Letter to the Editor
Copyright ©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Oncol. Jul 15, 2025; 17(7): 103282
Published online Jul 15, 2025. doi: 10.4251/wjgo.v17.i7.103282
Imaging-pathology correlation in pancreatic cancer: Methodological considerations and future directions
Arunkumar Krishnan
Arunkumar Krishnan, Department of Supportive Oncology, Atrium Health Levine Cancer, Charlotte, NC 28204, United States
Arunkumar Krishnan, Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC 27101, United States
Author contributions: Krishnan A conceptually developed the manuscript and conducted the assessment; Krishnan A was responsible for preparing the manuscript draft, which was subsequently reviewed and final approval.
Conflict-of-interest statement: The author declared no conflict of interest.
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: Arunkumar Krishnan, MD, Assistant Professor, Department of Supportive Oncology, Atrium Health Levine Cancer, 1021 Morehead Medical Drive, Suite 70100, Charlotte, NC 28204, United States. dr.arunkumar.krishnan@gmail.com
Received: November 14, 2024
Revised: February 27, 2025
Accepted: March 6, 2025
Published online: July 15, 2025
Processing time: 242 Days and 8 Hours
Core Tip

Core Tip: A study by Luo et al examined the relationship between different pathological types of pancreatic cancer (PC) and their corresponding imaging features. This present study showed an advancement in improving the diagnostic accuracy for PC. However, to further improve the robustness and applicability of the findings, it is important to adopt a multi-center, prospective research design. Such an approach would provide better generalizability and representation among diverse patient populations. Additionally, integrating advanced imaging techniques, including radiomics and artificial intelligence-driven analyses, could significantly mitigate inconsistencies among different observers, thereby elevating the precision of diagnostics. While the findings are promising, future research would greatly benefit from using multivariable analyses and strategies to address missing data, which would help control for potential confounding factors, thus reinforcing the credibility of imaging-pathology correlations. Moreover, establishing external validation cohorts is important for verifying the predictive capabilities of these findings across various clinical settings and diverse patient demographics.