临床外科杂志 ›› 2025, Vol. 33 ›› Issue (11): 1180-1183.doi: 10.3969/j.issn.1005-6483.20241175

• 论著 • 上一篇    下一篇

基于多模态影像的乳腺癌新辅助化疗效果的预测模型建立

  

  1. 261000  山东潍坊,潍坊市中医院乳腺甲状腺外科(宋以宁、邵光东、孙政、史明明),病理科(王晓琳),医学影像中心(李芹) 
  • 收稿日期:2024-07-16 接受日期:2024-07-16 出版日期:2025-11-20 发布日期:2025-11-20
  • 通讯作者: 史明明,Email:Kangren.2008@163.com
  • 基金资助:
    2022年潍坊市卫健委科研项目(WDWSJK-2022-095)

Establishment of a prediction model for the effect ofneoadjuvant chemotherapy in breast cancer based on multimodal imaging

  1. Department of Breast and Thyroid Surgery,Weifang Traditional Chinese Medicine Hospital,Weifang 261000,China
  • Received:2024-07-16 Accepted:2024-07-16 Online:2025-11-20 Published:2025-11-20

摘要: 目的 构建并验证基于多模态影像的乳腺癌新辅助化疗效果的预测模型。方法 2020年1月~2024年4月收治的乳腺癌伴同侧腋窝淋巴结转移病人121例,新辅助化疗后行手术切除,统计病理完全缓解(pCR)情况。新辅助化疗前后行磁共振、乳腺超声、钼靶检查,Logistic回归分析乳腺癌病人新辅助化疗效果的影响因素,基于影响因素构建多模态影像的乳腺癌新辅助化疗效果预测模型并进行模型的验证及效能评估。结果 有28例达到pCR。Logistic回归分析显示,肿瘤分期(OR=4.899,95%CI:2.016~11.909)、△表观扩散系数(ADC)(OR=4.419,95%CI:1.818~10.741)、△达峰时间(TTP)(OR=3.644,95%CI:1.499~8.855)是影响乳腺癌病人新辅助化疗效果的因素(P<0.05)。以上述影响因素作为预测变量建立列线图预测模型,风险率范围0.56~0.68。列线图模型验证结果显示,预测乳腺癌新辅助化疗效果的校正曲线趋近于理想曲线(P>0.05)。ROC曲线显示,列线图模型预测乳腺癌新辅助化疗效果的灵敏度78.57%,特异性为83.87%,AUC为0.851(95%CI:0.767~0.927)。结论 肿瘤分期、△ADC、△TTP与乳腺癌病人新辅助化疗效果密切相关,基于多模态影像构建乳腺癌新辅助化疗效果的预测模型预测效能良好。

关键词: 乳腺癌, 多模态影像, 新辅助化疗

Abstract: Objective To construct and validate a multimodal imagebased prediction model for the efficacy of neoadjuvant chemotherapy in breast cancer.Methods  The 121 patients with breast cancer with ipsilateral axillary lymph node metastasis admitted to the hospital from January 2020 ~ April 2024 were reviewed.The patient underwent surgical resection after neoadjuvant chemotherapy and the pathological complete response (pCR) was counted.High-resolution MRI,breast ultrasound and mammography were performed before and after neoadjuvant chemotherapy.Logistic regression was used to analyze the influencing factors of the neoadjuvant chemotherapy effect in breast cancer patients,and a multimodal imaging based on multimodal imaging was constructed to predict the effect of neoadjuvant chemotherapy for breast cancer,and the model was verified and evaluated for efficacy.Results  Twenty-eight cases achieved pCR.Logistic regression analysis showed that tumor stage (OR=4.899,95%CI:2.016~11.909),△apparent diffusion coefficient (ADC) (OR=4.419,95%CI:1.818~10.741),and △ time to peak (TTP) (OR=3.644,95%CI:1.499~8.855) were the factors affecting the effect of neoadjuvant chemotherapy in breast cancer patients (P<0.05).The nomogram prediction model was established with the above influencing factors as predictors,and the risk rate ranged from 0.56~0.68.The results of nomogram model validation showed that the calibration curve for predicting the effect of neoadjuvant chemotherapy for breast cancer was close to the ideal curve (P>0.05).The ROC curve showed that the nomogram model had a sensitivity of 78.57%,a specificity of 83.87%,and an AUC of 0.851 (95%CI:0.767~0.927) in predicting the effect of neoadjuvant chemotherapy in breast cancer.Conclusion Tumor stage,△ADC and △TTP are closely related to the effect of neoadjuvant chemotherapy in breast cancer patients,and the prediction model of neoadjuvant chemotherapy effect based on multimodal imaging has good predictive performance.

Key words: breast cancer, multimodal image, neoadjuvant chemotherapy

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