Contrast-enhanced CT radiomics for predicting lymph node metastasis in pancreatic ductal adenocarcinoma: A pilot study

Ke Li, Qiandong Yao, Jingjing Xiao, Meng Li, Jiali Yang, Wenjing Hou, Mingshan Du, Kang Chen, Yuan Qu, Lian Li, Jing Li, Xianqi Wang, Haoran Luo, Jia Yang, Zhuoli Zhang, Wei Chen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Background: We developed a computational model integrating clinical data and imaging features extracted from contrast-enhanced computed tomography (CECT) images, to predict lymph node (LN) metastasis in patients with pancreatic ductal adenocarcinoma (PDAC). Methods: This retrospective study included 159 patients with PDAC (118 in the primary cohort and 41 in the validation cohort) who underwent preoperative contrast-enhanced computed tomography examination between 2012 and 2015. All patients underwent surgery and lymph node status was determined. A total of 2041 radiomics features were extracted from venous phase images in the primary cohort, and optimal features were extracted to construct a radiomics signature. A combined prediction model was built by incorporating the radiomics signature and clinical characteristics selected by using multivariable logistic regression. Clinical prediction models were generated and used to evaluate both cohorts. Results: Fifteen features were selected for constructing the radiomics signature based on the primary cohort. The combined prediction model for identifying preoperative lymph node metastasis reached a better discrimination power than the clinical prediction model, with an area under the curve of 0.944 vs. 0.666 in the primary cohort, and 0.912 vs. 0.713 in the validation cohort. Conclusions: This pilot study demonstrated that a noninvasive radiomics signature extracted from contrast-enhanced computed tomography imaging can be conveniently used for preoperative prediction of lymph node metastasis in patients with PDAC.

Original languageEnglish (US)
Article number12
JournalCancer Imaging
Volume20
Issue number1
DOIs
StatePublished - Jan 30 2020

Keywords

  • CT
  • Lymph node metastasis
  • Pancreatic ductal adenocarcinoma
  • Radiomics

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Oncology
  • Radiology Nuclear Medicine and imaging

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