^(18)F-FDG PET/CT代谢参数预测乳腺癌腋窝淋巴结转移的价值  

Prediction of ^(18)F-FDG PET/CT Metabolic Parameters in Axillary Lymph Node Metastasis of Breast Cancer

作　　者：陈丹丹 楼云龙[1] 林政 CHEN Dandan;LOU Yunlong;LIN Zheng(Department of Nuclear Medicine,Meizhou People's Hospital,Meizhou 514013)

机构地区：[1]梅州市人民医院核医学科,广东梅州514013

出　　处：《中国医学影像学杂志》2024年第10期1027-1031,共5页Chinese Journal of Medical Imaging

基　　金：梅州市科技计划项目(221208162057340);梅州市人民医院科研培育项目(PY-C2021055)。

摘　　要：目的基于乳腺癌相关代谢参数建立无创性预测腋窝淋巴结转移(ALNM)的模型。资料与方法回顾性选取梅州市人民医院2016年1月1日—2023年3月30日诊断为乳腺癌且术前在我科行^(18)F-FDG PET/CT检查的患者158例,获取乳腺癌原发灶代谢参数[最大标准化摄取值(SUVmax)、代谢体积、糖酵解总量(TLG)]、腋窝摄取最高淋巴结SUVmax(SUVmax ALN)、腋窝淋巴结短径及临床相关指标[年龄、肿瘤最大径、病理类型、肿瘤位置]。根据手术病理结果将患者分为ALNM阳性组[ALNM(+)]和ALNM阴性组[ALNM(-)],分析两组间各参数的关系,筛选出最佳影响因素,并利用二元Logistic回归建立预测模型。结果两组间乳腺癌原发灶的TLG、代谢体积、腋窝淋巴结短径及SUVmax ALN差异有统计学意义(Z=-3.924~-1.812,P均<0.05),而年龄、肿瘤最大径、病理类型、肿瘤位置、原发灶SUVmax及SUV平均值差异无统计学意义(P均>0.05)。多因素二元Logistic回归分析显示,乳腺癌原发灶的TLG及SUVmax ALN可作为乳腺癌ALNM的独立危险因素,使用这两个因素建立回归模型为Logit(P)=0.142+0.443×SUVmax ALN-0.013×TLG。以TLG及SUVmax ALN构建的ALNM预测模型曲线下面积为0.769(95%CI 0.691~0.841,P<0.001)。结论乳腺癌原发灶的TLG及SUVmax ALN可作为独立预测乳腺癌ALNM的因素,基于这两个因素建立的预测模型可以较好地预测ALNM,该非侵入性的方法在临床可能有一定应用前景。Purpose To establish a non-invasive model for predicting axillary lymph node metastasis(ALNM)based on breast cancer related metabolic parameters.Materials and Methods A total of 158 patients diagnosed as breast cancer in Meizhou People's Hospital from January 1,2016 to March 30,2023 were selected,and all of them underwent whole-body PET/CT examination in our department before operation.Metabolic parameters of primary breast cancer[maximum standard uptake value(SUVmax),metabolic volume,total glycolysis(TLG)],highest axillary lymph node uptake SUVmax(SUVmaxALN),axillary lymph node short diameter and clinical related indexes[age,maximum tumor diameter,pathological type and tumor location]were obtained.According to the surgical and pathological results,the patients were divided into ALNM positive[ALNM(+)]group and ALNM negative[ALNM(-)]group.The relationship between the parameters of the two groups was analyzed,the best influencing factors were screened out,and binary Logistic regression was used to establish a prediction model to obtain the primary metabolic parameters of breast cancer.Results There were significant differences in TLG,metabolic volume,axillary lymph node short diameter and SUVmaxALN between ALNM(+)group and ALNM(-)group(Z=-3.924--1.812,all P<0.05),but there were no significant differences in age,tumor maximum diameter,pathological type,tumor location,primary focus SUVmax and SUVavg(all P>0.05).Multivariate Logistic regression analysis showed that TLG of breast cancer primary focus and SUVmaxALN could be used as independent risk factors of ALNM of breast cancer,and the regression model established by using these two factors was Logit(P)=0.142+0.443×SUVmaxALN-0.013×TLG.The area under the curve of ALNM prediction model based on TLG and SUVmaxALN was 0.769(95%CI 0.691-0.841,P<0.001).Conclusion TLG of breast cancer primary focus and SUVmaxALN can be used as independent predictors of ALNM of breast cancer,and the prediction model based on these two factors can predict ALNM well.This non-invasive method

关 键 词：乳腺肿瘤 正电子发射计算机断层摄影术 淋巴转移 预测 

分 类 号：R737.9[医药卫生—肿瘤] R445.4[医药卫生—临床医学]