1. CT radiomics nomogram for the preoperative prediction of lymph node metastasis in gastric cancer
- Author
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Huadan Xue, Zhengyu Jin, Jian-Chun Yu, Yafei Qi, Wei Liu, Yue Wang, Jing-Juan Liu, Yang Yu, and Jing Lei
- Subjects
Adult ,Male ,medicine.medical_specialty ,030218 nuclear medicine & medical imaging ,Metastasis ,Cohort Studies ,03 medical and health sciences ,0302 clinical medicine ,Predictive Value of Tests ,Stomach Neoplasms ,Preoperative Care ,medicine ,Humans ,Radiology, Nuclear Medicine and imaging ,Lymph node ,Aged ,Neoplasm Staging ,Retrospective Studies ,Receiver operating characteristic ,business.industry ,Area under the curve ,Cancer ,Retrospective cohort study ,General Medicine ,Middle Aged ,Nomogram ,medicine.disease ,Nomograms ,medicine.anatomical_structure ,ROC Curve ,Lymphatic Metastasis ,030220 oncology & carcinogenesis ,Cohort ,Female ,Radiology ,Tomography, X-Ray Computed ,business ,Algorithms - Abstract
To investigate the role of computed tomography (CT) radiomics for the preoperative prediction of lymph node (LN) metastasis in gastric cancer. This retrospective study included 247 consecutive patients (training cohort, 197 patients; test cohort, 50 patients) with surgically proven gastric cancer. Dedicated radiomics prototype software was used to segment lesions on preoperative arterial phase (AP) CT images and extract features. A radiomics model was constructed to predict the LN metastasis by using a random forest (RF) algorithm. Finally, a nomogram was built incorporating the radiomics scores and selected clinical predictors. Receiver operating characteristic (ROC) curves were used to validate the capability of the radiomics model and nomogram on both the training and test cohorts. The radiomics model showed a favorable discriminatory ability in the training cohort with an area under the curve (AUC) of 0.844 (95% CI, 0.759 to 0.909), which was confirmed in the test cohort with an AUC of 0.837 (95% CI, 0.705 to 0.926). The nomogram consisted of radiomics scores and the CT-reported LN status showed excellent discrimination in the training and test cohorts with AUCs of 0.886 (95% CI, 0.808 to 0.941) and 0.881 (95% CI, 0.759 to 0.956), respectively. The CT-based radiomics nomogram holds promise for use as a noninvasive tool in the individual prediction of LN metastasis in gastric cancer. • CT radiomics showed a favorable performance for the prediction of LN metastasis in gastric cancer. • Radiomics model outperformed the routine CT in predicting LN metastasis in gastric cancer. • The radiomics nomogram holds potential in the individualized prediction of LN metastasis in gastric cancer.
- Published
- 2019