Zhang Wanli, Li Nan, Li Jiamin, Zhao Yue, Long Yi, He Chutong, Zhang Chuanxian, Li Bo, Zhao Yandong, Lai Shengsheng, Ding Wenshuang, Gao Mingyong, Tan Lilian, Wei Xinhua, Yang Ruimeng, Jiang Xinqing
Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Guangzhou, China.
School of Medicine, South China University of Technology, Guangzhou, China.
Eur Radiol. 2025 Jun;35(6):3460-3475. doi: 10.1007/s00330-024-11247-9. Epub 2024 Dec 12.
To identify proliferative hepatocellular carcinoma (HCC) preoperatively using quantitative measurements combined with the updated standard 2021 LI-RADS universal lexicon-based qualitative features on multiphase dynamic CT (MDCT).
We retrospectively analyzed 273 patients (102 proliferative HCCs) who underwent preoperative MDCT with surgically confirmed HCC in two medical centers. Imaging features were evaluated according to the updated 2021 LI-RADS universal lexicon, and quantitative measurements were analyzed. All MDCT findings and clinical factors were compared. Four predictive models (clinical, CT quantitative-clinical, CT qualitative-clinical, and combinational models) were developed and validated in an external cohort for identifying proliferative HCC. ROC analysis was used to assess model performances. All models were tested in a subgroup of patients with a single lesion ≤ 5 cm (n = 124).
Both the CT quantitative-clinical and CT qualitative-clinical models effectively identified proliferative HCC in the training and external validation cohorts (all AUCs > 0.79). The combinational model, integrating one clinical (AFP ≥ 200 ng/mL), three qualitative (rim arterial phase hyperenhancement (APHE), non-smooth tumor margin, and incomplete or absent capsule), and one quantitative feature (standardized tumor-to-aorta density ratio in portal venous phase ≤ (- 0.13), showed significant improvement in the training cohort (AUC 0.871) and comparable performance in the validation cohort (AUC 0.870). Additionally, AFP ≥ 200 ng/mL and Rim APHE were significantly associated with HCC recurrence (p < 0.05).
The combinational model, integrating clinical, CT quantitative, and qualitative features, shows potential for the noninvasively preoperative prediction of proliferative HCC. Further validation is needed to establish its broader clinical utility.
Question Preoperative identification of proliferative HCC could influence patient treatment and prognosis, yet there is no CT-based universally applicable model to identify this subtype. Findings The updated standard 2021 LI-RADS universal lexicon-based features, in combination with quantitative MDCT measurements, could aid in the noninvasive detection of proliferative HCC. Clinical relevance The updated standard 2021 LI-RADS universal lexicon-based CT qualitative features and quantitative measurements may aid in identifying proliferative HCC and tumor recurrence, offering potential guidance for personalized treatment. Further studies are required to assess their generalizability to different clinical scenarios.
采用定量测量结合基于2021年更新标准的多期动态CT（MDCT）上基于LI-RADS通用词典的定性特征，术前识别增殖性肝细胞癌（HCC）。
我们回顾性分析了两个医学中心273例接受术前MDCT检查且手术确诊为HCC的患者（102例增殖性HCC）。根据2021年更新的LI-RADS通用词典评估影像特征，并分析定量测量结果。比较所有MDCT表现和临床因素。建立了四个预测模型（临床模型、CT定量-临床模型、CT定性-临床模型和联合模型），并在外部队列中进行验证以识别增殖性HCC。采用ROC分析评估模型性能。所有模型均在单个病灶≤5 cm的患者亚组（n = 124）中进行测试。
CT定量-临床模型和CT定性-临床模型在训练队列和外部验证队列中均能有效识别增殖性HCC（所有AUC均>0.79）。联合模型整合了一个临床特征（甲胎蛋白≥200 ng/mL）、三个定性特征（边缘动脉期强化（APHE）、肿瘤边缘不光滑、包膜不完整或无包膜）和一个定量特征（门静脉期标准化肿瘤与主动脉密度比≤（-0.13）），在训练队列中显示出显著改善（AUC 0.871），在验证队列中的表现相当（AUC 0.870）。此外，甲胎蛋白≥200 ng/mL和边缘APHE与HCC复发显著相关（p<0.05）。
整合临床、CT定量和定性特征的联合模型显示出术前无创预测增殖性HCC的潜力。需要进一步验证以确立其更广泛的临床应用价值。
问题 术前识别增殖性HCC可能影响患者治疗和预后，但尚无基于CT的普遍适用模型来识别该亚型。发现 基于2021年更新标准的LI-RADS通用词典的特征，结合MDCT定量测量，有助于无创检测增殖性HCC。临床意义 基于2021年更新标准的LI-RADS通用词典的CT定性特征和定量测量可能有助于识别增殖性HCC和肿瘤复发，为个性化治疗提供潜在指导。需要进一步研究评估其在不同临床场景中的可推广性。
