Li Jing, Wang Yi, Wang Rui, Gao Jian-Bo, Qu Jin-Rong
Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University (Henan Cancer Hospital), Zhengzhou, China.
Department of Pathology, The Affiliated Cancer Hospital of Zhengzhou University (Henan Cancer Hospital), Zhengzhou, China.
Front Oncol. 2022 Oct 4;12:942425. doi: 10.3389/fonc.2022.942425. eCollection 2022.
To develop and externally validate a spectral CT based nomogram for the preoperative prediction of LVI in patients with resectable GC.
The two centered study contained a retrospective primary dataset of 224 pathologically confirmed gastric adenocarcinomas (161 males, 63 females; mean age: 60.57 ± 10.81 years, range: 20-86 years) and an external prospective validation dataset from the second hospital (77 males and 35 females; mean age, 61.05 ± 10.51 years, range, 31 to 86 years). Triple-phase enhanced CT scans with gemstone spectral imaging mode were performed within one week before surgery. The clinicopathological characteristics were collected, the iodine concentration (IC) of the primary tumours at arterial phase (AP), venous phase (VP), and delayed phase (DP) were measured and then normalized to aorta (nICs). Univariable analysis was used to compare the differences of clinicopathological and IC values between LVI positive and negative groups. Independent predictors for LVI were screened by multivariable logistic regression analysis in primary dataset and used to develop a nomogram, and its performance was evaluated by using ROC analysis and tested in validation dataset. Its clinical use was evaluated by decision curve analysis (DCA).
Tumor thickness, Borrmann classification, CT reported lymph node (LN) status and nICDP were independent predictors for LVI, and the nomogram based on these indicators was significantly associated with LVI (<0.001). It yielded an AUC of 0.825 (95% confidence interval [95% CI], 0.769-0.872) and 0.802 (95% CI, 0.716-0.871) in primary and validation datasets (all <0.05), with promising clinical utility by DCA.
This study presented a dual energy CT quantification based nomogram, which enables preferable preoperative individualized prediction of LVI in patients with GC.
开发并外部验证一种基于光谱CT的列线图，用于术前预测可切除胃癌患者的淋巴管侵犯（LVI）情况。
两项中心研究包含一个回顾性的主要数据集，其中有224例经病理证实的胃腺癌患者（男性161例，女性63例；平均年龄：60.57±10.81岁，范围：20 - 86岁），以及来自第二医院的一个外部前瞻性验证数据集（男性77例，女性35例；平均年龄，61.05±10.51岁，范围，31至86岁）。在手术前一周内进行采用宝石光谱成像模式的三期增强CT扫描。收集临床病理特征，测量原发肿瘤在动脉期（AP）、静脉期（VP）和延迟期（DP）的碘浓度（IC），然后将其归一化为主动脉（nICs）。采用单因素分析比较LVI阳性和阴性组之间临床病理和IC值的差异。在主要数据集中通过多因素逻辑回归分析筛选LVI的独立预测因素，并用于开发列线图，通过ROC分析评估其性能，并在验证数据集中进行测试。通过决策曲线分析（DCA）评估其临床应用价值。
肿瘤厚度、Borrmann分类、CT报告的淋巴结（LN）状态和nICDP是LVI的独立预测因素，基于这些指标的列线图与LVI显著相关（<0.001）。在主要数据集和验证数据集中，其AUC分别为0.825（95%置信区间[95%CI]，0.769 - 0.872）和0.802（95%CI，0.716 - 0.871）（均<0.05），DCA显示具有良好的临床应用价值。
本研究提出了一种基于双能量CT定量的列线图，能够对胃癌患者的LVI进行较好的术前个体化预测。
