Cargando…
Preoperative CT texture features predict prognosis after curative resection in pancreatic cancer
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 t...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6874598/ https://www.ncbi.nlm.nih.gov/pubmed/31757989 http://dx.doi.org/10.1038/s41598-019-53831-w |
_version_ | 1783472869310726144 |
---|---|
author | Kim, Hyung Sun Kim, Young Jae Kim, Kwang Gi Park, Joon Seong |
author_facet | Kim, Hyung Sun Kim, Young Jae Kim, Kwang Gi Park, Joon Seong |
author_sort | Kim, Hyung Sun |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6874598 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-68745982019-12-04 Preoperative CT texture features predict prognosis after curative resection in pancreatic cancer Kim, Hyung Sun Kim, Young Jae Kim, Kwang Gi Park, Joon Seong Sci Rep Article 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. Nature Publishing Group UK 2019-11-22 /pmc/articles/PMC6874598/ /pubmed/31757989 http://dx.doi.org/10.1038/s41598-019-53831-w Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Kim, Hyung Sun Kim, Young Jae Kim, Kwang Gi Park, Joon Seong Preoperative CT texture features predict prognosis after curative resection in pancreatic cancer |
title | Preoperative CT texture features predict prognosis after curative resection in pancreatic cancer |
title_full | Preoperative CT texture features predict prognosis after curative resection in pancreatic cancer |
title_fullStr | Preoperative CT texture features predict prognosis after curative resection in pancreatic cancer |
title_full_unstemmed | Preoperative CT texture features predict prognosis after curative resection in pancreatic cancer |
title_short | Preoperative CT texture features predict prognosis after curative resection in pancreatic cancer |
title_sort | preoperative ct texture features predict prognosis after curative resection in pancreatic cancer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6874598/ https://www.ncbi.nlm.nih.gov/pubmed/31757989 http://dx.doi.org/10.1038/s41598-019-53831-w |
work_keys_str_mv | AT kimhyungsun preoperativecttexturefeaturespredictprognosisaftercurativeresectioninpancreaticcancer AT kimyoungjae preoperativecttexturefeaturespredictprognosisaftercurativeresectioninpancreaticcancer AT kimkwanggi preoperativecttexturefeaturespredictprognosisaftercurativeresectioninpancreaticcancer AT parkjoonseong preoperativecttexturefeaturespredictprognosisaftercurativeresectioninpancreaticcancer |