基于能谱CT纹理分析在预测胃癌术前淋巴结转移中的价值

王小雷; 高玉青; 徐鹤; 张书海; 李淑华; 赵灿灿; 段绍峰; 谢宗玉

doi:10.13898/j.cnki.issn.1000-2200.2021.01.006

基于能谱CT纹理分析在预测胃癌术前淋巴结转移中的价值

Value of texture analysis based on spectral CT in predicting preoperative lymph node metastasis of gastric cancer

摘要

摘要:
目的探讨能谱CT纹理分析在胃癌病人术前预测淋巴结转移中的价值。
方法回顾性分析80例经手术切除病理证实的胃癌病人（训练组为57例，验证组为23例）。使用专用的纹理分析软件AK对术前静脉期能谱70 keV CT图像进行分割病变并提取影像学特征。使用Mann-Whitney U检验分析2组之间的特征，保留P < 0.05的特征，进一步通过logistic回归分析寻找有鉴别能力的特征（P < 0.05），然后使用最小冗余最大相关方法剔除冗余，但保留与标签相关性最高的10个特征，使用逐步多元logistic回归，构建预测模型，并构建最终模型，通过ROC分析对模型的性能进行评价。
结果纹理特征方面，最小冗余最大相关方法选择的10个放射组学相关特征对训练组及验证组的鉴别能力较好（AUC>0.64）；多元logistic回归预测模型的AUC为0.79（0.69~0.89）。
结论基于能谱CT的纹理分析有望成为胃癌病人术前淋巴结转移预测的非侵入性工具。

Abstract:
ObjectiveTo study the value of spectral CT texture analysis in predicting preoperative lymph node metastasis in patients with gastric cancer.
MethodsEighty patients(including 57 cases in training group and 23 cases in verification group) with gastric cancer confirmed by surgical resection and pathology were retrospectively analyzed.The special texture analysis software AK was used to segment the lesions and extract the imaging features on the preoperative spectral CT 70 keV venous phase cross-sectional images.The Mann-Whitney U test was used to analyze the features between two groups, and the P < 0.05 features were preserved.The discriminative features were further found by single factor logistic regression analysis.The minimum redundancy maximum correlation method(MRMR) was used to eliminate the 10 features with the highest correlation with the label.Stepwise multiple logistic regression was used to construct the prediction model and final model.The performance of the model was evaluated using ROC analysis.
ResultsIn terms of texture features, the 10 radiology-related features selected by MRMR had better discriminative ability for training group and verification group(AUC>0.64), and the AUC of multivariate logistic regression prediction model was 0.79(0.69-0.89).
ConclusionsThe texture analysis based on spectral CT is expected to be a non-invasive tool for predicting preoperative lymph node metastasis in patients with gastric cancer.

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