Differentiating pancreatic from periampullary non-pancreatic cancer - a nomogram-based prediction model utilizing CT imaging

Q: What is the main goal of the nomogram-based model?

To differentiate pancreatic cancer from periampullary non-pancreatic cancers using CT imaging features through a predictive nomogram.

Q: How was the model developed and validated?

A retrospective cohort of 171 periampullary carcinoma patients was analyzed with multivariable logistic regression to select significant features, then the nomogram was internally validated using the same factors.

Q: Which CT imaging features were identified as independent risk factors?

Independent factors included DPDP (distance from distal end of dilated pancreatic duct to the papilla medial wall), DBDP (distance from distal end of dilated bile duct to the papilla medial wall), papillary enlargement, and visibility of pancreatic and/or bile ducts between the tumor and the papilla (VPBD).

Q: Why is preoperative differentiation clinically important?

Because it directly affects treatment strategies and has significant clinical consequences, including appropriate use or avoidance of neoadjuvant chemoradiotherapy depending on cancer type.

Sep 23, 2026

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A retrospective study develops and internally validates a CT-imaging–based nomogram to differentiate pancreatic cancer from periampullary non-pancreatic cancers. The analysis includes 171 periampullary carcinoma patients, comparing groups with pancreatic cancer versus non-pancreatic cancer. Multivariable logistic regression identifies four independent CT-related features and constructs a predictive model. Discriminative performance is evaluated with ROC-derived AUCs in both development and validation cohorts, supporting reliable clinical decision-making.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages12

Reading Time30 min

AccessFree to download

Abstract

Introduction

Background and clinical importance

Diagnostic workflow and limitations

Methods

Study design and population

Variables and statistical analysis

Results

Independent CT risk factors

Nomogram construction and performance

Conclusions

Zhang et al. Cancer Imaging (2025) 25:114 [https://doi.org/10.1186/s40644-025-00917-6](https://doi.org/10.1186/s40644-025-00917-6) Cancer Imaging RESEARCH Open Access Differentiating pancreatic from periampullary non-pancreatic cancer: a nomogram-based prediction model utilizing CT imaging Xiaohuan Zhang 1†, Junqing Wang2†, Wenjuan Wu2, Zhuiyang Zhang2, Fangming Chen2 and Lei Zhang 1,2* Abstract Background To develop a predictive nomogram for differentiating pancreatic cancer from periampullary nonpancreatic cancers based on computed tomography (CT) imaging features. Methods This retrospective study included 171 patients diagnosed with periampullary carcinoma (90 pancreatic cancer and 81 non-pancreatic cancer) . Variables assessed included CT imaging features along with relevant clinical data. Statistically significant variables were identified through multivariable logistic regression analysis, and a predictive nomogram was developed and internally validated based on these factors. Results Multivariable analysis identified the following independent risk factors: the distance from the distal end of the dilated pancreatic duct to the medial wall of the papilla (DPDP) (odds ratio [OR] 8. 76, P < 0. 05), the distance from the distal end of the dilated bile duct to the medial wall of the papilla (DBDP) (OR 31 . 83, P < 0. 05), papillary enlargement (OR 0 . 03, P < 0. 05), and visibility of pancreatic and/or bile ducts between the tumor and the papilla (VPBD) (OR 3 . 97, P < 0. 05) . A nomogram was constructed based on these four significant features. In both the development and validation cohorts, the nomogram demonstrated robust predictive performance, with areas under the receiver operating characteristic curve (AUCs) of 0.84 (95% CI, 0 .77–0. 91) and 0.81 (95% CI, 0 .67–0. 96), respectively. Conclusions This study underscores the value of CT imaging features in distinguishing pancreatic cancer from periampullary non-pancreatic cancers. The identification of key imaging markers with significant diagnostic value facilitated the development and validation of a nomogram that integrates these features, providing a more reliable tool for clinical decision-making. Keywords Pancreatic cancer, Periampullary cancer, Computed tomography, Risk factors, Nomogram †Xiaohuan Zhang and Junqing Wang are coefirst authors. *Correspondence: Lei Zhang [leon3183@163.com](leon3183@163.com) 1Department of Radiology, The Affiliated Wuxi No.2 People’s Hospital of Nanjing Medical University, Wuxi 214002, China 2Department of Radiology, Wuxi Second People’s Hospital, Jiangnan University Medical Center, Wuxi, China © The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, 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 licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit [http://creati](http://creati)[vecommons.org/l](vecommons.org/l)icenses/by-nc-nd/4.0/. Zhang et al. Cancer Imaging (2025) 25:114 Introduction Periampullary carcinomas encompass four main types: ampullary cancer, distal cholangiocarcinoma, pancreatic head cancer, and duodenal cancer [1]. Pancreatoduodenectomy is typically performed for bot

FAQs

What is the main goal of the nomogram-based model?

To differentiate pancreatic cancer from periampullary non-pancreatic cancers using CT imaging features through a predictive nomogram.

How was the model developed and validated?

A retrospective cohort of 171 periampullary carcinoma patients was analyzed with multivariable logistic regression to select significant features, then the nomogram was internally validated using the same factors.

Which CT imaging features were identified as independent risk factors?

Independent factors included DPDP (distance from distal end of dilated pancreatic duct to the papilla medial wall), DBDP (distance from distal end of dilated bile duct to the papilla medial wall), papillary enlargement, and visibility of pancreatic and/or bile ducts between the tumor and the papilla (VPBD).

Why is preoperative differentiation clinically important?

Because it directly affects treatment strategies and has significant clinical consequences, including appropriate use or avoidance of neoadjuvant chemoradiotherapy depending on cancer type.

Sep 23, 2026

Uploaded by Aldword