Department of Oral and Maxillofacial Surgery, Hospital of Stomatology, Guanghua School of Stomatology, Sun Yat-Sen University, Guangzhou, China.
Guangdong Provincial Key Laboratory of Stomatology, Guangzhou, China.
J Magn Reson Imaging. 2022 Jul;56(1):196-209. doi: 10.1002/jmri.28019. Epub 2021 Dec 10.
Adequate safe margin in tongue cancer radical surgery is one of the most important prognostic factors. However, the role of peritumoral tissues in predicting lymph node metastasis (LNM) and prognosis using radiomics analysis remains unclear.
To investigate whether magnetic resonance imaging (MRI)-based radiomics analysis with peritumoral extensions contributes toward the prediction of LNM and prognosis in tongue cancer.
Retrospective.
Two hundred and thirty-six patients (38.56% female) with tongue cancer (training set, N = 157; testing set, N = 79; 37.58% and 40.51% female for each).
FIELD STRENGTH/SEQUENCE: 1.5 T; T2-weighted turbo spin-echo images.
Radiomics models (R , R , R , R , R ) were developed with features extracted from the primary tumor without or with peritumoral extensions (3, 5, 10, and 15 mm, respectively). Clinicopathological characteristics selected from univariate analysis, including MRI-reported LN status, radiological extrinsic lingual muscle invasion, and pathological depth of invasion (DOI) were further incorporated into radiomics models to develop combined radiomics models (CR , CR , CR , CR , CR ). Finally, the model performance was validated in the testing set. DOI was measured from the adjacent normal mucosa to the deepest point of tumor invasion.
Chi-square test, regression analysis, receiver operating characteristic curve (ROC) analysis, decision analysis, spearman correlation analysis. The Delong test was used to compare area under the ROC (AUC). P < 0.05 was considered statistically significant.
Of all the models, the CR reached the highest AUC of 0.995 in the training set and 0.872 in the testing set. Radiomics features were significantly correlated with pathological DOI (correlation coefficients, -0.157 to -0.336). The CR was an independent indicator for poor disease-free survival (hazard ratio, 5.250) and overall survival (hazard ratio, 17.464) in the testing set.
Radiomics analysis with a 10-mm peritumoral extension had excellent power to predict LNM and prognosis in tongue cancer.
在舌癌根治术中，足够的安全切缘是最重要的预后因素之一。然而，利用影像组学分析，肿瘤周围组织在预测淋巴结转移（LNM）和预后中的作用尚不清楚。
探讨磁共振成像（MRI）基于肿瘤周围延伸的影像组学分析是否有助于预测舌癌的 LNM 和预后。
回顾性。
236 例（38.56%为女性）舌癌患者（训练集，N=157；测试集，N=79；每组分别有 37.58%和 40.51%为女性）。
磁场强度/序列：1.5T；T2 加权涡轮自旋回波图像。
使用从原发肿瘤中提取的特征，分别建立不包括和包括肿瘤周围延伸（3、5、10 和 15mm）的影像组学模型（R 、R 、R 、R 、R ）。从单变量分析中选择包括 MRI 报告的淋巴结状态、影像学外向性舌肌侵犯和病理浸润深度（DOI）在内的临床病理特征，进一步纳入影像组学模型，建立联合影像组学模型（CR 、CR 、CR 、CR 、CR ）。最后，在测试集中验证模型性能。DOI 是从相邻正常黏膜到肿瘤侵袭最深处测量的。
卡方检验、回归分析、受试者工作特征曲线（ROC）分析、决策分析、斯皮尔曼相关分析。采用 Delong 检验比较 ROC 下面积（AUC）。P<0.05 为统计学显著。
所有模型中，CR 在训练集的 AUC 为 0.995，在测试集的 AUC 为 0.872，达到最高。影像组学特征与病理 DOI 显著相关（相关系数为-0.157 至-0.336）。在测试集中，CR 是疾病无进展生存（风险比，5.250）和总生存（风险比，17.464）的独立预后因素。
肿瘤周围 10mm 延伸的影像组学分析具有良好的预测舌癌 LNM 和预后的能力。
