Li Yanzhuo, Li Sijie, Lei Yan, Liu Lianlian, Song Bin
1Department of Radiology, Minhang Hospital, Fudan University, Shanghai, People's Republic of China.
2Department of Radiology, Changhai Hospital, Naval Medical University, Shanghai, People's Republic of China.
Radiol Oncol. 2025 Apr 11;59(2):183-192. doi: 10.2478/raon-2025-0021. eCollection 2025 Jun 1.
Microvascular invasion (MVI), particularly its severity, correlates with prognosis in hepatocellular carcinoma (HCC), however, it remains uncertain which imaging traits are associated with MVI grades. Predicting MVI status precisely pre-surgery assists clinicians in making optimal treatment decisions.
213 HCC patients with surgically confirmed were assigned into three groups based on the severity of MVI (M0, M1, and M2). Clinical and imaging features were compared between each group. Univariate and multivariate analyses were used to identify the significant variables associated with MVI severity. Subsequently, nomograms were constructed to estimate MVI and its M2 grade by crucial factors. Nomograms were assessed for accuracy, clinical value, and efficacy using the area under the curve (AUC), calibration curve, and decision curve analysis (DCA).
Four factors associated with MVI (P < 0.05) were related, including non-solitary growth types, no/mini enhanced mode, peritumoral enhancement on arterial phase, and peritumoral hypointensity on hepatobiliary phase. Only the ratio of the maximum and minimum tumor diameter (Max/Min-R), confluent multinodule growth type, and non-washin/washout enhanced modes of those MVI-positive patients showed a strong correlation with M2 grade. The areas under the receiver operating characteristic (ROC) curves were 0.885 (95% confidence intervals [CI]: 0.833-0.937) in identifying MVI and 0.805 (95% CI: 0.703-0.908) in predicting its M2 grade, respectively. The nomograms demonstrated a high goodness-of-fit and clinical benefits in DCA and calibration curve.
Enhancement modes and tumor growth patterns of preoperative MRI were independent risk factors of MVI severity, which were valuable for facilitating individualized decision-making.
微血管侵犯（MVI），尤其是其严重程度，与肝细胞癌（HCC）的预后相关，然而，尚不确定哪些影像学特征与MVI分级有关。术前精确预测MVI状态有助于临床医生做出最佳治疗决策。
213例经手术确诊的HCC患者根据MVI严重程度分为三组（M0、M1和M2）。比较每组之间的临床和影像学特征。采用单因素和多因素分析确定与MVI严重程度相关的显著变量。随后，构建列线图，通过关键因素估计MVI及其M2分级。使用曲线下面积（AUC）、校准曲线和决策曲线分析（DCA）评估列线图的准确性、临床价值和效能。
与MVI相关的四个因素（P < 0.05），包括非孤立生长类型、无/轻度强化模式、动脉期瘤周强化和肝胆期瘤周低信号。仅MVI阳性患者的最大与最小肿瘤直径比值（Max/Min-R）、融合多结节生长类型和非廓清/廓清强化模式与M2分级密切相关。在识别MVI和预测其M2分级时，受试者操作特征（ROC）曲线下面积分别为0.885（95%置信区间[CI]：0.833 - 0.937）和0.805（95%CI：0.703 - 0.908）。列线图在DCA和校准曲线中显示出良好的拟合度和临床效益。
术前MRI的强化模式和肿瘤生长方式是MVI严重程度的独立危险因素，对促进个体化决策具有重要价值。
