首页|期刊导航|新医学|PET/CT影像组学鉴别肿瘤标志物阴性且FDG摄取阳性孤立性肺结节的临床价值

PET/CT影像组学鉴别肿瘤标志物阴性且FDG摄取阳性孤立性肺结节的临床价值OA

Clinical value of PET/CT radiomics in differentiating tumor marker-negative,FDG-avid solitary pulmonary nodules

中文摘要英文摘要

目的 探讨18F-氟代脱氧葡萄糖(18F-FDG)正电子发射断层扫描/计算机断层扫描(PET/CT)影像组学模型在鉴别肿瘤标志物阴性、FDG摄取阳性孤立性肺结节良恶性中的临床价值.方法 收集 2019年 1月至 2024年 12月保定市第一中心医院收治的 130例此类肺结节患者资料,按 7∶3比例随机分为训练集(n=91)与内部测试集(n=39).另从 TCIA 公共数据库中收集符合条件的独立病例作为外部验证集(n=45).使用 LIFEx软件提取 PET及CT 影像组学特征,经组内相关系数(ICC)稳定性评估、Spearman相关性分析及 LASSO 回归筛选核心特征.分别构建逻辑回归(LR)、随机森林(RF)和支持向量机(SVM)模型,采用受试者操作特征(ROC)曲线与决策曲线分析(DCA)评估并比较各模型性能.结果 最终筛选出 8个关键影像组学特征(PET与 CT各 4个).在内部测试集中,LR模型效能最优,且曲线下面积(AUC)为 0.819(95%CI 为 0.738~0.892),灵敏度与特异度分别为 0.792与 0.800.在外部验证集中,LR模型仍保持最佳鉴别性能,AUC为 0.801(95%CI 为 0.713~0.905),优于 RF 模型(AUC=0.721,P=0.041)与 SVM模型(AUC=0.717,P=0.028).DCA 显示,LR模型在内部测试集及外部验证集中均能提供较高的临床净获益.结论 针对肿瘤标志物阴性且 FDG摄取阳性的难辨性孤立性肺结节,PET/CT 影像组学模型(尤其是LR模型)具有良好的鉴别效能与泛化能力,可为术前决策提供客观的量化参考.

Objective To investigate the clinical value of an 18F-FDG PET/CT radiomics model in differentiating benign from malignant solitary pulmonary nodules with negative tumor markers and positive FDG uptake.Methods The data of 130 patients with such pulmonary nodules admitted to Baoding No.1 Central Hospital from January 2019 to December 2024 were collected.The patients were randomly divided into a training set(n=91)and an internal test set(n=39)at a ratio of 7:3.Eligible independent cases were additionally collected from the Cancer Imaging Archive(TCIA)public database as an external validation set(n=45).PET and CT radiomics features were extracted using LIFEx software.Core features were selected through intraclass correlation coefficient(ICC)stability assessment,Spearman correlation analysis,and least absolute shrinkage and selection operator(LASSO)regression.Logistic regression(LR),random forest(RF),and support vector machine(SVM)models were constructed separately.Receiver operating characteristic(ROC)curves and decision curve analysis(DCA)were used to evaluate and compare the performance of the models.Results A total of 8 key radiomics features were ultimately selected,including 4 PET features and 4 CT features.In the internal test set,the LR model showed the best performance,with an area under the curve(AUC)of 0.819(95%CI:0.738-0.892),a sensitivity of 0.792,and a specificity of 0.800.In the external validation set,the LR model also maintained the best discriminative performance,with an AUC of 0.801(95%CI:0.713-0.905),which was significantly higher than those of the RF model(AUC=0.721,P=0.041)and the SVM model(AUC=0.717,P=0.028).DCA demonstrated that the LR model yielded greater clinical net benefit in both the internal test set and the external validation set.Conclusions For difficult-to-differentiate solitary pulmonary nodules with negative tumor markers and high FDG uptake,PET/CT radiomics models,particularly the LR model,have good discriminative performance and generalizability and can provide an objective quantitative reference for preoperative decision-making.

张建媛;席永昌;尤立强;张建阳;张力丹;田晓媛

保定市第一中心医院核医学科,河北 保定 071000保定市第一中心医院核医学科,河北 保定 071000保定市第一中心医院核医学科,河北 保定 071000保定市第一中心医院核医学科,河北 保定 071000保定市第一中心医院核医学科,河北 保定 071000保定市第一中心医院核医学科,河北 保定 071000

医药卫生

肺结节正电子发射计算机断层显像影像组学预测模型肿瘤标志物阴性

Solitary pulmonary nodulePET/CTRadiomicsPrediction modelNegative tumor markers

《新医学》 2026 (8)

881-890,10

河北省医学科学研究课题计划项目(20232029)保定市科技计划项目(2241ZF262)

10.12464/j.issn.0253-9802.2026-0156

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