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Noninvasive identification of proliferative hepatocellular carcinoma on multiphase dynamic CT: quantitative and LI-RADS lexicon-based evaluation

  • Wanli Zhang,
  • Nan Li,
  • Jiamin Li,
  • Yue Zhao,
  • Yi Long,
  • Chutong He,
  • Chuanxian Zhang,
  • Bo Li,
  • Yandong Zhao,
  • Shengsheng Lai,
  • Wenshuang Ding,
  • Mingyong Gao,
  • Lilian Tan,
  • Xinhua Wei,
  • Ruimeng Yang,
  • Xinqing Jiang

摘要

Objective

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).

Methods

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).

Results

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).

Conclusions

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.

Key Points

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.