Literature DB >> 7997096

MRI scanner variability studies using a semi-automated analysis system.

R J Hyde1, J H Ellis, E A Gardner, Y Zhang, P L Carson.   

Abstract

Due to the unique design of the Parallel Rod Test Object (PRoTO) and the associated semi-automated analysis program, it was necessary to test it extensively for precision and accuracy, and preliminarily for utility, before its distribution for wider use in MRI system quality control (QC). The test object and analysis program measured the desired quantities reproducibly and they accurately measured predicted changes from intentionally adjusted imaging system parameters, yielding sensitivity of the various test measures to deviation in the system operating parameters. From a single scan of the most recent revision of the test object, multiple quantitative quality control measures were obtained throughout the scanning volume on two MR imaging systems over periods of six and twelve months, respectively. From these and earlier trials, an initial indication was obtained of which performance measures are worth monitoring for QC. This experience suggests that signal-to-noise ratio (SNR) and distortion (including display scale) should be monitored but not necessarily the resolution. The latter was only found to alter at the same time or later than other parameters such as SNR had changed. Slice thickness was found to vary on some units and this measure was also used in normalizing the SNR by voxel volume. SNR, distortion, and resolution measurements using field-echo sequences were less stable than those using spin-echo sequences. Use of this QC program to test a wide variety of image quality measures allowed timely assessment of the long-term variability of the units tested. Long-term variability may become among the most important measures for comparison of system performance and maintenance.(ABSTRACT TRUNCATED AT 250 WORDS)

Mesh:

Year:  1994        PMID: 7997096     DOI: 10.1016/0730-725x(94)91241-n

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


  4 in total

1.  Quality assurance of clinical MRI scanners using ACR MRI phantom: preliminary results.

Authors:  Chien-Chuan Chen; Yung-Liang Wan; Yau-Yau Wai; Ho-Ling Liu
Journal:  J Digit Imaging       Date:  2004-12       Impact factor: 4.056

2.  The Osteoarthritis Initiative (OAI) magnetic resonance imaging quality assurance update.

Authors:  E Schneider; M Nessaiver
Journal:  Osteoarthritis Cartilage       Date:  2012-10-23       Impact factor: 6.576

3.  The osteoarthritis initiative (OAI) magnetic resonance imaging quality assurance methods and results.

Authors:  E Schneider; M NessAiver; D White; D Purdy; L Martin; L Fanella; D Davis; M Vignone; G Wu; R Gullapalli
Journal:  Osteoarthritis Cartilage       Date:  2008-04-18       Impact factor: 6.576

4.  A Deep Learning-based Model for Detecting Abnormalities on Brain MR Images for Triaging: Preliminary Results from a Multisite Experience.

Authors:  Romane Gauriau; Bernardo C Bizzo; Felipe C Kitamura; Osvaldo Landi Junior; Suely F Ferraciolli; Fabiola B C Macruz; Tiago A Sanchez; Marcio R T Garcia; Leonardo M Vedolin; Romeu C Domingues; Emerson L Gasparetto; Katherine P Andriole
Journal:  Radiol Artif Intell       Date:  2021-04-21
  4 in total

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