Have a personal or library account? Click to login
Original article. Perihilar cholangiocarcinoma: accuracy of 16-detector-row computed tomography in evaluating tumor extension and resectability Cover

Original article. Perihilar cholangiocarcinoma: accuracy of 16-detector-row computed tomography in evaluating tumor extension and resectability

Open Access
|Feb 2017

Abstract

Background: Management of perihilar cholangiocarcinoma is mainly by surgery. Computed tomography is the imaging choice by which to evaluate tumor extension and resectability. However, reports concerning the accuracy of computed tomography for this purpose differ.

Objective: To retrospectively assess the accuracy of 16-detector-row computed tomography in evaluating tumor extension and tumor resectability of perihilar cholangiocarcinoma.

Method: Sixty-two patients attending our hospital from January 2004 to June 2011were included in this study. Tumor extension and resectability were retrospectively reviewed. Pathological results, diagnostic laparoscopy, and surgical findings were used as references.

Result: The accuracy for predictability of resectability was 80.7%. The accuracy of 16-detector-row computed tomography in evaluating tumor extension was; 95.2% for prediction of ductal involvement, 85.7% for prediction of hepatic artery invasion, 79.1% for prediction of portal vein invasion, 67.3% for prediction of N1 nodal involvement and 90.9% for prediction of N2 nodal involvement.

Conclusion: Good accuracy was found using 16-detector-row computed tomography in overall evaluation of tumor resectability. For tumor extension, 16-detector-row computed tomography has good accuracy except for evaluating N1 nodes.

DOI: https://doi.org/10.5372/1905-7415.0704.204 | Journal eISSN: 1875-855X | Journal ISSN: 1905-7415
Language: English
Page range: 499 - 507
Published on: Feb 4, 2017
Published by: Chulalongkorn University
In partnership with: Paradigm Publishing Services
Publication frequency: 6 issues per year

© 2017 Tunyarat Wattanasatesiri, Boonchoo Sirichindakul, Naruemon Klaikaew, Bundit Chaopathomkul, published by Chulalongkorn University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.