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Preoperative CT texture features predict prognosis after curative resection in pancreatic cancer

Authors
 Hyung Sun Kim  ;  Young Jae Kim  ;  Kwang Gi Kim  ;  Joon Seong Park 
Citation
 SCIENTIFIC REPORTS, Vol.9(1) : 17389, 2019 
Journal Title
 SCIENTIFIC REPORTS 
Issue Date
2019
Abstract
Pancreatic cancer is a lethal disease, and resistance to chemotherapy is a critical factor influencing the postoperative prognosis. Tumour heterogeneity is an important indicator of chemoresistance. Therefore, we analysed tumour heterogeneity in preoperative computed tomography scans by performing texture analysis using the grey-level run-length matrix and analysed the correlation of survival with the value obtained in these analyses. We analysed 116 consecutive patients who underwent curative resection and had preoperative contrast-enhanced computed tomography data available for analysis. A region of interest was drawn on all slices with a visible tumour and normal pancreas on the arterial phase computed tomography scans; the correlation of pathological characteristics with grey-level run-length matrix features was analysed. We then performed Kaplan-Meier survival curve analysis among pancreatic cancer patients. The grey-level non-uniformity values in grey-level run-length matrix features for tumours were higher than those for normal pancreas. High grey-level non-uniformity values represent a non-uniform texture, i.e., heterogeneity. Grey-level run-length matrix features showed that recurrence-free survival was shorter in the group with high grey-level non-uniformity 135 values (p = 0.025). Our analyses of the correlation between pathological outcomes and grey-level run-length matrix features in pancreatic cancer patients showed that grey-level non-uniformity values were powerful prognostic indicators.
DOI
10.1038/s41598-019-53831-w
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Surgery (외과학교실) > 1. Journal Papers
Yonsei Authors
Kim, Hyung Sun(김형선) ORCID logo https://orcid.org/0000-0002-9002-3569
Park, Joon Seong(박준성) ORCID logo https://orcid.org/0000-0001-8048-9990
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/174605
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