74566The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
The Affiliated 91596Huai'an No. 1 People's Hospital of Nanjing Medical University, Huai'an, Jiangsu, China.
Technol Cancer Res Treat. 2022 Jan-Dec;21:15330338221111229. doi: 10.1177/15330338221111229.
To explore whether preoperative contrast-enhanced computed tomogrpahy (CT) can predict lymphovascular invasion (LVI) in esophageal squamous cell carcinoma (ESCC), and provide a reliable reference for the formulation of clinical individualized treatment plans. This retrospective study enrolled 228 patients with surgically resected and pathologically confirmed ESCC, including 36 patients with LVI and 192 patients without LVI. All patients underwent contrast-enhanced CT (CECT) scan within 2 weeks before the operation. Tumor size (including tumor length and maximum tumor thickness), tumor-to-normal wall enhancement ratio (TNR), and gross tumor volume (GTV) were obtained. All clinical features and CECT-derived parameters associated with LVI were analyzed by univariate and multivariate analysis. The independent predictors for LVI were identified, and their combination was built by multivariate logistic regression analysis, using the significant variables from the univariate analysis as inputs. Univariate analysis of clinical features and CECT-derived parameters revealed that age, TNR, and clinical N stage (cN stage) were significantly associated with LVI. The multivariable analysis results demonstrated that age (odds ratio [OR]: 5.32, 95% confidence interval [CI]: 2.224-12.743, <.001), TNR (OR: 5.399, 95% CI: 1.609-18.110, = .006), and cN stage (cN1: OR: 2.874, 95% CI: 1.182-6.989, = .02; cN2: OR: 6.876, 95% CI: 2.222-21.227) were identified to be independent predictors for LVI. The combination of age, TNR, and cN stage achieved a relatively higher area under the curve (AUC) (0.798), accuracy (ACC) (65.4%), sensitivity (SEN) (69.4%), specificity (SPE) (79.7%), positive predictive value (PPV) (77.4%), and negative predictive value (NPV) (71.6%). The combination of clinical features and CECT-derived parameters may be effective in predicting LVI status preoperatively in ESCC.
为了探讨术前增强 CT 能否预测食管鳞癌(ESCC)的淋巴管侵犯(LVI),为临床个体化治疗方案的制定提供可靠的参考依据。本回顾性研究纳入了 228 例经手术切除和病理证实的 ESCC 患者,其中 36 例存在 LVI,192 例不存在 LVI。所有患者均在术前 2 周内行增强 CT(CECT)扫描。获取肿瘤大小(包括肿瘤长度和最大肿瘤厚度)、肿瘤-正常壁强化比值(TNR)和大体肿瘤体积(GTV)。对与 LVI 相关的所有临床特征和 CECT 衍生参数进行单因素和多因素分析。采用单因素分析中的显著变量作为输入,通过多因素 logistic 回归分析确定 LVI 的独立预测因素,并对其进行组合。单因素分析显示,年龄、TNR 和临床 N 分期(cN 分期)与 LVI 显著相关。多因素分析结果显示,年龄(优势比 [OR]:5.32,95%置信区间 [CI]:2.224-12.743,<0.001)、TNR(OR:5.399,95%CI:1.609-18.110,=0.006)和 cN 分期(cN1:OR:2.874,95%CI:1.182-6.989,=0.02;cN2:OR:6.876,95%CI:2.222-21.227)是 LVI 的独立预测因素。年龄、TNR 和 cN 分期的组合具有较高的曲线下面积(AUC)(0.798)、准确度(ACC)(65.4%)、敏感性(SEN)(69.4%)、特异性(SPE)(79.7%)、阳性预测值(PPV)(77.4%)和阴性预测值(NPV)(71.6%)。临床特征和 CECT 衍生参数的组合可能有助于术前预测 ESCC 的 LVI 状态。