基于 CT 影像组学的无创预测肝细胞癌 NQO1 表达水平的研究。
CT radiomics for noninvasively predicting NQO1 expression levels in hepatocellular carcinoma.
机构信息
Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, PR China.
Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, PR China.
出版信息
PLoS One. 2023 Sep 11;18(9):e0290900. doi: 10.1371/journal.pone.0290900. eCollection 2023.
Using noninvasive radiomics to predict pathological biomarkers is an innovative work worthy of exploration. This retrospective cohort study aimed to analyze the correlation between NAD(P)H quinone oxidoreductase 1 (NQO1) expression levels and the prognosis of patients with hepatocellular carcinoma (HCC) and to construct radiomic models to predict the expression levels of NQO1 prior to surgery. Data of patients with HCC from The Cancer Genome Atlas (TCGA) and the corresponding arterial phase-enhanced CT images from The Cancer Imaging Archive were obtained for prognosis analysis, radiomic feature extraction, and model development. In total, 286 patients with HCC from TCGA were included. According to the cut-off value calculated using R, patients were divided into high-expression (n = 143) and low-expression groups (n = 143). Kaplan-Meier survival analysis showed that higher NQO1 expression levels were significantly associated with worse prognosis in patients with HCC (p = 0.017). Further multivariate analysis confirmed that high NQO1 expression was an independent risk factor for poor prognosis (HR = 1.761, 95% CI: 1.136-2.73, p = 0.011). Based on the arterial phase-enhanced CT images, six radiomic features were extracted, and a new bi-regional radiomics model was established, which could noninvasively predict higher NQO1 expression with good performance. The area under the curve (AUC) was 0.9079 (95% CI 0.8127-1.0000). The accuracy, sensitivity, and specificity were 0.86, 0.88, and 0.84, respectively, with a threshold value of 0.404. The data verification of our center showed that this model has good predictive efficiency, with an AUC of 0.8791 (95% CI 0.6979-1.0000). In conclusion, there existed a significant correlation between the CT image features and the expression level of NQO1, which could indirectly reflect the prognosis of patients with HCC. The predictive model based on arterial phase CT imaging features has good stability and diagnostic efficiency and is a potential means of identifying the expression level of NQO1 in HCC tissues before surgery.
使用无创放射组学预测病理生物标志物是一项值得探索的创新工作。本回顾性队列研究旨在分析 NAD(P)H 醌氧化还原酶 1(NQO1)表达水平与肝细胞癌(HCC)患者预后的相关性,并构建放射组学模型以预测手术前 NQO1 的表达水平。从 The Cancer Genome Atlas(TCGA)获得 HCC 患者的数据以及来自 The Cancer Imaging Archive 的相应动脉期增强 CT 图像,用于预后分析、放射组学特征提取和模型开发。总共纳入了来自 TCGA 的 286 名 HCC 患者。根据 R 计算的截止值,患者被分为高表达组(n=143)和低表达组(n=143)。Kaplan-Meier 生存分析表明,NQO1 表达水平较高与 HCC 患者预后较差显著相关(p=0.017)。进一步的多变量分析证实,高 NQO1 表达是预后不良的独立危险因素(HR=1.761,95%CI:1.136-2.73,p=0.011)。基于动脉期增强 CT 图像,提取了 6 个放射组学特征,并建立了一个新的双区域放射组学模型,可以无创地预测更高的 NQO1 表达,具有良好的性能。曲线下面积(AUC)为 0.9079(95%CI 0.8127-1.0000)。准确性、敏感性和特异性分别为 0.86、0.88 和 0.84,阈值为 0.404。本中心的数据验证表明,该模型具有良好的预测效率,AUC 为 0.8791(95%CI 0.6979-1.0000)。总之,CT 图像特征与 NQO1 表达水平之间存在显著相关性,这可以间接反映 HCC 患者的预后。基于动脉期 CT 成像特征的预测模型具有良好的稳定性和诊断效率,是术前识别 HCC 组织中 NQO1 表达水平的一种潜在手段。
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