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.

Highlights

  • Pancreatic cancer is a lethal disease, and resistance to chemotherapy is a critical factor influencing the postoperative prognosis

  • Chemoresistance is an important factor influencing the prognosis after curative resection, and tumour heterogeneity is an important indicator of the chemoresistance

  • Quantitative imaging techniques based on radiomics have recently gained prominence as potential methods to provide mineable data from imaging analysis using automatically extracted data-characterisation processes[11,12,13,14]

Read more

Summary

Introduction

Pancreatic cancer is a lethal disease, and resistance to chemotherapy is a critical factor influencing the postoperative prognosis. 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. Our analyses of the correlation between pathological outcomes and grey-level run-length matrix features in pancreatic cancer patients showed that greylevel non-uniformity values were powerful prognostic indicators. In this study, we analysed tumour heterogeneity using preoperative computed tomography (CT) by performing texture analysis with the grey-level run-length matrix (GLRLM) approach. We used these data to analyse the correlation between survival and the obtained tumour heterogeneity values in a large sample of curative-intent resected pancreatic cancers

Methods
Results
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.