Contrast-enhanced ultrasound for diagnosing subtypes of intrahepatic cholangiocarcinoma: a comparative study with poorly differentiated hepatocellular carcinoma.

IF 3.5 2区 医学 Q2 ONCOLOGY
Nan Zhang, Yue Yang, Ke Lin, Bin Qiao, Dao-Peng Yang, Dong-Dong Jin, Bin Li, Dong-Liang Zhao, Xiao-Hua Xie, Xiao-Yan Xie, Ji-Hui Kang, Bo-Wen Zhuang
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引用次数: 0

Abstract

Background: Pathologically, intrahepatic cholangiocarcinoma (ICC) is classified into small-duct (SD) type and large-duct (LD) type, each with distinct clinicopathological characteristics. The contrast-enhanced ultrasound (CEUS) features of the two ICC types remain insufficiently explored.

Purpose: To evaluate liver CEUS imaging for differentiating the SD and LD types of ICC and further compare them with poorly differentiated hepatocellular carcinoma (pHCC).

Materials and methods: A single-center retrospective study enrolled 252 patients with SD-type ICC, LD-type ICC, or pHCC between October 2017 and August 2023. Logistic regression analyses identified independent clinical, pathological, ultrasound, and CEUS predictors. Based on these features, a decision tree-based diagnostic model was developed. The model's performance was evaluated using receiver operating characteristic (ROC) curve analysis in both the training and validation cohorts, as well as in subgroup stratified by tumor size ≤ 5 cm and > 5 cm. Differences in overall survival (OS) and recurrence-free survival (RFS) based on the model were further analyzed.

Results: Overall, 252 patients (mean age, 58.4 ± 10.7 years; 174 males) with 140 SD-type ICC, 55 LD-type ICC and 57 pHCC were enrolled. Multivariate analysis revealed that AFP, CEA, CA19-9, HBsAg status, arterial phase enhancement pattern, washout time ≤ 45 s, and marked washout were independent predictors for tumor categories differentiation (all P <.05). The decision tree-based model incorporating the major features demonstrated excellent performance in both the training cohort (AUC 0.89) and validation cohort (AUC 0.88), as well as in tumor size ≤ 5 cm (AUC 0.90) and > 5 cm (AUC 0.84). OS was significantly worse in LD-type ICC patients compared to SD-type and pHCC (P <.05 for both), while RFS showed no significant difference.

Conclusions: A user-friendly, decision tree-based diagnostic model was developed to accurately predict ICC subtypes and pHCC, facilitating improved clinical decision-making. The decision tree-based diagnostic model effectively diagnosed small-duct type and large-duct type intrahepatic cholangiocarcinoma, as well as poorly differentiated hepatocellular carcinoma.

Abstract Image

Abstract Image

Abstract Image

超声造影诊断肝内胆管癌亚型:与低分化肝细胞癌的比较研究
背景:肝内胆管癌(ICC)在病理学上分为小管型(SD)和大管型(LD),各有不同的临床病理特征。对比增强超声(CEUS)特征的两种ICC类型仍未充分探讨。目的:探讨肝超声造影(CEUS)对ICC的SD型和LD型鉴别价值,并与低分化肝癌(pHCC)进行比较。材料和方法:2017年10月至2023年8月,一项单中心回顾性研究纳入了252例sd型ICC、ld型ICC或pHCC患者。逻辑回归分析确定了独立的临床、病理、超声和超声造影预测因子。基于这些特征,建立了基于决策树的诊断模型。采用受试者工作特征(ROC)曲线分析对训练组和验证组以及按肿瘤大小≤5cm和> 5cm分层的亚组进行模型性能评估。进一步分析基于模型的总生存期(OS)和无复发生存期(RFS)的差异。结果:共纳入252例患者(平均年龄58.4±10.7岁,男性174例),其中sd型ICC 140例,ld型ICC 55例,pHCC 57例。多因素分析显示,AFP、CEA、CA19-9、HBsAg状态、动脉期增强模式、洗脱时间≤45 s、明显洗脱是肿瘤分类分化的独立预测因子(P值均为5 cm (AUC 0.84))。与sd型和pHCC相比,ld型ICC患者的OS明显更差(P结论:建立了一个用户友好的、基于决策树的诊断模型,可以准确预测ICC亚型和pHCC,有助于改善临床决策。基于决策树的诊断模型可有效诊断小管型和大管型肝内胆管癌以及低分化肝细胞癌。
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来源期刊
Cancer Imaging
Cancer Imaging ONCOLOGY-RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
CiteScore
7.00
自引率
0.00%
发文量
66
审稿时长
>12 weeks
期刊介绍: Cancer Imaging is an open access, peer-reviewed journal publishing original articles, reviews and editorials written by expert international radiologists working in oncology. The journal encompasses CT, MR, PET, ultrasound, radionuclide and multimodal imaging in all kinds of malignant tumours, plus new developments, techniques and innovations. Topics of interest include: Breast Imaging Chest Complications of treatment Ear, Nose & Throat Gastrointestinal Hepatobiliary & Pancreatic Imaging biomarkers Interventional Lymphoma Measurement of tumour response Molecular functional imaging Musculoskeletal Neuro oncology Nuclear Medicine Paediatric.
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