Department of Radiology, West China Hospital, Sichuan University, No.37 Guoxue Alley, Chengdu, 610041, China.
Department of Radiology, Peking Union Medical College Hospital (Dongdan campus), No.1 Shuaifuyuan Wangfujing Dongcheng District, Beijing, 100730, China.
Eur Radiol. 2021 Oct;31(10):7696-7704. doi: 10.1007/s00330-021-07898-7. Epub 2021 Apr 15.
To identify image features of macrotrabecular-massive (MTM) hepatocellular carcinoma (HCC) and to determine its role in predicting MTM-HCC.
Patients who underwent preoperative gadoxetic acid-enhanced MRI and with surgery proven HCC were retrospectively included. Imaging features were assessed according to Liver Imaging Reporting and Data System. Quantitative measurements were recorded. Clinical characteristics and imaging findings were compared between MTM-HCCs and non-MTM-HCCs. Predictive factors of MTM-HCC were screened with univariate analyses and then identified with multivariate logistic regression. A regression-based diagnostic model was constructed. ROC analyses were used to determine cutoff values, AUC, and corresponding 95% confidence interval (CI) of findings. The diagnostic performance was validated by 10-fold cross-validation.
One hundred and forty-one patients with 37 MTM-HCCs were included. Multivariate analyses identified high platelet count (≥ 163.5 × 10/ul, odds ratio = 3.20; 95% CI: 1.29, 7.96; p = 0.012), low tumor-to-liver ADC ratio (≤ 1.05, odds ratio = 3.05; 95% CI, 1.23 - 7.55; p = 0.016), and necrosis or severe ischemia (odds ratio = 11.61; 95% CI, 3.99 - 33.76, p < 0.001) as independent predictors of MTM-HCC. Necrosis or severe ischemia alone helped identify 86% MTM-HCCs with a specificity of 66%. The average AUCs were 0.81 (95% CI: 0.71, 0.90) for the regression-based diagnostic model, with a sensitivity of 57% and specificity of 92%.
Necrosis or severe ischemia was a sensitive imaging feature of MTM-HCC. Noninvasive prediction of this subtype can be achieved with good accuracy and excellent specificity when findings were combined.
• The macrotrabecular-massive (MTM) hepatocellular carcinoma (HCC) represents an aggressive subtype of HCC and is associated with poor prognosis. • Imaging features of necrosis or severe ischemia alone helped identify 86% MTM-HCCs with a specificity of 66%. • A regression-based diagnostic model including high platelet count (≥ 163.5 × 10/ul), low tumor-to-liver ADC ratio (≤ 1.05), and necrosis or severe ischemia can provide noninvasive assessment of MTM-HCC with good accuracy and high specificity.
确定巨梁型/块状（MTM）肝细胞癌（HCC）的影像学特征，并确定其在预测 MTM-HCC 中的作用。
回顾性纳入接受术前钆塞酸增强 MRI 检查且经手术证实为 HCC 的患者。根据肝脏影像报告和数据系统评估影像学特征。记录定量测量值。比较 MTM-HCC 与非 MTM-HCC 之间的临床特征和影像学表现。使用单因素分析筛选 MTM-HCC 的预测因素，然后使用多因素逻辑回归进行识别。构建基于回归的诊断模型。使用 ROC 分析确定各项指标的截断值、AUC 及其相应的 95%置信区间（CI）。通过 10 折交叉验证验证诊断性能。
共纳入 141 例患者，其中 37 例为 MTM-HCC。多因素分析确定血小板计数高（≥163.5×10/ul，比值比=3.20；95%CI：1.29，7.96；p=0.012）、肿瘤与肝脏 ADC 比值低（≤1.05，比值比=3.05；95%CI，1.23-7.55；p=0.016）和坏死或严重缺血（比值比=11.61；95%CI，3.99-33.76，p<0.001）为 MTM-HCC 的独立预测因素。仅坏死或严重缺血即可识别 86%的 MTM-HCC，特异性为 66%。基于回归的诊断模型的平均 AUC 为 0.81（95%CI：0.71，0.90），敏感性为 57%，特异性为 92%。
坏死或严重缺血是 MTM-HCC 的敏感影像学特征。当将这些发现结合使用时，这种亚型的无创预测可以达到较高的准确性和极好的特异性。
