Nuclear Medicine Department, University Hospital, Caen, France.
Nuclear Medicine Department, François Baclesse Cancer Centre, Caen, France.
Eur J Nucl Med Mol Imaging. 2019 Feb;46(2):421-428. doi: 10.1007/s00259-018-4151-8. Epub 2018 Sep 14.
To determine EARL-compliant prognostic SUV thresholds in a mature cohort of patients with locally advanced NSCLC, and to demonstrate how detrimental it is to use a threshold determined on an older-generation PET system with a newer PET/CT machine, and vice versa, or to use such a threshold with non-harmonized multicentre pooled data.
This was a single-centre retrospective study including 139 consecutive stage IIIA-IIIB patients. PET data were acquired as per the EANM guidelines and reconstructed with unfiltered point spread function (PSF) reconstruction. Subsequently, a 6.3 mm Gaussian filter was applied using the EQ.PET (Siemens Healthineers) methodology to meet the EANM/EARL harmonizing standards (PSF). A multicentre study including non-EARL-compliant systems was simulated by randomly creating four groups of patients whose images were reconstructed with unfiltered PSF and PSF with Gaussian post-filtering of 3, 5, and 10 mm. Identification of optimal SUV thresholds was based on a two-fold cross-validation process that partitioned the overall sample into learning and validation subsamples. Proportional Cox hazards models were used to estimate age-adjusted and multivariable-adjusted hazard ratios (HRs) and their 95% confidence intervals. Kaplan-Meier curves were compared using the log rank test.
Median follow-up was 28 months (1-104 months). For the whole population, the estimated overall survival rate at 36 months was 0.39 [0.31-0.47]. The optimal SUV cutoff value was 25.43 (95% CI: 23.41-26.31) and 8.47 (95% CI: 7.23-9.31) for the PSF and for the EARL-compliant dataset respectively. These SUV cutoff values were both significantly and independently associated with lung cancer mortality; HRs were 1.73 (1.05-2.84) and 1.92 (1.16-3.19) for the PSF and the EARL-compliant dataset respectively. When (i) applying the optimal PSF SUV cutoff on an EARL-compliant dataset and the optimal EARL SUV cutoff on a PSF dataset or (ii) applying the optimal EARL compliant SUV cutoff to a simulated multicentre dataset, the tumour SUV was no longer significantly associated with lung cancer mortality.
The present study provides the PET community with an EARL-compliant SUV as an independent prognosticator for advanced NSCLC that should be confirmed in a larger cohort, ideally at other EARL accredited centres, and highlights the need to harmonize PET quantitative metrics when using them for risk stratification of patients.
在局部晚期 NSCLC 的成熟患者队列中确定符合 EARL 标准的预后 SUV 阈值，并展示使用旧一代 PET 系统上确定的阈值对较新的 PET/CT 机器的不利影响，反之亦然，或者使用非协调的多中心汇总数据。
这是一项单中心回顾性研究，包括 139 例连续的 IIIA-IIIB 期患者。PET 数据按照 EANM 指南采集，并使用未过滤的点扩散函数 (PSF) 重建进行重建。随后，使用 EQ.PET（西门子医疗）方法应用 6.3 毫米高斯滤波器（Siemens Healthineers）以满足 EANM/EARL 协调标准（PSF）。通过随机创建四个患者组来模拟非 EARL 符合系统的多中心研究，这些图像使用未过滤的 PSF 和 PSF 进行重建，PSF 具有 3、5 和 10 毫米的高斯后滤波。最佳 SUV 阈值的确定基于两倍交叉验证过程，该过程将整个样本分为学习和验证子样本。使用比例 Cox 风险模型估计年龄调整和多变量调整后的风险比 (HR) 及其 95%置信区间。使用对数秩检验比较 Kaplan-Meier 曲线。
中位随访时间为 28 个月（1-104 个月）。对于整个人群，36 个月时的总体生存率估计为 0.39[0.31-0.47]。最佳 SUV 截止值为 25.43（95%CI：23.41-26.31）和 8.47（95%CI：7.23-9.31），分别用于 PSF 和符合 EARL 数据集。这些 SUV 截止值均与肺癌死亡率显著且独立相关；PSF 的 HR 为 1.73（1.05-2.84），符合 EARL 数据集的 HR 为 1.92（1.16-3.19）。当 (i) 将最佳 PSF SUV 截止值应用于符合 EARL 的数据集和最佳 EARL SUV 截止值应用于 PSF 数据集时，或 (ii) 将最佳 EARL 符合 SUV 截止值应用于模拟的多中心数据集时，肿瘤 SUV 与肺癌死亡率不再显著相关。
本研究为 PET 社区提供了符合 EARL 标准的 SUV 作为晚期 NSCLC 的独立预后标志物，该标志物需要在更大的队列中得到证实，理想情况下是在其他 EARL 认可的中心，并强调在使用它们对患者进行风险分层时需要协调 PET 定量指标。
