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局部晚期非小细胞肺癌患者风险分层的 FDG PET/CT 最佳容积学参数:来自 ACRIN 6668/RTOG 0235 试验的结果。

Optimal FDG PET/CT volumetric parameters for risk stratification in patients with locally advanced non-small cell lung cancer: results from the ACRIN 6668/RTOG 0235 trial.

机构信息

Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA.

Department of Radiology, University of Minnesota, Minneapolis, MN, USA.

出版信息

Eur J Nucl Med Mol Imaging. 2017 Nov;44(12):1969-1983. doi: 10.1007/s00259-017-3753-x. Epub 2017 Jul 8.

Abstract

PURPOSE

In recent years, multiple studies have demonstrated the value of volumetric FDG-PET/CT parameters as independent prognostic factors in patients with non-small cell lung cancer (NSCLC). We aimed to determine the optimal cut-off points of pretreatment volumetric FDG-PET/CT parameters in predicting overall survival (OS) in patients with locally advanced NSCLC and to recommend imaging biomarkers appropriate for routine clinical applications.

METHODS

Patients with inoperable stage IIB/III NSCLC enrolled in ACRIN 6668/RTOG 0235 were included. Pretreatment FDG-PET scans were quantified using semiautomatic adaptive contrast-oriented thresholding and local-background partial-volume-effect-correction algorithms. For each patient, the following indices were measured: metabolic tumor volume (MTV), total lesion glycolysis (TLG), SUVmax, SUVmean, partial-volume-corrected TLG (pvcTLG), and pvcSUVmean for the whole-body, primary tumor, and regional lymph nodes. The association between each index and patient outcome was assessed using Cox proportional hazards regression. Optimal cut-off points were estimated using recursive binary partitioning in a conditional inference framework and used in Kaplan-Meier curves with log-rank testing. The discriminatory ability of each index was examined using time-dependent receiver operating characteristic (ROC) curves and corresponding area under the curve (AUC(t)).

RESULTS

The study included 196 patients. Pretreatment whole-body and primary tumor MTV, TLG, and pvcTLG were independently prognostic of OS. Optimal cut-off points were 175.0, 270.9, and 35.5 cm for whole-body TLG, pvcTLG, and MTV, and were 168.2, 239.8, and 17.4 cm for primary tumor TLG, pvcTLG, and MTV, respectively. In time-dependent ROC analysis, AUC(t) for MTV and TLG were uniformly higher than that of SUV measures over all time points. Primary tumor and whole-body parameters demonstrated similar patterns of separation for those patients above versus below the optimal cut-off points in Kaplan-Meier curves and in time-dependent ROC analysis.

CONCLUSION

We demonstrated that pretreatment whole-body and primary tumor volumetric FDG-PET/CT parameters, including MTV, TLG, and pvcTLG, are strongly prognostic for OS in patients with locally advanced NSCLC, and have similar discriminatory ability. Therefore, we believe that, after validation in future trials, the derived optimal cut-off points for primary tumor volumetric FDG-PET/CT parameters, or their more refined versions, could be incorporated into routine clinical practice, and may provide more accurate prognostication and staging based on tumor metabolic features.

摘要

目的

近年来,多项研究表明,容积式 FDG-PET/CT 参数作为非小细胞肺癌(NSCLC)患者的独立预后因素具有重要价值。本研究旨在确定无法手术的 IIB/III 期 NSCLC 患者治疗前容积式 FDG-PET/CT 参数的最佳截断值,以预测总生存期(OS),并推荐适用于常规临床应用的影像学生物标志物。

方法

本研究纳入了 ACRIN 6668/RTOG 0235 试验中不可手术的 IIB/III 期 NSCLC 患者。采用半自动自适应对比导向阈值和局部背景部分容积效应校正算法对 FDG-PET 扫描进行定量分析。对每位患者测量以下指标:代谢肿瘤体积(MTV)、总病灶糖酵解(TLG)、SUVmax、SUVmean、全身体积校正的 TLG(pvcTLG)和局部病灶 SUVmean。采用 Cox 比例风险回归评估各指标与患者结局的相关性。采用条件推断框架中的递归二分划分法估计最佳截断值,并采用 Kaplan-Meier 曲线和对数秩检验。使用时间依赖性接受者操作特征(ROC)曲线和相应的曲线下面积(AUC(t))评估各指标的判别能力。

结果

本研究共纳入 196 例患者。治疗前全身和原发肿瘤 MTV、TLG 和 pvcTLG 与 OS 独立相关。最佳截断值分别为全身 TLG、pvcTLG 和 MTV 为 175.0、270.9 和 35.5 cm,原发肿瘤 TLG、pvcTLG 和 MTV 分别为 168.2、239.8 和 17.4 cm。在时间依赖性 ROC 分析中,MTV 和 TLG 的 AUC(t)在所有时间点均高于 SUV 测量值。Kaplan-Meier 曲线和时间依赖性 ROC 分析中,最佳截断值以上和以下患者的全身和原发肿瘤参数的分离模式相似。

结论

我们证明,治疗前全身和原发肿瘤 FDG-PET/CT 容积参数(包括 MTV、TLG 和 pvcTLG)与局部晚期 NSCLC 患者的 OS 具有强相关性,且具有相似的判别能力。因此,我们认为,在未来的试验中验证后,原发性肿瘤 FDG-PET/CT 容积参数的最佳截断值(或其更精细的版本)可以纳入常规临床实践,并可能基于肿瘤代谢特征提供更准确的预后和分期。

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