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光谱 CT 参数对非小细胞肺癌 EGFR 基因突变的预测价值。

Predictive value of spectral computed tomography parameters for EGFR gene mutation in non-small-cell lung cancer.

机构信息

Department of Radiology, The First Affiliated Hospital of Xinjiang Medical University, Urumchi 830011, China; Department of Radiology, Xinjiang Medical University Affiliated Tumor Hospital, Urumchi 830011, China.

Department of Laboratory, Traditional Chinese Medical Hospital of Xinjiang Uygur Autonomous Region, Urumchi 830011, China.

出版信息

Clin Radiol. 2024 Aug;79(8):e1049-e1056. doi: 10.1016/j.crad.2024.04.019. Epub 2024 May 4.

Abstract

AIM

To explore the predictive value of morphological signs and quantitative parameters from spectral CT for EGFR gene mutations in intermediate and advanced non-small-cell lung cancer (NSCLC).

MATERIALS AND METHODS

This retrospective observational study included patients with intermediate or advanced NSCLC at Xinjiang Medical University Affiliated Tumor Hospital between January 2017 and December 2019. The patients were divided into the EGFR gene mutation-positive and -negative groups.

RESULTS

Seventy-nine patients aged 60.75 ± 9.66 years old were included: 32 were EGFR mutation-positive, and 47 were negative. There were significant differences in pathological stage (P<0.001), tumor diameter (P=0.019), lobulation sign, intrapulmonary metastasis, mediastinal lymph node metastasis, distant metastasis (P<0.001), bone metastasis (P<0.001), arterial phase normalized iodine concentration (NIC) (P=0.001), venous phase NIC (P=0.001), slope of the energy spectrum curve (λ) (P<0.001), and CT value at 70 keV in arterial phase (P=0.004) and venous phase (P=0.003) between the EGFR mutation-positive and -negative patients. The multivariable logistic regression analysis showed that intrapulmonary metastasis, distant metastasis, venous phase NIC, venous phase λ, and pathological stage were independent factors predicting EGFR gene mutations, with high diagnostic power (AUC = 0.975, 91.5% sensitivity, and 90.6% specificity).

CONCLUSION

The pathological stage and the spectral CT parameters of intrapulmonary metastasis, distant metastasis, venous phase NIC, and venous phase λ might pre-operatively predict EGFR gene mutations in intermediate and advanced NSCLC.

摘要

目的

探讨能谱 CT 形态学征象及定量参数对中晚期非小细胞肺癌(NSCLC)表皮生长因子受体(EGFR)基因突变的预测价值。

材料与方法

本回顾性观察性研究纳入 2017 年 1 月至 2019 年 12 月于新疆医科大学附属肿瘤医院就诊的中晚期 NSCLC 患者。将患者分为 EGFR 基因突变阳性组和阴性组。

结果

共纳入 79 例患者,年龄 60.75±9.66 岁:32 例 EGFR 基因突变阳性,47 例阴性。两组患者的病理分期(P<0.001)、肿瘤直径(P=0.019)、分叶征、肺内转移、纵隔淋巴结转移、远处转移(P<0.001)、骨转移(P<0.001)、动脉期标准化碘浓度(NIC)(P=0.001)、静脉期 NIC(P=0.001)、能谱曲线斜率(λ)(P<0.001)、动脉期 70keV 下 CT 值(P=0.004)和静脉期 CT 值(P=0.003)存在显著差异。多变量逻辑回归分析显示,肺内转移、远处转移、静脉期 NIC、静脉期 λ 和病理分期是 EGFR 基因突变的独立预测因素,具有较高的诊断效能(AUC=0.975,敏感性 91.5%,特异性 90.6%)。

结论

中晚期 NSCLC 患者的病理分期和能谱 CT 肺内转移、远处转移、静脉期 NIC、静脉期 λ 等参数可能有助于术前预测 EGFR 基因突变。

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