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基于 FDG PET/CT 动态显像的净流入常数在肺癌转移性与非转移性淋巴结鉴别诊断中的价值。

The value of net influx constant based on FDG PET/CT dynamic imaging in the differential diagnosis of metastatic from non-metastatic lymph nodes in lung cancer.

机构信息

Department of Graduate School, Dalian Medical University, Dalian, China.

Department of Nuclear Medicine, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital and Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College/Shenzhen Clinical Research Center for Cancer, Shenzhen, China.

出版信息

Ann Nucl Med. 2024 Nov;38(11):904-912. doi: 10.1007/s12149-024-01964-y. Epub 2024 Jul 29.

Abstract

OBJECTIVES

This study aims to evaluate the value of the dynamic and static quantitative metabolic parameters derived from F-fluorodeoxyglucose (FDG)-positron emission tomography/CT (PET/CT) in the differential diagnosis of metastatic from non-metastatic lymph nodes (LNs) in lung cancer and to validate them based on the results of a previous study.

METHODS

One hundred and twenty-one patients with lung nodules or masses detected on chest CT scan underwent F-FDG PET/CT dynamic + static imaging with informed consent. A retrospective collection of 126 LNs in 37 patients with lung cancer was pathologically confirmed. Static image analysis parameters include LN-SUV and LN-SUV/primary tumor SUV (LN-SUV/PT-SUV). Dynamic metabolic parameters including the net influx rate (K) and the surrogate of perfusion (K) and of each LN were obtained by applying the irreversible two-tissue compartment model using in-house Matlab software. K/K was then calculated as a separate marker. Based on the pathological findings, we divided into a metastatic group and a non-metastatic group. The χ test was used to evaluate the agreement of the individual and combined diagnosis of each metabolic parameter with the gold standard. The receiver-operating characteristic (ROC) analysis was performed for each parameter to determine the diagnostic efficacy in differentiating non-metastatic from metastatic LNs with high FDG-avid. P < 0.05 was considered statistically significant.

RESULTS

Among the 126 FDG-avid LNs confirmed by pathology, 70 LNs were metastatic, and 56 LNs were non-metastatic. For ROC analysis, in separate assays, the dynamic metabolic parameter K [sensitivity (SEN) of 84.30%, specificity (SPE) of 94.60%, accuracy of 88.89%, and AUC of 0.895] had a better diagnostic value than the static metabolic parameter SUV (SEN of 82.90%, SPE of 62.50%, accuracy of 74.60%, and AUC of 0.727) in differentiating between metastatic from non-metastatic LNs groups, respectively. In the combined diagnosis group, the combined SUV + K diagnosis had a better diagnostic value in the differential diagnosis of metastatic from non-metastatic LNs, with SEN, SPE, accuracy, and AUC of 84.3%, 94.6%, 88.89%, and 0.907, respectively.

CONCLUSIONS

When the cutoff value of K was 0.022 ml/g/min, it had a high diagnostic value in the differential diagnosis between metastasis and non-metastasis in FDG-avid LNs of lung cancer, especially in improving the specificity. The combination of SUV and K is expected to be a reliable metabolic parameter for N-staging of lung cancer.

摘要

目的

本研究旨在评估氟-18 氟代脱氧葡萄糖(FDG)-正电子发射断层扫描/计算机断层扫描(PET/CT)的动态和静态定量代谢参数在肺癌转移性和非转移性淋巴结(LNs)鉴别诊断中的价值,并基于之前的研究结果进行验证。

方法

121 名经胸部 CT 扫描发现肺部结节或肿块的患者在知情同意的情况下接受 F-FDG PET/CT 动态+静态成像。回顾性收集了 37 名肺癌患者的 126 个 LN,这些 LN 均经病理证实。静态图像分析参数包括 LN-SUV 和 LN-SUV/原发性肿瘤 SUV(LN-SUV/PT-SUV)。应用内部 Matlab 软件,采用不可逆双组织室模型,获得了包括净流入率(K)和灌注替代物(K)在内的每个 LN 的动态代谢参数。然后,将 K/K 作为一个单独的标志物进行计算。根据病理结果,我们将其分为转移性组和非转移性组。使用 χ 检验评估每个代谢参数的单独和联合诊断与金标准的一致性。对每个参数进行受试者工作特征(ROC)分析,以确定区分高 FDG 摄取的非转移性和转移性 LN 的诊断效能。P<0.05 被认为具有统计学意义。

结果

在经病理证实的 126 个 FDG 摄取的 LN 中,70 个为转移性,56 个为非转移性。在单独的检测中,动态代谢参数 K[灵敏度(SEN)为 84.30%,特异性(SPE)为 94.60%,准确性为 88.89%,曲线下面积(AUC)为 0.895]的诊断价值优于静态代谢参数 SUV[SEN 为 82.90%,SPE 为 62.50%,准确性为 74.60%,AUC 为 0.727],用于区分转移性和非转移性 LN 组。在联合诊断组中,SUV+K 联合诊断在鉴别转移性和非转移性 LN 方面具有更好的诊断价值,其 SEN、SPE、准确性和 AUC 分别为 84.3%、94.6%、88.89%和 0.907。

结论

当 K 的截断值为 0.022ml/g/min 时,它在 FDG 摄取的肺癌 LN 中对转移和非转移的鉴别诊断具有较高的诊断价值,特别是在提高特异性方面。SUV 和 K 的联合有望成为肺癌 N 分期的可靠代谢参数。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac71/11489159/472e573620d1/12149_2024_1964_Fig1_HTML.jpg

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