School of Computer and Information Engineering, Hanshan Normal University, Chaozhou, 521041, Guangdong, China.
School of Mathematics and Statistics, Hanshan Normal University, Chaozhou, 521041, Guangdong, China.
Sci Rep. 2024 Oct 30;14(1):26082. doi: 10.1038/s41598-024-77680-4.
Programmed cell death ligand-1 (PD-L1) is an ideal checkpoint for immunohistochemical detection. The method of obtaining PD-L1 expression through biopsy can impact the accurate assessment of PD-L1 expression due to the spatial and temporal heterogeneity of tumors. Because of the limited sample size, biopsies often give only a localized picture of the tumor. In this retrospective study, a total of 2,386 metabolic tumor volume (MTV) features were extracted from F-FDG PET-CT images. A radiomics model was developed to holistically and non-invasively assess PD-L1 expression in patients with esophageal squamous cell carcinoma by identifying seven independent factors through feature screening. The radiomics model shows effective discrimination, with an area under the receiver operating characteristic curve of 0.888 [95% confidence interval (CI): 0.831-0.945] and 0.889 (95% CI: 0.706-1.000) for the training and validation cohorts, respectively. The results of the decision curve analysis demonstrated that utilizing the radiation model to forecast PD-L1 expression levels yielded more net benefits at threshold probabilities below 0.669. The clinical impact curves demonstrate that when the threshold probability is less than 0.501, the loss-to-benefit ratio is less than one in all cases.
程序性细胞死亡配体-1(PD-L1)是免疫组织化学检测的理想检查点。由于肿瘤的空间和时间异质性,通过活检获得 PD-L1 表达的方法可能会影响 PD-L1 表达的准确评估。由于样本量有限,活检通常只能提供肿瘤的局部情况。在这项回顾性研究中,从 F-FDG PET-CT 图像中提取了 2386 个代谢肿瘤体积(MTV)特征。通过特征筛选,确定了 7 个独立因素,建立了一个放射组学模型,通过整体和非侵入性的方法评估食管鳞状细胞癌患者的 PD-L1 表达。该放射组学模型显示出有效的判别能力,在训练和验证队列中的受试者工作特征曲线下面积分别为 0.888(95%置信区间:0.831-0.945)和 0.889(95%置信区间:0.706-1.000)。决策曲线分析的结果表明,利用放射模型预测 PD-L1 表达水平在阈值概率低于 0.669 时会产生更多的净收益。临床影响曲线表明,当阈值概率小于 0.501 时,在所有情况下,损失与收益的比率都小于 1。