MRI SCANNER VARIABILITY STUDIES USING A SEMIAUTOMATED ANALYSIS SYSTEM

Citation
Rj. Hyde et al., MRI SCANNER VARIABILITY STUDIES USING A SEMIAUTOMATED ANALYSIS SYSTEM, Magnetic resonance imaging, 12(7), 1994, pp. 1089-1097
Citations number
NO
Categorie Soggetti
Radiology,Nuclear Medicine & Medical Imaging
Journal title
ISSN journal
0730725X
Volume
12
Issue
7
Year of publication
1994
Pages
1089 - 1097
Database
ISI
SICI code
0730-725X(1994)12:7<1089:MSVSUA>2.0.ZU;2-N
Abstract
Due to the unique design of the Parallel Rod Test Object (PRoTO) and t he associated semi-automated analysis program, it was necessary to tes t it extensively for precision and accuracy, and preliminarily for uti lity, before its distribution for wider use in MRI system quality cont rol (QC). The test object and analysis program measured the desired qu antities reproducibly and they accurately measured predicted changes f rom intentionally adjusted imaging system parameters, yielding sensiti vity of the various test measures to deviation in the system operating parameters. From a single scan of the most recent revision of the tes t 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-nois e ratio (SNR) and distortion (including display scale) should be monit ored 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 meas ure was also used in normalizing the SNR by voxel volume. SNR, distort ion, 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 assessme nt of the long-term variability of the units tested. Long-term variabi lity may become among the most important measures for comparison of sy stem performance and maintenance. Results are still inconclusive on th e importance of tracking measures from sequences that are potentially most sensitive to small system misadjustments.