Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, No.366, Taishan Street, Taian, Shandong Province, 271000, China.
Department of Radiology, Taian City Central Hospital, No.29, Longtan Road, Taian, Shandong Province, 271000, China.
BMC Cancer. 2023 Nov 27;23(1):1158. doi: 10.1186/s12885-023-11332-0.
Thymic epithelial tumors (TETs) are the most common primary neoplasms of the anterior mediastinum. Different risk subgroups of TETs have different prognosis and therapeutic strategies, therefore, preoperative identification of different risk subgroups is of high clinical significance. This study aims to explore the diagnostic efficiency of quantitative computed tomography (CT) parameters combined with preoperative systemic inflammatory markers in differentiating low-risk thymic epithelial tumors (LTETs) from high-risk thymic epithelial tumors (HTETs).
74 Asian patients with TETs confirmed by biopsy or postoperative pathology between January 2013 and October 2022 were collected retrospectively and divided into two risk subgroups: LTET group (type A, AB and B1 thymomas) and HTET group (type B2, B3 thymomas and thymic carcinoma). Statistical analysis were performed between the two groups in terms of quantitative CT parameters and preoperative systemic inflammatory markers. Multivariate logistic regression analysis was used to determine the independent predictors of risk subgroups of TETs. The area under curve (AUC) and optimal cut-off values were calculated by receiver operating characteristic (ROC) curves.
47 TETs were in LTET group, while 27 TETs were in HTET group. In addition to tumor size and CT value of the tumor on plain scan, there were statistical significance comparing in CT value of the tumor on arterial phase (CTv-AP) and venous phase (CTv-VP), and maximum enhanced CT value (CE) of the tumor between the two groups (for all, P < 0.05). For systemic inflammatory markers, HTET group was significantly higher than LTET group (for all, P < 0.05), including platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR) and systemic immune-inflammation index (SII). Multivariate logistic regression analysis showed that NLR (odds ratio [OR] = 2.511, 95% confidence interval [CI]: 1.322-4.772, P = 0.005), CTv-AP (OR = 0.939, 95%CI: 0.888-0.994, P = 0.031) and CTv-VP (OR = 0.923, 95%CI: 0.871-0.979, P = 0.008) were the independent predictors of risk subgroups of TETs. The AUC value of 0.887 for the combined model was significantly higher than NLR (0.698), CTv-AP (0.800) or CTv-VP (0.811) alone. The optimal cut-off values for NLR, CTv-AP and CTv-VP were 2.523, 63.44 Hounsfeld Unit (HU) and 88.29HU, respectively.
Quantitative CT parameters and preoperative systemic inflammatory markers can differentiate LTETs from HTETs, and the combined model has the potential to improve diagnostic efficiency and to help the patient management.
胸腺瘤（TETs）是前纵隔最常见的原发性肿瘤。不同风险亚组的胸腺瘤具有不同的预后和治疗策略，因此术前识别不同的风险亚组具有重要的临床意义。本研究旨在探讨定量 CT（CT）参数与术前全身炎症标志物联合在区分低危胸腺瘤（LTETs）和高危胸腺瘤（HTETs）中的诊断效率。
回顾性收集了 2013 年 1 月至 2022 年 10 月期间经活检或术后病理证实的 74 例亚洲 TETs 患者，分为两组：LTET 组（A型、AB 型和 B1 型胸腺瘤）和 HTET 组（B2 型、B3 型胸腺瘤和胸腺癌）。对两组患者的定量 CT 参数和术前全身炎症标志物进行统计学分析。采用多变量逻辑回归分析确定 TETs 风险亚组的独立预测因子。通过受试者工作特征（ROC）曲线计算曲线下面积（AUC）和最佳截断值。
74 例 TETs 中，47 例为 LTETs，27 例为 HTETs。除了肿瘤大小和平扫 CT 值外，两组患者的动脉期 CT 值（CTv-AP）、静脉期 CT 值（CTv-VP）和肿瘤最大增强 CT 值（CE）均有统计学差异（均 P<0.05）。对于全身炎症标志物，HTET 组明显高于 LTET 组（均 P<0.05），包括血小板与淋巴细胞比值（PLR）、中性粒细胞与淋巴细胞比值（NLR）和全身免疫炎症指数（SII）。多变量逻辑回归分析显示，NLR（比值比[OR]＝2.511，95%置信区间[CI]：1.322-4.772，P＝0.005）、CTv-AP（OR＝0.939，95%CI：0.888-0.994，P＝0.031）和 CTv-VP（OR＝0.923，95%CI：0.871-0.979，P＝0.008）是 TETs 风险亚组的独立预测因子。联合模型的 AUC 值为 0.887，明显高于 NLR（0.698）、CTv-AP（0.800）或 CTv-VP（0.811）单独使用。NLR、CTv-AP 和 CTv-VP 的最佳截断值分别为 2.523、63.44Hounsfeld Unit（HU）和 88.29HU。
定量 CT 参数和术前全身炎症标志物可区分 LTETs 和 HTETs，联合模型具有提高诊断效率和帮助患者管理的潜力。
