50 years old was 63.89%, which was higher than that of benign disease patients (P<0.05). The proportion of patients with malignant lesions who have a history of breastfeeding was 19.44%, which was lower than that of patients with benign lesions (P<0.05). The family history of breast cancer in patients with malignant lesions was 44.44%, which was higher than that in patients with benign lesions (P<0.05). The proportion of CEA>2.1 ng/ml in patients with malignant lesions was 58.33%, which was higher than that in patients with benign lesions (P<0.05).The proportion of CA15-3>18.7 U/ml in patients with malignant lesions was 63.89%, which was higher than that in patients with benign lesions (P<0.05). The proportion of malignant disease patients with miR-194>1.60 was 72.22%, which was higher than that of benign disease patients (P<0.05).The proportion of malignant lesions with structural distortion, blood flow signals II-III, posterior echo attenuation, and microcalcification was 44.44%, 41.67%, 52.78%, and 66.67%, respectively, which was higher than that of benign lesions (P<0.05). Logistic regression analysis showed that family history of breast cancer, structural distortion, blood flow type and posterior echo attenuation,CEA,CA15-3 and miR-194 were the influencing factors of NML malignancy (P<0.05), the area under the ROC curve predicted by the equation for malignant NML was 0.846 (95% CI: 0.762-0.930), P<0.05, sensitivity and specificity were 73.50% and 77.30%, respectively. Conclusion: Building a predictive model for malignant NML based on clinical data and ultrasound image features has certain application value and is worthy of further clinical research. |
| Key words: Non mass breast lesions Benign Malignant Predicted value ultrasonic |
