Li Pinxiong, Liang Yun, Zeng Baozhen, Yang Guangjun, Zhu Chao, Zhao Ke, Xu Zeyan, Wang Guiqu, Han Chu, Ye Huifen, Liu Zaiyi, Zhu Yun, Liang Changhong
Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan Er Road, Guangzhou 510080, China; Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan Er Road, Guangzhou 510080, China.
Department of Hepatobiliary Surgery, The First Affiliated Hospital of Kunming Medical University, 295 Xichang Road, Kunming 650032, China.
Eur J Radiol. 2022 Jun;151:110309. doi: 10.1016/j.ejrad.2022.110309. Epub 2022 Apr 9.
Intra-tumoral tertiary lymphoid structures (TLSs) are associated with a favorable prognosis for patients with hepatocellular carcinoma (HCC). We aimed to identify image features related to TLSs and develop a nomogram for preoperative noninvasive prediction of intra-tumoral TLSs.
This retrospective study enrolled patients with HCC who underwent contrast-enhanced computed tomography before surgery between January 2014 and September 2020. Two radiologists retrospectively and independently reviewed the CT imaging features, and interobserver agreement was assessed. Univariable and multivariable logistic regression analyses were applied to investigate clinical laboratory data and imaging features related to TLSs. A regression-based predictive model and nomogram were constructed using the identified predictors. Nomogram diagnostic performance was assessed with the area under the receiver operating characteristic curve (AUC) and calibration curves, and validated using 5-fold cross-validation.
Ninety-three of the 142 HCCs were TLS + HCCs. Multivariable analyses identified intratumor arteries (odds ratio [OR]: 0.23; 95% confidence interval [CI]: 0.07-0.63; p = 0.007), intratumor hemorrhage (OR: 0.08; 95% CI: 0.01-0.50; p = 0.012), positive HBsAg or HCVAB status (OR: 4.52; 95% CI: 1.65-13.29; p = 0.004), platelet count (≥186.5 × 10 /L, OR: 0.38; 95% CI: 0.16-0.86; p = 0.022), and aspartate transaminase level (≥33.2 IU/l, OR: 0.24; 95% CI: 0.09-0.59; p = 0.003) as independent predictors of intra-tumoral TLSs. AUC of the regression-based model was 0.79 (95% CI:0.72-0.86) and average AUC at 5-fold cross-validation was 0.75 (95% CI: 0.71-0.80).
CT-based nomogram is promising for preoperative prediction of intra-tumoral TLS in HCC.
肿瘤内三级淋巴结构(TLSs)与肝细胞癌(HCC)患者的良好预后相关。我们旨在识别与TLSs相关的影像特征,并开发一种列线图用于术前无创预测肿瘤内TLSs。
这项回顾性研究纳入了2014年1月至2020年9月期间术前接受对比增强计算机断层扫描的HCC患者。两名放射科医生回顾性地独立评估CT影像特征,并评估观察者间的一致性。应用单变量和多变量逻辑回归分析来研究与TLSs相关的临床实验室数据和影像特征。使用确定的预测因子构建基于回归的预测模型和列线图。通过受试者操作特征曲线(AUC)下面积和校准曲线评估列线图的诊断性能,并使用五折交叉验证进行验证。
142例HCC中有93例为TLS + HCC。多变量分析确定肿瘤内动脉(比值比[OR]:0.23;95%置信区间[CI]:0.07 - 0.63;p = 0.007)、肿瘤内出血(OR:0.08;95% CI:0.01 - 0.50;p = 0.012)、HBsAg或HCVAB阳性状态(OR:4.52;95% CI:1.65 - 13.29;p = 0.004)、血小板计数(≥186.5×10⁹/L,OR:0.38;95% CI:0.16 - 0.86;p = 0.022)以及天冬氨酸转氨酶水平(≥33.2 IU/L,OR:0.24;95% CI:0.09 - 0.59;p = 0.003)为肿瘤内TLSs的独立预测因子。基于回归的模型的AUC为0.79(95% CI:0.72 - 0.86),五折交叉验证时的平均AUC为0.75(95% CI:0.71 - 0.80)。
基于CT的列线图在术前预测HCC肿瘤内TLS方面具有前景。