Yang Yan, Wei Huanhuan, Fu Fangfang, Wei Wei, Wu Yaping, Bai Yan, Li Qing, Wang Meiyun
Department of Medical Imaging, People's Hospital of Zhengzhou University, Henan Provincial People's Hospital, Zhengzhou, China.
Henan Key Laboratory of Neurological Imaging, Henan Provincial People's Hospital, Zhengzhou, China.
Front Radiol. 2023 Aug 8;3:1212382. doi: 10.3389/fradi.2023.1212382. eCollection 2023.
The purpose of this study was to investigate the value of a clinical radiomics model based on Positron emission tomography-computed tomography (PET-CT) radiomics features combined with clinical predictors of Lymphovascular invasion (LVI) in predicting preoperative LVI in patients with colorectal cancer (CRC).
A total of 95 CRC patients who underwent preoperative F-fluorodeoxyglucose (FDG) PET-CT examination were retrospectively enrolled. Univariate and multivariate logistic regression analyses were used to analyse clinical factors and PET metabolic data in the LVI-positive and LVI-negative groups to identify independent predictors of LVI. We constructed four prediction models based on radiomics features and clinical data to predict LVI status. The predictive efficacy of different models was evaluated according to the receiver operating characteristic curve. Then, the nomogram of the best model was constructed, and its performance was evaluated using calibration and clinical decision curves.
Mean standardized uptake value (SUVmean), maximum tumour diameter and lymph node metastasis were independent predictors of LVI in CRC patients ( < 0.05). The clinical radiomics model obtained the best prediction performance, with an Area Under Curve (AUC) of 0.922 (95%CI 0.820-0.977) and 0.918 (95%CI 0.782-0.982) in the training and validation cohorts, respectively. A nomogram based on the clinical radiomics model was constructed, and the calibration curve fitted well ( > 0.05).
The clinical radiomics prediction model constructed in this study has high value in the preoperative individualized prediction of LVI in CRC patients.
本研究旨在探讨基于正电子发射断层扫描-计算机断层扫描（PET-CT）影像组学特征联合淋巴管侵犯（LVI）临床预测指标的临床影像组学模型在预测结直肠癌（CRC）患者术前LVI中的价值。
回顾性纳入95例接受术前F-氟脱氧葡萄糖（FDG）PET-CT检查的CRC患者。采用单因素和多因素逻辑回归分析对LVI阳性和LVI阴性组的临床因素和PET代谢数据进行分析，以确定LVI的独立预测指标。我们基于影像组学特征和临床数据构建了四个预测模型来预测LVI状态。根据受试者工作特征曲线评估不同模型的预测效能。然后，构建最佳模型的列线图，并使用校准和临床决策曲线评估其性能。
平均标准化摄取值（SUVmean）、最大肿瘤直径和淋巴结转移是CRC患者LVI的独立预测指标（<0.05）。临床影像组学模型获得了最佳预测性能，在训练队列和验证队列中的曲线下面积（AUC）分别为0.922（95%CI 0.820-0.977）和0.918（95%CI 0.782-0.982）。构建了基于临床影像组学模型的列线图，校准曲线拟合良好（>0.05）。
本研究构建的临床影像组学预测模型在CRC患者术前LVI的个体化预测中具有较高价值。
