Literature DB >> 29339222

Measurement variability of liver metastases from neuroendocrine tumors on different magnetic resonance imaging sequences.

T Lestra1, L Kanagaratnam2, S Mulé3, A Janvier3, H Brixi4, G Cadiot4, A Dohan5, C Hoeffel6.   

Abstract

PURPOSE: To assess dimension measurement variability of liver metastases from neuroendocrine tumors (LMNET) on different magnetic resonance imaging (MRI) sequences.
MATERIAL AND METHODS: In this institutional review board-approved retrospective study from January 2011 to December 2012, all liver MRI examinations performed at our department in patients with at least one measurable LMNET according to response evaluation criteria in solid tumors (RECIST1.1) were included. Up to two lesions were selected on T2-weighted MR images. Three reviewers independently measured long axes of 135 hepatic metastases in 30 patients (16 men, 14 women, mean age 61±11.4 (SD) years; range 28-78 years), during two separate reading sessions, on T2-weighted, diffusion-weighted MRI (DWI) (b; 50, 400, 800 s/mm2) and arterial, portal and late phases after intravenous administration of a gadolinium chelate. Intraclass-correlation coefficients and Bland-Altman plots were used to assess intra-and interobserver variability.
RESULTS: Intra- and interobserver agreements ranged between 0.87-0.98, and 0.88-0.97, respectively. Intersequence agreements ranged between 0.92 [95%CI: 0.82-0.98] and 0.98 [95%CI: 0.93-0.99]. 95% limits of agreement for measurements were -10.2%,+8.9% for DWI (b=50s/mm2) versus -21.9%,+24.2% and -15.8,+17.2% for arterial and portal phases, respectively.
CONCLUSION: An increase<9% in measurement and a decrease of -10% on DWI should not be considered as true changes, with 95% confidence, versus 24% and -22% on arterial and 17%, -16% on portal phases, respectively. DWI might thus be the most reliable MR sequence for monitoring size variations of LMNETs.
Copyright © 2017 Editions françaises de radiologie. Published by Elsevier Masson SAS. All rights reserved.

Entities:  

Keywords:  Interobserver variability; Liver metastasis; Magnetic resonance imaging (MRI); Neuroendocrine tumors (NET); Response evaluation criteria in solid tumors (RECIST)

Mesh:

Substances:

Year:  2018        PMID: 29339222     DOI: 10.1016/j.diii.2017.12.009

Source DB:  PubMed          Journal:  Diagn Interv Imaging        ISSN: 2211-5684            Impact factor:   4.026


  5 in total

1.  Multi-contrast four-dimensional magnetic resonance imaging (MC-4D-MRI): Development and initial evaluation in liver tumor patients.

Authors:  Lei Zhang; Fang-Fang Yin; Tian Li; Xinzhi Teng; Haonan Xiao; Wendy Harris; Lei Ren; Feng-Ming Spring Kong; Hong Ge; Ronghu Mao; Jing Cai
Journal:  Med Phys       Date:  2021-11-18       Impact factor: 4.506

2.  Automatized Hepatic Tumor Volume Analysis of Neuroendocrine Liver Metastases by Gd-EOB MRI-A Deep-Learning Model to Support Multidisciplinary Cancer Conference Decision-Making.

Authors:  Uli Fehrenbach; Siyi Xin; Alexander Hartenstein; Timo Alexander Auer; Franziska Dräger; Konrad Froböse; Henning Jann; Martina Mogl; Holger Amthauer; Dominik Geisel; Timm Denecke; Bertram Wiedenmann; Tobias Penzkofer
Journal:  Cancers (Basel)       Date:  2021-05-31       Impact factor: 6.639

Review 3.  Surgical Management of Neuroendocrine Tumours of the Pancreas.

Authors:  Regis Souche; Christian Hobeika; Elisabeth Hain; Sebastien Gaujoux
Journal:  J Clin Med       Date:  2020-09-16       Impact factor: 4.241

Review 4.  What Are the Place and Modalities of Surgical Management for Pancreatic Neuroendocrine Neoplasms? A Narrative Review.

Authors:  Samuel Frey; Eric Mirallié; Maëlle Le Bras; Nicolas Regenet
Journal:  Cancers (Basel)       Date:  2021-11-26       Impact factor: 6.639

5.  Evaluation of Multisource Adaptive MRI Fusion for Gross Tumor Volume Delineation of Hepatocellular Carcinoma.

Authors:  Andy Lai-Yin Cheung; Lei Zhang; Chenyang Liu; Tian Li; Anson Ho-Yin Cheung; Chun Leung; Angus Kwong-Chuen Leung; Sai-Kit Lam; Victor Ho-Fun Lee; Jing Cai
Journal:  Front Oncol       Date:  2022-02-25       Impact factor: 6.244

  5 in total

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