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Review | Open Access

Computed Tomography Scans in the Prediction of Margin‐Negative Resection in Pancreatic Cancer Following Neoadjuvant Treatment: An Updated Systematic Review and Meta‐Analysis

Ehsan Emami1 Dina Seyedi2Alireza Hassanpour3Faizan Bashir4 Elina Attaran5Maryam Mostofi6 ( )Mohammadjavad Abbaspour7Farzin Tahmasbi Arashlow8Pariya Zibaei9Alaleh Alizadeh10 Neda Tizro11Arash Saberian12Komeil Aghazadeh‐Habashi13Masoud Noroozi14 ( )Niloofar Deravi11 ( )
Student Research Committee, School of Pharmacy, Tehran University of Medical Science, Tehran, Iran
Musculoskeletal Imaging Research Center (MIRC), Tehran University of Medical Sciences, Tehran, Iran
Student Research Committee, School of Nursing and Midwifery, Mazandaran University of Medical Sciences, Sari, Iran
School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
Department of Medicine, Tabriz Medical Sciences Branch, Islamic Azad University, Tabriz, Iran
Faculty of Medicine, Ondokuz Mayis University, Samsun, Turkey
School of Medicine, Najafabad Branch, Islamic Azad University, Najafabad, Iran
Medical Students Research Centre, Iran University of Medical Sciences, Tehran, Iran
School of Medicine, Dezful University of Medical Science, Dezful, Iran
Faculty of Medicine, Mashhad Branch, Islamic Azad University, Mashhad, Iran
Student Research Committee, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Medical Imaging Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
Student Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran
Department of Biomedical Engineering, Faculty of Engineering, University of Isfahan, Isfahan, Iran

Ehsan Emami, Dina Seyedi and Alireza Hassanpour contributed equally to this work and share first authorship.

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Abstract

Pancreatic cancer is a highly lethal malignancy with a rising incidence. An early diagnosis of pancreatic cancer is challenging, and although computed tomography (CT) scans are the primary imaging modality for assessing resectability after neoadjuvant treatment, their accuracy in predicting margin‐negative (R0) resection remains a concern. This systematic review and meta‐analysis evaluated the role of CT scans in predicting R0 resection in patients with pancreatic cancer post‐neoadjuvant therapy. A search of PubMed, Scopus, and Google Scholar was conducted up to October 4, 2025, with adherence to the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses guidelines. Study selection, data extraction, and quality assessment were performed independently by two reviewers. Pooled sensitivity, specificity, and the area under the curve were assessed using the bivariate random‐effects model. Nine unique articles providing 10 study estimates met the inclusion criteria. A meta‐analysis showed significant heterogeneity for specificity (I2 = 87%) and sensitivity (I2 = 90%). Pooled sensitivity was 0.50 (95% confidence interval [CI]: 0.34–0.66) and pooled specificity was 0.75 (95% CI: 0.61–0.85). The area under the curve for overall diagnostic performance was 0.69 (95% CI: 0.65–0.73). The pooled diagnostic odds ratio was 3.00 (95% CI: 1.85–4.86). Deeks' funnel plot analysis showed no significant publication bias. Although CT scans play a crucial role in pancreatic cancer staging, their ability to predict R0 resection after neoadjuvant therapy is limited by low sensitivity and moderate specificity, as shown by the low area under the curve. These findings indicate the requirement for multimodal preoperative assessment strategies incorporating advanced imaging techniques and other diagnostic modalities to improve surgical planning and patients' outcomes.

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iRADIOLOGY
Pages 147-156

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Emami E, Seyedi D, Hassanpour A, et al. Computed Tomography Scans in the Prediction of Margin‐Negative Resection in Pancreatic Cancer Following Neoadjuvant Treatment: An Updated Systematic Review and Meta‐Analysis. iRADIOLOGY, 2026, 4(2): 147-156. https://doi.org/10.1002/ird3.70064

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Received: 13 May 2025
Revised: 22 December 2025
Accepted: 01 February 2026
Published: 12 April 2026
© 2026 The Author(s). Tsinghua University Press.

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.