Department of Radiology, Xi'an Jiaotong University, Xi'an, 710049, China.
Department of Radiology, Baoji Central Hospital, Baoji, 721000, China.
BMC Pulm Med. 2023 Apr 14;23(1):122. doi: 10.1186/s12890-023-02422-7.
To investigate the value of preoperative computed tomography (CT) texture features, routine imaging features, and clinical features in the prognosis of non-small cell lung cancer (NSCLC) after radical resection.
Demographic parameters and clinically features were analyzed in 107 patients with stage I-IIIB NSCLC, while 73 of these patients received CT scanning and radiomic characteristics for prognosis assessment. Texture analysis features include histogram, gray size area matrix and gray co-occurrence matrix features. The clinical risk features were identified using univariate and multivariate logistic analyses. By incorporating the radiomics score (Rad-score) and clinical risk features with multivariate cox regression, a combined nomogram was built. The nomogram performance was assessed by its calibration, clinical usefulness and Harrell's concordance index (C-index). The 5-year OS between the dichotomized subgroups was compared using Kaplan-Meier (KM) analysis and the log-rank test.
Consisting of 4 selected features, the radiomics signature showed a favorable discriminative performance for prognosis, with an AUC of 0.91 (95% CI: 0.84 ~ 0.97). The nomogram, consisting of the radiomics signature, N stage, and tumor size, showed good calibration. The nomogram also exhibited prognostic ability with a C-index of 0.91 (95% CI, 0.86-0.95) for OS. The decision curve analysis indicated that the nomogram was clinically useful. According to the KM survival curves, the low-risk group had higher 5-year survival rate compared to high-risk.
The as developed nomogram, combining with preoperative radiomics evidence, N stage, and tumor size, has potential to preoperatively predict the prognosis of NSCLC with a high accuracy and could assist to treatment for the NSCLC patients in the clinic.
探讨术前计算机断层扫描(CT)纹理特征、常规影像学特征和临床特征在非小细胞肺癌(NSCLC)根治性切除术后预后中的价值。
分析 107 例ⅠB-ⅢB 期 NSCLC 患者的人口统计学参数和临床特征,其中 73 例患者接受 CT 扫描和放射组学特征进行预后评估。纹理分析特征包括直方图、灰度大小区域矩阵和灰度共生矩阵特征。采用单变量和多变量逻辑分析识别临床风险特征。通过将放射组学评分(Rad-score)和临床风险特征与多变量 Cox 回归相结合,构建了一个联合列线图。通过校准、临床实用性和 Harrell 的一致性指数(C-index)评估列线图的性能。通过 Kaplan-Meier(KM)分析和对数秩检验比较二分类亚组之间的 5 年 OS。
由 4 个选定特征组成的放射组学特征对预后具有良好的区分性能,AUC 为 0.91(95%CI:0.84~0.97)。列线图由放射组学特征、N 分期和肿瘤大小组成,具有良好的校准度。该列线图也具有预后能力,OS 的 C-index 为 0.91(95%CI,0.86-0.95)。决策曲线分析表明该列线图具有临床实用性。根据 KM 生存曲线,低风险组的 5 年生存率高于高风险组。
该列线图结合术前放射组学证据、N 分期和肿瘤大小,具有预测 NSCLC 预后的高准确性潜力,可辅助临床 NSCLC 患者的治疗。