Department of Ultrasound, Putuo People's Hospital, School of Medicine, Tongji University, Shanghai, China.
Department of Radiology, Tongde Hospital of Zhejiang Province, Hangzhou, Zhejiang, China.
Abdom Radiol (NY). 2024 Apr;49(4):1306-1319. doi: 10.1007/s00261-024-04205-y. Epub 2024 Feb 26.
To explore the value of multi-parametric MRI (mp-MRI) radiomic model for preoperative prediction of recurrence and/or metastasis (RM) as well as survival benefits in patients with rectal cancer.
A retrospective analysis of 234 patients from two centers with histologically confirmed rectal adenocarcinoma was conducted. All patients were divided into three groups: training, internal validation (in-vad) and external validation (ex-vad) sets. In the training set, radiomic features were extracted from T2WI, DWI, and contrast enhancement T1WI (CE-T1) sequence. Radiomic signature (RS) score was then calculated for feature screening to construct a rad-score model. Subsequently, preoperative clinical features with statistical significance were selected to construct a clinical model. Independent predictors from clinical and RS related to RM were selected to build the combined model and nomogram.
After feature extraction, 26 features were selected to construct the rad-score model. RS (OR = 0.007, p < 0.01), MR-detected T stage (mrT) (OR = 2.92, p = 0.03) and MR-detected circumferential resection margin (mrCRM) (OR = 4.70, p = 0.01) were identified as independent predictors of RM. Then, clinical model and combined model were constructed. ROC curve showed that the AUC, accuracy, sensitivity and specificity of the combined model were higher than that of the other two models in three sets. Kaplan-Meier curves showed that poorer disease-free survival (DFS) time was observed for patients in pT3-4 stages with low RS score (p < 0.001), similar results were also found in pCRM-positive patients (p < 0.05).
The mp-MRI radiomics model can be served as a noninvasive and accurate predictors of RM in rectal cancer that may support clinical decision-making.
探索多参数 MRI（mp-MRI）放射组学模型在预测直肠癌患者复发和/或转移（RM）以及生存获益方面的价值。
对来自两个中心的 234 例经组织学证实的直肠腺癌患者进行回顾性分析。所有患者分为三组：训练组、内部验证组（in-vad）和外部验证组（ex-vad）。在训练组中，从 T2WI、DWI 和对比增强 T1WI（CE-T1）序列中提取放射组学特征。然后计算放射组学特征（RS）评分，进行特征筛选，构建 rad-score 模型。随后，选择具有统计学意义的术前临床特征构建临床模型。选择与 RM 相关的临床和 RS 的独立预测因素构建联合模型和列线图。
在特征提取后，选择 26 个特征构建 rad-score 模型。RS（OR=0.007，p<0.01）、MR 检测 T 分期（mrT）（OR=2.92，p=0.03）和 MR 检测环周切缘（mrCRM）（OR=4.70，p=0.01）被确定为 RM 的独立预测因素。然后，构建了临床模型和联合模型。ROC 曲线显示，在三个组中，联合模型的 AUC、准确性、敏感性和特异性均高于其他两个模型。Kaplan-Meier 曲线显示，在 RS 评分较低的 pT3-4 期患者中，无病生存（DFS）时间较差（p<0.001），在 pCRM 阳性患者中也观察到类似的结果（p<0.05）。
mp-MRI 放射组学模型可作为预测直肠癌 RM 的一种非侵入性、准确的预测指标，可能有助于临床决策。
