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Dynamic Contrast Enhanced Magnetic Resonance Imaging of an Orthotopic Pancreatic Cancer Mouse Model
Published on: April 18, 2015
Identifying Outcomes of Patients With Advanced Pancreatic Adenocarcinoma and RECIST Stable Disease Using Radiomics
Qiuxia Yang1, Yize Mao2, Hui Xie1
1Department of Medical Imaging Center, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Purpose:
Few studies have explored the biomarkers for predicting the heterogeneous outcomes of patients with advanced pancreatic adenocarcinoma showing stable disease (SD) on the initial postchemotherapy computed tomography. We aimed to devise a radiomics signature (RS) to predict these outcomes for further risk stratification.
Materials And Methods:
Patients with advanced pancreatic adenocarcinoma and SD after chemotherapy were included. Pancreatic lesions on initial postchemotherapy computed tomography images were evaluated by radiomics analysis for predicting early death (≤ 1 year). RS was then internally and externally tested. The progression-free survival and objective response rate were compared between the low-risk and high-risk group of patients classified following RS.
Results:
Approximately 62.7% of patients receiving chemotherapy showed SD at first response evaluation in the primary cohort, which were 59.6% and 57.9% in internal and external testing cohorts, respectively. The RS predicted 1-year overall survival well, with areas under the receiver operating characteristic curve of 0.91 in the training cohort, 0.90 in the validation cohort, 0.84 in the internal testing cohort, and 0.87 in the external testing cohort. The high-risk group had a shorter median progression-free survival (7.3 months v 9.0 months, P = .016, in the training cohort; 5.9 months v 9.2 months, P = .026, in the internal testing cohort) and a lower objective response rate (2.2% v 24.0% in the training cohort) than the low-risk group. In addition, RS was not related to the clinical characteristics and chemotherapy regimens.
Conclusion:
RS independently predicts the outcomes of patients with SD after chemotherapy well and can help to improve treatment decisions by identifying patients for whom current treatment may not be suitable.
