摘要
目的 探讨术前MRI影像学特征联合血清炎症因子预测乳腺浸润性导管癌病理分级的诊断效能。方法 回顾性收集2021年12月~2024年3月盐城市第一人民医院127例乳腺浸润性导管癌患者,根据病理分级分为低级别组(n=76)与高级别组(n=51)。患者术前行MRI及血常规检查,收集临床指标包括年龄、淋巴细胞、单核细胞、中性粒细胞和血小板计数,计算衍生指标中性粒细胞-淋巴细胞比值(NLR)、血小板-淋巴细胞比值(PLR)、淋巴细胞-单核细胞比值(LMR)和全身免疫炎症指数(SII);收集影像学特征包括肿瘤最大径、肿瘤形态、位置、象限、实质强化特点、MRI报告腋窝淋巴结状态、时间-信号强度曲线类型、BI-RADS分类。比较两组间临床影像学特征的差异,采用Spearman相关性分析临床影像学特征与乳腺癌病理分级的相关性。结果 NLR、SII、肿瘤最大径、BI-RADS分类在低级别与高级别组间的差异有统计学意义(P<0.05),与病理分级均呈正相关(P<0.05),其中SII预测乳腺癌病理分级的诊断效能最高(AUC=0.663);联合4个特征后,诊断效能提升(AUC=0.750)。结论 MRI影像特征联合血清炎症因子对预测乳腺癌病理分级具有一定临床价值。
Objective To investigate the diagnostic efficacy of preoperative MRI features combined with serum inflammatory factors in predicting the pathological grading of breast invasive ductal carcinoma.Methods A retrospective analysis was conducted on 127 patients diagnosed with breast invasive ductal carcinoma at Yancheng First People's Hospital from December 2021 to March 2024.Based on pathological grading,the cohort was stratified into a low-grade group(n=76)and a high-grade group(n=51).Patients underwent preoperative MRI and blood routine examinations.Clinical indicators including age,lymphocyte,monocyte,neutrophil and platelet counts were collected,and derived indicators neutrophil-lymphocyte ratio(NLR),platelet-lymphocyte ratio(PLR),lymphocyte-monocyte ratio(LMR)and systemic immune-inflammation index(SII)were calculated.Radiological features included maximum tumor diameter,tumor morphology,location,quadrant,parenchymal enhancement characteristics,MRI-reported axillary lymph node status,time-signal intensity curve type,and BI-RADS classification.The differences in clinical and radiological features between the two groups were compared,and Spearman correlation were used to analyze the correlation between clinical-radiological features and pathological grading of breast cancer.Results There were statistically significant differences in NLR,SII,maximum tumor diameter and BI-RADS classification between the low and high grade groups(P<0.05),and all of them were positively correlated with pathological grading(P<0.05).Among them,SII had the highest diagnostic efficacy in predicting the pathological grading of breast cancer,with an AUC of 0.663.The diagnostic efficacy was improved by combining the four features,with an AUC of 0.750.Conclusion The combination of MRI features and serum inflammatory factors has clinical value in predicting the pathological grading of breast cancer.
作者
汪洁
王曼曼
耿其楠
WANG Jie;WANG Manman;GENG Qinan(School of Medical Imaging,Jiangsu Vocational College of Medicine,Yancheng 224005,China;Department of Imaging,Yancheng First People's Hospital,Yancheng 224000,China)
出处
《分子影像学杂志》
2025年第9期1150-1156,共7页
Journal of Molecular Imaging
基金
盐城市科技局基础研究计划项目(YCBK2023029)。
关键词
乳腺浸润性导管癌
MRI
炎症因子
病理分级
breast invasive ductal carcinoma
MRI
inflammatory factors
pathological grade
