Skip to main navigation Skip to search Skip to main content

Preoperative risk prediction for intraductal papillary mucinous neoplasms by quantitative CT image analysis

  • Marc A. Attiyeh
  • , Jayasree Chakraborty
  • , Lior Gazit
  • , Liana Langdon-Embry
  • , Mithat Gonen
  • , Vinod P. Balachandran
  • , Michael I. D'Angelica
  • , Ronald P. DeMatteo
  • , William R. Jarnagin
  • , T. Peter Kingham
  • , Peter J. Allen
  • , Richard K. Do
  • , Amber L. Simpson

Research output: Contribution to journal › Article › peer-review

Abstract

Background: Intraductal papillary mucinous neoplasms (IPMNs) are radiographically identifiable potential precursor lesions of pancreatic adenocarcinoma. While resection is recommended when main duct dilation is present, management of branch duct IPMN (BD-IPMN) remains controversial. This study sought to evaluate whether preoperative quantitative imaging features of BD-IPMNs could distinguish low-risk disease (low- and intermediate-grade dysplasia) from high-risk disease (high-grade dysplasia and invasive carcinoma). Methods: Patients who underwent resection between 2005 and 2015 with pathologically proven BD-IPMN and a preoperative CT scan were included in the study. Quantitative image features were extracted using texture analysis and a novel quantitative mural nodularity feature developed for the study. Significant features on univariate analysis were combined with clinical variables to build a multivariate prediction model. Results: Within the study group of 103 patients, 76 (74%) had low-risk disease and 27 (26%) had high-risk disease. Quantitative imaging features were prognostic of low-vs. high-risk disease. The model based only on clinical variables achieved an AUC of 0.67 and 0.79 with the addition of quantitative imaging features. Conclusion: Quantitative image analysis of BD-IPMNs is a novel method that may enable risk stratification. External validation may provide a reliable non-invasive prognostic tool for clinicians.

Original languageEnglish
Pages (from-to)212-218
Number of pages7
JournalHPB
Volume21
Issue number2
DOIs
StatePublished - Feb 2019
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2018 International Hepato-Pancreato-Biliary Association Inc.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

ASJC Scopus subject areas

  • Hepatology
  • Gastroenterology

Fingerprint

Dive into the research topics of 'Preoperative risk prediction for intraductal papillary mucinous neoplasms by quantitative CT image analysis'. Together they form a unique fingerprint.

Cite this