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基于F-FDG PET/CT的影像组学列线图用于术前预测大结节型-巨块型肝细胞癌:一项双中心研究

F-FDG PET/CT-based radiomics nomogram for preoperative prediction of macrotrabecular-massive hepatocellular carcinoma: a two-center study.

作者信息

Hu Siqi, Kang Yinqian, Xie Yujie, Yang Ting, Yang Yuan, Jiao Ju, Zou Qiong, Zhang Hong, Zhang Yong

机构信息

Department of Nuclear Medicine, The Third Affiliated Hospital of Sun Yat-Sen University, No. 600 Tianhe Road, Tianhe District, Guangzhou, 510630, China.

Department of Anesthesiology, Sun Yat-Sen University Cancer Center, No. 651 Dongfeng East Road, Yuexiu District, Guangzhou, 510060, China.

出版信息

Abdom Radiol (NY). 2023 Feb;48(2):532-542. doi: 10.1007/s00261-022-03722-y. Epub 2022 Nov 12.

Abstract

PURPOSE

To explore the potential of β-2-[18F] fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (F-FDG PET/CT) in the evaluation of macrotrabecular-massive (MTM) hepatocellular carcinoma (HCC) and to apply radiomics approach to build a radiomics nomogram for predicting MTM-HCC.

METHODS

This study included 140 (training cohort:101; validation cohort:39) HCC patients who underwent preoperative F-FDG PET/CT at two institutions. The clinical features and tumor FDG metabolism measured by the tumor-to-liver ratio (TLR) via F-FDG PET/CT were retrospectively collected. Radiomics features were extracted from F-FDG PET/CT images and a radiomics score (Rad-score) was calculated. A radiomics nomogram was then constructed by combining Rad-score and independent clinical features and was assessed with a calibration curve. The performance of the radiomics nomogram, Rad-score and TLR was evaluated by receiver operating characteristic (ROC) curves and decision curve analysis (DCA).

RESULTS

A total of six top weighted radiomics features were selected from PET/CT images by the least absolute shrinkage and selection operator (LASSO) regression algorithm and were used to construct a Rad-score. Multivariate analysis identified Rad-score (OR = 2.183, P = 0.004), age ≤ 50 years (OR = 3.136, P = 0.036), AST > 40U/L (OR = 0.270, P = 0.017) and TLR (OR = 1.641, P = 0.049) as independent predictors of MTM-HCC. The radiomics nomogram had a higher area under the curves (AUCs) than the Rad-score and TLR for predicting MTM-HCC in both training (0.849 [95% CI 0.774-0.924] vs. 0.764 [95% CI 0.669-0.843], 0.763 [95% CI 0.668-0.842]) and validation (0.749 [95% CI 0.584-0.873] vs. 0.690 [95% CI 0.522-0.828], 0.541 [95% CI 0.374-0.701]) cohorts. DCA showed the radiomics nomogram to be more clinically useful than Rad-score and TLR.

CONCLUSIONS

Tumor FDG metabolism is significantly associated with MTM-HCC. A F-FDG PET/CT-based radiomics nomogram may be useful for preoperatively predicting the MTM subtype in primary HCC patients, contributing to pretreatment decision-making.

摘要

目的

探讨β-2-[18F]氟-2-脱氧-D-葡萄糖正电子发射断层扫描/计算机断层扫描(F-FDG PET/CT)在评估大结节型-巨块型(MTM)肝细胞癌(HCC)中的潜力,并应用放射组学方法构建预测MTM-HCC的放射组学列线图。

方法

本研究纳入了140例(训练队列:101例;验证队列:39例)在两家机构接受术前F-FDG PET/CT检查的HCC患者。回顾性收集临床特征以及通过F-FDG PET/CT测量的肿瘤与肝脏比值(TLR)所反映的肿瘤FDG代谢情况。从F-FDG PET/CT图像中提取放射组学特征并计算放射组学评分(Rad-score)。然后将Rad-score与独立临床特征相结合构建放射组学列线图,并通过校准曲线进行评估。通过受试者工作特征(ROC)曲线和决策曲线分析(DCA)评估放射组学列线图、Rad-score和TLR的性能。

结果

通过最小绝对收缩和选择算子(LASSO)回归算法从PET/CT图像中总共选择了6个权重最高的放射组学特征,并用于构建Rad-score。多变量分析确定Rad-score(比值比[OR]=2.183,P=0.004)、年龄≤50岁(OR=3.136,P=0.036)、谷草转氨酶(AST)>40U/L(OR=0.270,P=0.017)和TLR(OR=1.641,P=0.049)为MTM-HCC的独立预测因素。在训练队列(0.849[95%可信区间(CI)0.774-0.924]对0.764[95%CI 0.669-0.843]、0.763[95%CI 0.668-0.842])和验证队列(0.749[95%CI 0.584-0.873]对0.690[95%CI 0.522-0.828]、0.541[95%CI 0.374-0.701])中,放射组学列线图在预测MTM-HCC方面的曲线下面积(AUC)高于Rad-score和TLR。DCA显示放射组学列线图在临床上比Rad-score和TLR更有用。

结论

肿瘤FDG代谢与MTM-HCC显著相关。基于F-FDG PET/CT的放射组学列线图可能有助于术前预测原发性HCC患者的MTM亚型,为治疗前决策提供依据。

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