多参数肝脏 MRI 预测微波消融后肝细胞癌的早期复发。
Multiparametric liver MRI for predicting early recurrence of hepatocellular carcinoma after microwave ablation.
机构信息
Department of Interventional Ultrasound, PLA Medical College & Fifth Medical Center of Chinese PLA General Hospital, Haidian District, No. 28, Fuxing Road, Beijing, 100853, People's Republic of China.
Department of Medical Imaging, PLA Medical College & First Medical Center Chinese PLA General Hospital, Beijing, People's Republic of China.
出版信息
Cancer Imaging. 2022 Aug 30;22(1):42. doi: 10.1186/s40644-022-00471-5.
BACKGROUND
High early recurrence (ER) of hepatocellular carcinoma (HCC) after microwave ablation (MWA) represents a sign of aggressive behavior and severely worsens prognosis. The aim of this study was to estimate the outcome of HCC following MWA and develop a response algorithmic strategy based on multiparametric MRI and clinical variables.
METHODS
In this retrospective study, we reviewed the records of 339 patients (mean age, 62 ± 12 years; 106 men) treated with percutaneous MWA for HCC between January 2014 and December 2017 that were evaluated by multiparametric MRI. These patients were randomly split into a development and an internal validation group (3:1). Logistic regression analysis was used to screen imaging features. Multivariate Cox regression analysis was then performed to determine predictors of ER (within 2 years) of MWA. The response algorithmic strategy to predict ER was developed and validated using these data sets. ER rates were also evaluated by Kaplan-Meier analysis.
RESULTS
Based on logistic regression analyses, we established an image response algorithm integrating ill-defined margins, lack of capsule enhancement, pre-ablative ADC, ΔADC, and EADC to calculate recurrence scores and define the risk of ER. In a multivariate Cox regression model, the independent risk factors of ER (p < 0.05) were minimal ablative margin (MAM) (HR 0.57; 95% CI 0.35 - 0.95; p < 0.001), the recurrence score (HR: 9.25; 95% CI 4.25 - 16.56; p = 0.021), and tumor size (HR 6.21; 95% CI 1.25 - 10.82; p = 0.014). Combining MAM and tumor size, the recurrence score calculated by the response algorithmic strategy provided predictive accuracy of 93.5%, with sensitivity of 92.3% and specificity of 83.1%. Kaplan-Meier estimates of the rates of ER in the low-risk and high-risk groups were 6.8% (95% CI 4.0 - 9.6) and 30.5% (95% CI 23.6 - 37.4), respectively.
CONCLUSION
A response algorithmic strategy based on multiparametric MRI and clinical variables was useful for predicting the ER of HCC after MWA.
背景
肝癌微波消融（MWA）后早期高复发（ER）是侵袭性行为的标志，严重恶化预后。本研究旨在评估 MWA 后 HCC 的结局，并基于多参数 MRI 和临床变量制定反应算法策略。
方法
这是一项回顾性研究，我们对 2014 年 1 月至 2017 年 12 月期间接受经皮 MWA 治疗的 339 例 HCC 患者（平均年龄 62±12 岁，106 例男性）的记录进行了回顾。所有患者均接受多参数 MRI 评估。这些患者被随机分为开发组和内部验证组（3:1）。使用逻辑回归分析筛选影像学特征。然后进行多变量 Cox 回归分析，以确定 MWA 后 ER（2 年内）的预测因子。使用这些数据集开发和验证预测 ER 的反应算法策略。通过 Kaplan-Meier 分析评估 ER 率。
结果
基于逻辑回归分析，我们建立了一种图像反应算法，该算法整合了不明确的边界、缺乏包膜增强、消融前 ADC 值、ΔADC 值和 EADC 值，以计算复发评分并定义 ER 的风险。在多变量 Cox 回归模型中，ER 的独立危险因素（p<0.05）是最小消融边界（MAM）（HR 0.57；95%CI 0.35-0.95；p<0.001）、复发评分（HR：9.25；95%CI 4.25-16.56；p=0.021）和肿瘤大小（HR 6.21；95%CI 1.25-10.82；p=0.014）。结合 MAM 和肿瘤大小，反应算法策略计算的复发评分提供了 93.5%的预测准确性，敏感性为 92.3%，特异性为 83.1%。低危组和高危组的 ER 发生率的 Kaplan-Meier 估计值分别为 6.8%（95%CI 4.0-9.6）和 30.5%（95%CI 23.6-37.4）。
结论
基于多参数 MRI 和临床变量的反应算法策略有助于预测 MWA 后 HCC 的 ER。
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