利用传统超声波、Sonazoid 增强超声波和生化指标预测肝细胞癌的微血管侵犯:一项多中心研究。

IF 4.1 2区 医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Insights into Imaging Pub Date : 2024-10-28 DOI:10.1186/s13244-024-01743-3
Dan Lu, Li-Fan Wang, Hong Han, Lin-Lin Li, Wen-Tao Kong, Qian Zhou, Bo-Yang Zhou, Yi-Kang Sun, Hao-Hao Yin, Ming-Rui Zhu, Xin-Yuan Hu, Qing Lu, Han-Sheng Xia, Xi Wang, Chong-Ke Zhao, Jian-Hua Zhou, Hui-Xiong Xu
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Univariate and multivariate logistic regression analyses on clinical information, biochemical indicator, and US imaging features were performed in the training set to seek independent predictors for MVI-positive. The models were constructed and evaluated using the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis in both validation and test sets. Subgroup analyses in patients with different liver background and tumor sizes were conducted to further investigate the model's performance.</p><p><strong>Results: </strong>Logistic regression analyses showed that obscure tumor boundary in B-mode US, intra-tumoral artery in pulsed-wave Doppler US, complete Kupffer-phase agent clearance in Sonazoid-CEUS, and biomedical indicator PIVKA-II were independently correlated with MVI-positive. The combined model comprising all predictors showed the highest AUC, which were 0.937 and 0.893 in the validation and test sets. 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引用次数: 0

摘要

目的:开发并验证基于多模态超声和生化指标的术前预测模型,用于识别单发肝细胞癌(HCC)≤5 cm患者的微血管侵犯(MVI):方法:2022年5月至2023年11月,三家机构共纳入318例病理确诊的单发肝细胞癌≤5厘米的患者。所有患者均接受了术前生化、常规超声(US)和造影剂增强超声(CEUS)(Sonazoid,0.6 mL,栓剂注射)检查。在训练集中对临床信息、生化指标和 US 成像特征进行了单变量和多变量逻辑回归分析,以寻找 MVI 阳性的独立预测因素。在验证集和测试集中,使用接收者操作特征曲线下面积(AUC)、校准曲线和决策曲线分析构建和评估了模型。为了进一步研究模型的性能,还对不同肝脏背景和肿瘤大小的患者进行了分组分析:逻辑回归分析表明,B型超声检查中肿瘤边界不明显、脉冲多普勒超声检查中肿瘤内动脉不明显、Sonazoid-CEUS检查中Kupffer相剂完全清除以及生物医学指标PIVKA-II与MVI阳性独立相关。包含所有预测因子的组合模型显示出最高的AUC,在验证集和测试集中分别为0.937和0.893。两组模型都实现了良好的校准和显著的净效益。在亚组分析中未发现明显差异:结论:生化指标、常规 US 和 Sonazoid-CEUS 特征的组合有助于单个 HCC ≤ 5 cm 患者的术前 MVI 预测:传统 US、Sonazoid-CEUS 和生化指标的成像特征调查显示,在单个 HCC ≤ 5 厘米的患者中,MVI 阳性与 MVI 阳性有显著关系,因此可以构建 MVI 状态的术前预测模型,帮助做出治疗决策:要点:MVI状态对于单个HCC≤5厘米的患者非常重要。基于传统 US、Sonazoid-CEUS 和 PIVKA-II 的模型在 MVI 预测方面表现最佳。组合模型具有术前预测MVI状态的潜力。
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Prediction of microvascular invasion in hepatocellular carcinoma with conventional ultrasound, Sonazoid-enhanced ultrasound, and biochemical indicator: a multicenter study.

Purpose: To develop and validate a preoperative prediction model based on multimodal ultrasound and biochemical indicator for identifying microvascular invasion (MVI) in patients with a single hepatocellular carcinoma (HCC) ≤ 5 cm.

Methods: From May 2022 to November 2023, a total of 318 patients with pathologically confirmed single HCC ≤ 5 cm from three institutions were enrolled. All of them underwent preoperative biochemical, conventional ultrasound (US), and contrast-enhanced ultrasound (CEUS) (Sonazoid, 0.6 mL, bolus injection) examinations. Univariate and multivariate logistic regression analyses on clinical information, biochemical indicator, and US imaging features were performed in the training set to seek independent predictors for MVI-positive. The models were constructed and evaluated using the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis in both validation and test sets. Subgroup analyses in patients with different liver background and tumor sizes were conducted to further investigate the model's performance.

Results: Logistic regression analyses showed that obscure tumor boundary in B-mode US, intra-tumoral artery in pulsed-wave Doppler US, complete Kupffer-phase agent clearance in Sonazoid-CEUS, and biomedical indicator PIVKA-II were independently correlated with MVI-positive. The combined model comprising all predictors showed the highest AUC, which were 0.937 and 0.893 in the validation and test sets. Good calibration and prominent net benefit were achieved in both sets. No significant difference was found in subgroup analyses.

Conclusions: The combination of biochemical indicator, conventional US, and Sonazoid-CEUS features could help preoperative MVI prediction in patients with a single HCC ≤ 5 cm.

Critical relevance statement: Investigation of imaging features in conventional US, Sonazoid-CEUS, and biochemical indicators showed a significant relation with MVI-positivity in patients with a single HCC ≤ 5 cm, allowing the construction of a model for preoperative prediction of MVI status to help treatment decision making.

Key points: MVI status is important for patients with a single HCC ≤ 5 cm. The model based on conventional US, Sonazoid-CEUS and PIVKA-II performs best for MVI prediction. The combined model has potential for preoperative prediction of MVI status.

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来源期刊
Insights into Imaging
Insights into Imaging Medicine-Radiology, Nuclear Medicine and Imaging
CiteScore
7.30
自引率
4.30%
发文量
182
审稿时长
13 weeks
期刊介绍: Insights into Imaging (I³) is a peer-reviewed open access journal published under the brand SpringerOpen. All content published in the journal is freely available online to anyone, anywhere! I³ continuously updates scientific knowledge and progress in best-practice standards in radiology through the publication of original articles and state-of-the-art reviews and opinions, along with recommendations and statements from the leading radiological societies in Europe. Founded by the European Society of Radiology (ESR), I³ creates a platform for educational material, guidelines and recommendations, and a forum for topics of controversy. A balanced combination of review articles, original papers, short communications from European radiological congresses and information on society matters makes I³ an indispensable source for current information in this field. I³ is owned by the ESR, however authors retain copyright to their article according to the Creative Commons Attribution License (see Copyright and License Agreement). All articles can be read, redistributed and reused for free, as long as the author of the original work is cited properly. The open access fees (article-processing charges) for this journal are kindly sponsored by ESR for all Members. The journal went open access in 2012, which means that all articles published since then are freely available online.
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