Radiomics nomogram for the preoperative prediction of lymph node metastasis in pancreatic ductal adenocarcinoma

Cancer Imaging

Suizhi Gao¹  Shiwei Guo¹  Gang Jin¹  Hui Jiang²  Jianming Zheng²  Jing Li³  Xu Fang³  Li Wang³  Chao Ma³  Kai Cao³  Jianping Lu³  Yun Bian³  Chengwei Shao³ 

[1] Department of Pancreatic Surgery, Changhai Hospital, The Naval Medical University, Shanghai, China;Department of Pathology, Changhai Hospital, The Naval Medical University, Shanghai, China;Department of Radiology, Changhai Hospital, The Naval Medical University, 168 Changhai Road, 200433, Shanghai, China;

关键词: Pancreatic neoplasm;    Carcinoma;    Pancreatic ductal adenocarcinoma;    Lymph nodes;    Computed tomography;    Radiomics;    Nomograms;   

DOI  :  10.1186/s40644-021-00443-1

来源: Springer

【 摘 要 】

PurposeTo develop and validate a radiomics nomogram for the preoperative prediction of lymph node (LN) metastasis in pancreatic ductal adenocarcinoma (PDAC).Materials and methodsIn this retrospective study, 225 patients with surgically resected, pathologically confirmed PDAC underwent multislice computed tomography (MSCT) between January 2014 and January 2017. Radiomics features were extracted from arterial CT scans. The least absolute shrinkage and selection operator method was used to select the features. Multivariable logistic regression analysis was used to develop the predictive model, and a radiomics nomogram was built and internally validated in 45 consecutive patients with PDAC between February 2017 and December 2017. The performance of the nomogram was assessed in the training and validation cohort. Finally, the clinical usefulness of the nomogram was estimated using decision curve analysis (DCA).ResultsThe radiomics signature, which consisted of 13 selected features of the arterial phase, was significantly associated with LN status (p < 0.05) in both the training and validation cohorts. The multivariable logistic regression model included the radiomics signature and CT-reported LN status. The individualized prediction nomogram showed good discrimination in the training cohort [area under the curve (AUC), 0.75; 95% confidence interval (CI), 0.68–0.82] and in the validation cohort (AUC, 0.81; 95% CI, 0.69–0.94) and good calibration. DCA demonstrated that the radiomics nomogram was clinically useful.ConclusionsThe presented radiomics nomogram that incorporates the radiomics signature and CT-reported LN status is a noninvasive, preoperative prediction tool with favorable predictive accuracy for LN metastasis in patients with PDAC.

【 授权许可】

CC BY