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| Texture analysis of CT images used to assess pathological grades of pancreatic neuroendocrine neoplasms |
| YU Hao-peng, LI Mou, ZHANG Lin, YANG Cheng-min, ZHANG Yong-chang, SONG Bin |
| Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China |
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Abstract Objective: To evaluate the accuracy of the texture analysis to determinate the pathological grades of pancreatic neuroendocrine neoplasms(PNEN). Methods: 109 cases of pancreatic neuroendocrine neoplasms, confirmed by surgery or pathological biopsy, were retrospectively enrolled in our study. Both arterial phase and portal vein phase CT images of including patients were manual sketch the region of interest(ROI) by ITK Snap software. A.K. software was used for texture extraction, and R software with The least absolute shrinkage and selection operator(LASSO) was used for calculation. Results: In aterial phase, 5 texture features were selected, including maximum 3D diameter, kurtosis, GLCMEntropy_AllDirection_offset7_SD, quantile0.025 and Surface volume ratio, with AUROC of 0.715, 0.529, 0.724, 0.672 and 0.698, respectively. In portal vein phase, 2 texture features were selected including maximum 3D diameter and surface volume ratio, with AUROC of 0.722 and 0.703, respectively. Conclusions: Texture analysis of CT images can be used to evaluate the pathological classification of PNEN.
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Received: 11 August 2018
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