Literature DB >> 33281035

Incidental pancreatic cystic lesions: comparison between CT with model-based algorithm and MRI.

D Ippolito1, C Maino2, A Pecorelli1, A De Vito1, L Riva1, C Talei Franzesi1, S Sironi3.   

Abstract

INTRODUCTION: The present study aims to compare low-kV CT reconstructed with MBIR technique with MRI in detecting high-risk stigmata and worrisome features in patients with pancreatic cystic lesions.
METHODS: We retrospective enrolled 75 patients who underwent low-kV CT with contrast media injection for general abdominal disorders and MRI with MRCP sequences. The reviewer, blinded to clinical and histopathological data, recorded the overall number of pancreatic cystic lesions, size, location, presence of calcifications, septa, or solid enhancing or non-enhancing components, main pancreatic duct (MPD) communication, and MPD dilatation. Mean differences with 95% limits of agreement, ICC, and κ statistics were used to compare CT and MRI.
RESULTS: More pancreatic cystic lesions were detected with MRI than with CT, however, the ICC value of 0.81 suggested a good agreement. According to the evaluated target lesion, a very good agreement (ICC = 0.98) was found regarding the diameter (21.4 mm CT vs 21.8 mm MRI), the location (κ = 0.90), the detection of MPD dilatation (κ = 1), the presence of septa (κ = 0.86) and the MPD communication (κ = 0.87). A moderate agreement on the assessment of enhanced components was noted (κ = 0.44), while there was only a fair agreement about the presence of calcifications (κ = 0.87).
CONCLUSION: MDCT can be considered almost equivalent to MRI with MRCP in the evaluation of worrisome features and high-risk stigmata, offering detailed morphologic features helpful for their characterization. IMPLICATIONS FOR PRACTICE: Even if MRI is considered the reference standard in pancreatic cystic lesions characterization, CT can be considered a useful tool as a first-line imaging technique to identify worrisome features and high-risk stigmata.
Copyright © 2020 The College of Radiographers. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Magnetic resonance cholangiopancreatography; Multidetector computed tomography; Pancreatic intraductal neoplasms; Pancreatic neoplasms

Year:  2020        PMID: 33281035     DOI: 10.1016/j.radi.2020.11.016

Source DB:  PubMed          Journal:  Radiography (Lond)        ISSN: 1078-8174


  1 in total

1.  A deep learning algorithm to improve readers' interpretation and speed of pancreatic cystic lesions on dual-phase enhanced CT.

Authors:  Xiheng Wang; Zhaoyong Sun; Huadan Xue; Taiping Qu; Sihang Cheng; Juan Li; Yatong Li; Li Mao; Xiuli Li; Liang Zhu; Xiao Li; Longjing Zhang; Zhengyu Jin; Yizhou Yu
Journal:  Abdom Radiol (NY)       Date:  2022-03-27
  1 in total

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