| 李庆龙,詹鹏超,邢静静,刘星,梁盼,张永高,高剑波.临床资料联合CT影像组学特征评估胃癌程序性死亡配体1状态[J].中国医学影像技术,2024,40(9):1371~1376 |
| 临床资料联合CT影像组学特征评估胃癌程序性死亡配体1状态 |
| Clinical data combined with CT radiomics features for evaluating programmed cell death-ligand 1 status in gastric cancer |
| 投稿时间：2024-02-08 修订日期：2024-05-02 |
| DOI：10.13929/j.issn.1003-3289.2024.09.020 |
| 中文关键词: 胃肿瘤 程序性细胞死亡1配体2蛋白 体层摄影术,X线计算机 影像组学 |
| 英文关键词:stomach neoplasms programmed cell death 1 ligand 2 protein tomography, X-ray computed radiomics |
| 基金项目: |
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| 摘要点击次数: 525 |
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| 中文摘要: |
| 目的 观察临床资料联合CT影像组学特征评估胃癌程序性死亡配体1(PD-L1)状态的价值。方法 回顾性按7[DK(]∶[DK)]3比例将277例胃癌患者随机分为训练集(n=195)与验证集(n=82):训练集含PD-L1阳性亚组88例、阴性亚组107例,验证集各含37及45例。比较不同集别亚组间临床及常规CT特征,分析胃癌PD-L1状态的独立影响因素,基于CT筛选影像组学特征,建立临床模型、影像组学模型及临床-影像组学联合模型,观察各模型评估胃癌PD-L1状态的效能。结果 训练集亚组间Borrmann分型、cN分期、cM分期、临床分期、肿瘤最大径及厚径差异均有统计学意义(P均＜0.05);Borrmann分型、临床分期及肿瘤厚径均为PD-L1阳性的独立影响因素(P均＜0.05)。临床模型、影像组学模型及临床-影像组学联合模型评估训练集胃癌PD-L1状态的曲线下面积(AUC)分别为0.748、0.832及0.841,在验证集分别为0.657、0.801及0.789;临床模型的AUC均低于其他模型(P均＜0.05)。结论 临床资料联合CT影像组学特征有助于评估胃癌PD-L1状态。 |
| 英文摘要: |
| Objective To observe the value of clinical data combined with CT radiomics features for evaluating programmed cell death-ligand 1 (PD-L1) status in gastric cancer. Methods Totally 277 gastric cancer patients were retrospectively enrolled and randomly divided into training set (n=195) and validation set (n=82) at the ratio of 7 ∶ 3. There were 88 cases in PD-L1 positive subgroup and 107 cases in negative subgroup of training set, while 37 and 45 cases of validation set, respectively. The clinical and conventional CT features were compared between subgroups in both sets, the independent influencing factors of PD-L1 status in gastric cancer were analyzed, and radiomic features were screened based on CT data. Then clinical model, radiomics model and clinical-radiomics model were established, and the efficacy of each model for evaluating PD-L1 status in gastric cancer was observed. Results In training set, Borrmann type, cN stage, cM stage, clinical stage, maximum diameter and thickness were significant difference between subgroups (all P＜0.05). Borrmann type, clinical stage and the thickness were all independent influencing factors of PD-L1 positivity (all P＜0.05). The area under the curve (AUC) of clinical model, radiomic model and clinical-radiomics model for evaluating PD-L1 status in gastric cancer in training set was 0.748, 0.832 and 0.841, respectively, and was 0.657, 0.801 and 0.789 in validation set, respectively. AUC of clinical model was lower than the other models (all P＜0.05). Conclusion Clinical data combined with CT radiomics features was helpful for evaluating PD-L1 status in gastric cancer. |
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