AUTHOR=Jiang Yuming , Wang Wei , Chen Chuanli , Zhang Xiaodong , Zha Xuefan , Lv Wenbing , Xie Jingjing , Huang Weicai , Sun Zepang , Hu Yanfeng , Yu Jiang , Li Tuanjie , Zhou Zhiwei , Xu Yikai , Li Guoxin 

TITLE=Radiomics Signature on Computed Tomography Imaging: Association With Lymph Node Metastasis in Patients With Gastric Cancer

JOURNAL=Frontiers in Oncology

VOLUME=9

YEAR=2019

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2019.00340

DOI=10.3389/fonc.2019.00340

ISSN=2234-943X

ABSTRACT=<p><bold>Background:</bold> To evaluate whether radiomic feature-based computed tomography (CT) imaging signatures allow prediction of lymph node (LN) metastasis in gastric cancer (GC) and to develop a preoperative nomogram for predicting LN status.</p><p><bold>Methods:</bold> We retrospectively analyzed radiomics features of CT images in 1,689 consecutive patients from three cancer centers. The prediction model was developed in the training cohort and validated in internal and external validation cohorts. Lasso regression model was utilized to select features and build radiomics signature. Multivariable logistic regression analysis was utilized to develop the model. We integrated the radiomics signature, clinical T and N stage, and other independent clinicopathologic variables, and this was presented as a radiomics nomogram. The performance of the nomogram was assessed with calibration, discrimination, and clinical usefulness.</p><p><bold>Results:</bold> The radiomics signature was significantly associated with pathological LN stage in training and validation cohorts. Multivariable logistic analysis found the radiomics signature was an independent predictor of LN metastasis. The nomogram showed good discrimination and calibration.</p><p><bold>Conclusions:</bold> The newly developed radiomic signature was a powerful predictor of LN metastasis and the radiomics nomogram could facilitate the preoperative individualized prediction of LN status.</p>