Retrospective Study
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Radiol. Nov 28, 2023; 15(11): 304-314
Published online Nov 28, 2023. doi: 10.4329/wjr.v15.i11.304
Radiomics analysis with three-dimensional and two-dimensional segmentation to predict survival outcomes in pancreatic cancer
Mohammed Saleh, Mayur Virarkar, Hagar S Mahmoud, Vincenzo K Wong, Carlos Ignacio Gonzalez Baerga, Miti Parikh, Sherif B Elsherif, Priya R Bhosale
Mohammed Saleh, Hagar S Mahmoud, Vincenzo K Wong, Priya R Bhosale, Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, United States
Mayur Virarkar, Carlos Ignacio Gonzalez Baerga, Sherif B Elsherif, Department of Diagnostic Radiology, The University of Florida College of Medicine, Jacksonville, FL 32209, United States
Miti Parikh, Keck School of Medicine, University of South California, Los Angeles, CA 90033, United States
Author contributions: Saleh M, Virarkar M, Mahmoud HS, Wong VK, Gonzalez Baerga CI, Parikh M, Elsherif SB, and Bhosale PR have equally contributed to this paper with conception and design of the study, literature review and analysis, drafting and critical revision and editing, and final approval of the final version.
Institutional review board statement: The study was reviewed and approved by the University of Texas MD Anderson Cancer Center Institutional Review Board (approval No. 4 IRB00005015).
Informed consent statement: The informed consent was waived by the University of Texas MD Anderson Cancer Center Institutional Review Board.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: No additional data are available.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Carlos Ignacio Gonzalez Baerga, MD, Research Assistant, Department of Diagnostic Radiology, The University of Florida College of Medicine, 655 8th Street West, Jacksonville, FL 32209, United States. carlos.gonzalezbaerga@jax.ufl.edu
Received: August 28, 2023
Peer-review started: August 28, 2023
First decision: September 19, 2023
Revised: September 20, 2023
Accepted: October 23, 2023
Article in press: October 23, 2023
Published online: November 28, 2023
Processing time: 88 Days and 2.6 Hours
Core Tip

Core Tip: The use of radiomics to assess pancreatic cancer has been limited. This retrospective study evaluated the performance of 2-dimensional (2D) and 3D radiomic software in determining survival outcomes of pancreatic cancer patients. The mean tumor density was the only variable to reliably predict overall survival (OS) irrespective of the type of analysis. Mean tumor density may be able to differentiate survival and potentially may be help in treatment planning irrespective of the texture analysis software used. Higher skewness [hazard ratio (HR) = 3.067, P = 0.008] and higher kurtosis (HR = 1.176, P = 0.029) correlated with worse OS based on 2D analysis.