Literature DB >> 24602825

Fully-automated quality assurance in multi-center studies using MRI phantom measurements.

Mathias Davids1, Frank G Zöllner2, Michaela Ruttorf1, Frauke Nees3, Herta Flor3, Gunter Schumann4, Lothar R Schad1.   

Abstract

Phantom measurements allow for investigating the overall quality characteristics of an MRI scanner. Especially within multicenter studies, these characteristics ensure the comparability of the results across different sites, in addition to the performance stability of a single scanner over time. This comparability requires consistent phantoms, sequence protocols, and quality assurance criteria. Within the scope of this work, a software library was implemented for fully-automated determination of important quality characteristics (comprising signal-to-noise ratio, image uniformity, ghosting artifacts, chemical shift and spatial resolution and linearity) including methods for data preparation, automated pre- and postprocessing as well as visualization and interpretation. All methods were evaluated using both synthetic images with predefined distortions and a set of 44 real phantom measurements involving eight sites and three manufacturers. Using the synthetic phantom images, predefined levels of distortion that were incorporated artificially were correctly detected by the automated routines with no more than 2.6% of relative error. In addition, the methods were applied to real phantom measurements - all data sets could be evaluated automatically considering all quality parameters as long as the acquisition protocols are followed. Shortcomings of the processability only occurred in the ghosting artifacts (39/44 evaluable) and the spatial linearity (43/44 evaluable) analysis due to gross misalignments of the phantom during image acquisition. Based on evaluation results, the accuracy of the evaluation appears to be robust to misalignments, artifacts, and distortions affecting the images, allowing for objective fully-automated evaluation and interpretation of large data set numbers.
Copyright © 2014 Elsevier Inc. All rights reserved.

Keywords:  Automated quality assurance; MRI; Multicenter study; Phantom measurement

Mesh:

Year:  2014        PMID: 24602825     DOI: 10.1016/j.mri.2014.01.017

Source DB:  PubMed          Journal:  Magn Reson Imaging        ISSN: 0730-725X            Impact factor:   2.546


  15 in total

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Review 3.  [Big data and artificial intelligence for diagnostic decision support in atypical dementia].

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Review 4.  Standardization of Small Animal Imaging-Current Status and Future Prospects.

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Review 7.  [Quantitative perfusion imaging in magnetic resonance imaging].

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9.  A connectivity-based test-retest dataset of multi-modal magnetic resonance imaging in young healthy adults.

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