Ren Jiliang, Yuan Ying, Tao Xiaofeng
Department of Radiology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, No. 639 Zhizaoju Road, Shanghai, 200010, China.
Eur Radiol. 2022 Apr;32(4):2739-2747. doi: 10.1007/s00330-021-08310-0. Epub 2021 Oct 12.
To investigate the feasibility of whole-tumor histogram analysis of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) MRI for predicting occult lymph node metastasis (LNM) in early-stage oral tongue squamous cell cancer (OTSCC).
This retrospective study included 55 early-stage OTSCC (cT1-2N0M0) patients; 34 with pathological LNM and 21 without. Eight whole-tumor histogram features were extracted from quantitative apparent diffusion coefficient (ADC) maps and two semi-quantitative DCE parametric maps (wash-in and wash-out). The clinicopathological factors and histogram features were compared between the two groups. Stepwise logistic regression was used to identify independent predictors. Receiver operating characteristic curves were generated to assess the performances of significant variables and a combined model for predicting occult LNM.
MRI-determined depth of invasion and ADC was significantly higher in the LNM group, with respective areas under the curve (AUCs) of 0.67 and 0.69, and accuracies of 0.73 and 0.73. ADC. ADC and wash-in were significantly lower in the LNM group, with respective AUCs of 0.68, 0.71, and 0.69, and accuracies of 0.65, 0.71, and 0.64. Histogram features from wash-out maps were not significantly associated with cervical node status. In the logistic regression analysis, ADC, ADC and wash-in were independent predictors. The combined model yielded the best predictive performance, with an AUC of 0.87 and an accuracy of 0.82.
Whole-tumor histogram analysis of ADC and wash-in maps is a feasible tool for preoperative evaluation of cervical node status in early-stage OTSCC.
• Histogram analysis of parametric maps from DWI and DCE-MRI may assist the prediction of occult LNM in early-stage OTSCC. • ADC, ADC, and wash-in were independent predictors. • The combined model exhibited good predictive performance, with an accuracy of 0.82.
探讨扩散加权成像（DWI）和动态对比增强（DCE）MRI的全肿瘤直方图分析预测早期口腔舌鳞状细胞癌（OTSCC）隐匿性淋巴结转移（LNM）的可行性。
本回顾性研究纳入55例早期OTSCC（cT1 - 2N0M0）患者，其中34例有病理LNM，21例无病理LNM。从定量表观扩散系数（ADC）图和两个半定量DCE参数图（流入和流出）中提取8个全肿瘤直方图特征。比较两组的临床病理因素和直方图特征。采用逐步逻辑回归确定独立预测因素。绘制受试者工作特征曲线以评估显著变量和预测隐匿性LNM的联合模型的性能。
LNM组MRI确定的浸润深度和ADC显著更高，曲线下面积（AUC）分别为0.67和0.69，准确率分别为0.73和0.73。LNM组的ADC、ADC和流入显著更低，AUC分别为0.68、0.71和0.69，准确率分别为0.65、0.71和0.64。流出图的直方图特征与颈部淋巴结状态无显著相关性。在逻辑回归分析中，ADC、ADC和流入是独立预测因素。联合模型具有最佳预测性能，AUC为0.87，准确率为0.82。
ADC图和流入图的全肿瘤直方图分析是术前评估早期OTSCC颈部淋巴结状态的可行工具。
• DWI和DCE - MRI参数图的直方图分析可能有助于预测早期OTSCC的隐匿性LNM。• ADC、ADC和流入是独立预测因素。• 联合模型表现出良好预测性能，准确率为0.82。
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