Literature DB >> 17183129

Reproducibility of reference tissue quantification of dynamic contrast-enhanced data: comparison with a fixed vascular input function.

S Walker-Samuel1, C C Parker, M O Leach, D J Collins.   

Abstract

Reference tissues are currently used to analyse dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data. The assessment of tumour response to treatment with anti-cancer drugs is a particularly important application of this type of analysis and requires a measure of reproducibility to define a level above which a significant change due to therapy can be inferred. This study compares the reproducibility of such quantification strategies with that found using a published, group-averaged uptake curve. It is shown that reference tissue quantification gives poorer reproducibility for most parameters than that found using a group-averaged plasma curve (a change in K(trans) of greater than 41.8% and 16.4% would be considered significant in the two approaches, respectively), but successfully incorporates some of the variability observed in plasma kinetics between visits and provides vascular input functions that, across the group, are comparable with the group-averaged curve. This study therefore provides an indirect validation of the methodology.

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Year:  2006        PMID: 17183129     DOI: 10.1088/0031-9155/52/1/006

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  17 in total

Review 1.  Diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) for monitoring anticancer therapy.

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2.  Multiparametric MRI biomarkers for measuring vascular disrupting effect on cancer.

Authors:  Huaijun Wang; Guy Marchal; Yicheng Ni
Journal:  World J Radiol       Date:  2011-01-28

3.  Incorporating the effects of transcytolemmal water exchange in a reference region model for DCE-MRI analysis: theory, simulations, and experimental results.

Authors:  Thomas E Yankeelov; Jeffrey J Luci; Laura M DeBusk; P Charles Lin; John C Gore
Journal:  Magn Reson Med       Date:  2008-02       Impact factor: 4.668

4.  A clinically feasible method to estimate pharmacokinetic parameters in breast cancer.

Authors:  Jun Li; Yanming Yu; Yibao Zhang; Shanglian Bao; Chunxue Wu; Xiaoying Wang; Jie Li; Xiaopeng Zhang; Jiani Hu
Journal:  Med Phys       Date:  2009-08       Impact factor: 4.071

5.  A model-constrained Monte Carlo method for blind arterial input function estimation in dynamic contrast-enhanced MRI: II. In vivo results.

Authors:  Matthias C Schabel; Edward V R DiBella; Randy L Jensen; Karen L Salzman
Journal:  Phys Med Biol       Date:  2010-08-03       Impact factor: 3.609

6.  The impact of reliable prebolus T 1 measurements or a fixed T 1 value in the assessment of glioma patients with dynamic contrast enhancing MRI.

Authors:  Anna Tietze; Kim Mouridsen; Irene Klærke Mikkelsen
Journal:  Neuroradiology       Date:  2015-03-06       Impact factor: 2.804

7.  Vascular characterisation of triple negative breast carcinomas using dynamic MRI.

Authors:  Sonia P Li; Anwar R Padhani; N Jane Taylor; Mark J Beresford; Mei-Lin W Ah-See; J James Stirling; James A d'Arcy; David J Collins; Andreas Makris
Journal:  Eur Radiol       Date:  2011-01-22       Impact factor: 5.315

8.  Validation of dynamic contrast-enhanced magnetic resonance imaging-derived vascular permeability measurements using quantitative autoradiography in the RG2 rat brain tumor model.

Authors:  Moira C Ferrier; Hemant Sarin; Steve H Fung; Bawarjan Schatlo; Ryszard M Pluta; Sandeep N Gupta; Peter L Choyke; Edward H Oldfield; David Thomasson; John A Butman
Journal:  Neoplasia       Date:  2007-07       Impact factor: 5.715

9.  Reproducibility assessment of a multiple reference tissue method for quantitative dynamic contrast enhanced-MRI analysis.

Authors:  Cheng Yang; Gregory S Karczmar; Milica Medved; Aytekin Oto; Marta Zamora; Walter M Stadler
Journal:  Magn Reson Med       Date:  2009-04       Impact factor: 4.668

10.  Feasibility of using limited-population-based arterial input function for pharmacokinetic modeling of osteosarcoma dynamic contrast-enhanced MRI data.

Authors:  Ya Wang; Wei Huang; David M Panicek; Lawrence H Schwartz; Jason A Koutcher
Journal:  Magn Reson Med       Date:  2008-05       Impact factor: 4.668

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