Literature DB >> 23239041

Inter- and intra-rater reproducibility of quantitative dynamic contrast enhanced MRI using TWIST perfusion data in a uterine fibroid model.

Matthew S Davenport1, Tobias Heye, Brian M Dale, Jeffrey J Horvath, Steven R Breault, Sebastian Feuerlein, Mustafa R Bashir, Daniel T Boll, Elmar M Merkle.   

Abstract

PURPOSE: To determine the reproducibility of TWIST-derived (Time-Resolved Angiography with Interleaved Stochastic Trajectories) quantitative dynamic contrast enhanced (DCE) MRI in a uterine fibroid model.
MATERIALS AND METHODS: The institutional review board approved this retrospective study. Dynamic contrast-enhanced TWIST datasets from 15 randomly selected 1.5 Tesla pelvic MR studies were postprocessed. Five readers recorded kinetic parameters (K(trans) [volume transfer constant], ve [extracellular extravascular space volume], kep [flux rate constant], iAUC [initial area under the gadolinium-time curve]) of the largest uterine fibroid using three region-of-interest (ROI) selection methods. Measurements were randomized and repeated three times, and measures of reproducibility were calculated.
RESULTS: The intra-rater coefficients of variation (CVs, brackets indicate 95% confidence intervals) varied from 4.6% to 7.6% (K(trans) 7.6% [6.1%, 9.1%], kep 7.2% [5.9%, 8.5%], ve 4.6% [3.8%, 5.4%], and iAUC 7.2% [6.1%, 8.3%]). ve was the most reproducible (P < 0.05). Inter-rater reproducibility was significantly (P < 0.05) greater for the large ROI method (range of intraclass correlation coefficients [ICCs] = 0.80-0.98 versus 0.48-0.63 [user-defined ROI] versus 0.41-0.69 [targeted ROI]). The uterine fibroid accounted for the greatest fraction of variance for the large ROI method (range across kinetic parameters: 83-98% versus 56-69% [user-defined ROI] versus 47-74% [targeted ROI]). The reader accounted for the greatest fraction of variance for the user-defined ROI method (0.4-14.1% versus 0.1-3.0% [large ROI] versus <0.1-1.5% [targeted ROI]).
CONCLUSION: Changes in TWIST-derived DCE-MRI kinetic parameters of up to 9-15% may be attributable to measurement error. Large DCE-MRI regions of interest are the most reproducible across multiple readers.
Copyright © 2012 Wiley Periodicals, Inc.

Entities:  

Keywords:  DCE-MRI; perfusion; reproducibility

Mesh:

Substances:

Year:  2012        PMID: 23239041     DOI: 10.1002/jmri.23974

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  7 in total

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Review 2.  [Quantitative perfusion imaging in magnetic resonance imaging].

Authors:  F G Zöllner; T Gaa; F Zimmer; M M Ong; P Riffel; D Hausmann; S O Schoenberg; M Weis
Journal:  Radiologe       Date:  2016-02       Impact factor: 0.635

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Authors:  Jean-Philip Daniel Weber; Judith Eva Spiro; Matthias Scheffler; Jürgen Wolf; Lucia Nogova; Marc Tittgemeyer; David Maintz; Hendrik Laue; Thorsten Persigehl
Journal:  PLoS One       Date:  2022-03-08       Impact factor: 3.240

4.  Interreader Variability of Dynamic Contrast-enhanced MRI of Recurrent Glioblastoma: The Multicenter ACRIN 6677/RTOG 0625 Study.

Authors:  Daniel P Barboriak; Zheng Zhang; Pratikkumar Desai; Bradley S Snyder; Yair Safriel; Robert C McKinstry; Felix Bokstein; Gregory Sorensen; Mark R Gilbert; Jerrold L Boxerman
Journal:  Radiology       Date:  2018-11-27       Impact factor: 29.146

5.  Reproducibility of Dynamic Contrast-Enhanced MRI in Renal Cell Carcinoma: A Prospective Analysis on Intra- and Interobserver and Scan-Rescan Performance of Pharmacokinetic Parameters.

Authors:  Haiyi Wang; Zihua Su; Huiyi Ye; Xiao Xu; Zhipeng Sun; Lu Li; Feixue Duan; Yuanyuan Song; Tryphon Lambrou; Lin Ma
Journal:  Medicine (Baltimore)       Date:  2015-09       Impact factor: 1.817

6.  Dynamic Contrast-enhanced MR Imaging in Renal Cell Carcinoma: Reproducibility of Histogram Analysis on Pharmacokinetic Parameters.

Authors:  Hai-Yi Wang; Zi-Hua Su; Xiao Xu; Zhi-Peng Sun; Fei-Xue Duan; Yuan-Yuan Song; Lu Li; Ying-Wei Wang; Xin Ma; Ai-Tao Guo; Lin Ma; Hui-Yi Ye
Journal:  Sci Rep       Date:  2016-07-06       Impact factor: 4.379

7.  An open source software for analysis of dynamic contrast enhanced magnetic resonance images: UMMPerfusion revisited.

Authors:  Frank G Zöllner; Markus Daab; Steven P Sourbron; Lothar R Schad; Stefan O Schoenberg; Gerald Weisser
Journal:  BMC Med Imaging       Date:  2016-01-14       Impact factor: 1.930

  7 in total

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