MRI Texture Analysis Predicts p53 Status in Head and Neck Squamous Cell Carcinoma
MRI Texture Analysis Predicts p53 Status in Head and Neck Squamous Cell Carcinoma
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DOI：
10.3174/ajnr.a4110
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发表时间：
2015-01-01
影响因子：
3.5
通讯作者：
Dort, J. C.
中科院分区：
文献类型：
--
作者：
Dang, M.;Lysack, J. T.;Dort, J. C.
背景和目的：头颈部癌症是常见的，了解预后是患者管理的重要组成部分。除了肿瘤、淋巴结、转移分期系统之外，肿瘤生物标志物在了解预后和指导治疗方面变得越来越有用。我们评估是否MR成像纹理分析将正确分类口咽鳞状细胞癌根据p53 status.MATERIALS和METHODS：一个队列的16例口咽鳞状细胞癌进行了前瞻性评估，通过使用标准的临床，组织病理学和成像技术。对肿瘤进行p53染色，并由解剖病理学家评分。由神经放射科医生选择MR成像上的感兴趣区域，然后使用我们的2D快速时频变换工具进行分析。量化的纹理进行了评估，通过使用子集大小的前向选择算法在怀卡托知识分析环境。被发现是显着的特征被用来创建一个统计模型来预测p53状态。该模型进行了测试，通过使用贝叶斯网络分类器与10倍分层cross-validation.RESULTS：特征选择确定了7个显着的纹理变量，用于预测模型。由此产生的模型预测p53状态的准确率为81.3%（P <0.05）。交叉验证显示了中等水平的协议（kappa = 0.625）。结论：这项研究表明，MR成像纹理分析正确预测口咽鳞状细胞癌p53的状态与类似的80%的准确性。随着我们对肿瘤生物标志物的了解和依赖性的扩大，MR成像纹理分析值得在口咽鳞状细胞癌和其他头颈部肿瘤中进行进一步研究。
BACKGROUND AND PURPOSE: Head and neck cancer is common, and understanding the prognosis is an important part of patient management. In addition to the Tumor, Node, Metastasis staging system, tumor biomarkers are becoming more useful in understanding prognosis and directing treatment. We assessed whether MR imaging texture analysis would correctly classify oropharyngeal squamous cell carcinoma according to p53 status.MATERIALS AND METHODS: A cohort of 16 patients with oropharyngeal squamous cell carcinoma was prospectively evaluated by using standard clinical, histopathologic, and imaging techniques. Tumors were stained for p53 and scored by an anatomic pathologist. Regions of interest on MR imaging were selected by a neuroradiologist and then analyzed by using our 2D fast time-frequency transform tool. The quantified textures were assessed by using the subset-size forward-selection algorithm in the Waikato Environment for Knowledge Analysis. Features found to be significant were used to create a statistical model to predict p53 status. The model was tested by using a Bayesian network classifier with 10-fold stratified cross-validation.RESULTS: Feature selection identified 7 significant texture variables that were used in a predictive model. The resulting model predicted p53 status with 81.3% accuracy (P < .05). Cross-validation showed a moderate level of agreement (kappa = 0.625).CONCLUSIONS: This study shows that MR imaging texture analysis correctly predicts p53 status in oropharyngeal squamous cell carcinoma with similar to 80% accuracy. As our knowledge of and dependence on tumor biomarkers expand, MR imaging texture analysis warrants further study in oropharyngeal squamous cell carcinoma and other head and neck tumors.