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J Magn Reson Imaging ; 43(1): 213-9, 2016 Jan.
Article in English | MEDLINE | ID: mdl-26013043

ABSTRACT

PURPOSE: To propose a magnetic resonance imaging (MRI) quality assurance procedure that can be used for multicenter comparison of different MR scanners for quantitative diffusion-weighted imaging (DWI). MATERIALS AND METHODS: Twenty-six centers (35 MR scanners with field strengths: 1T, 1.5T, and 3T) were enrolled in the study. Two different DWI acquisition series (b-value ranges 0-1000 and 0-3000 s/mm(2) , respectively) were performed for each MR scanner. All DWI acquisitions were performed by using a cylindrical doped water phantom. Mean apparent diffusion coefficient (ADC) values as well as ADC values along each of the three main orthogonal directions of the diffusion gradients (x, y, and z) were calculated. Short-term repeatability of ADC measurement was evaluated for 26 MR scanners. RESULTS: A good agreement was found between the nominal and measured mean ADC over all the centers. More than 80% of mean ADC measurements were within 5% from the nominal value, and the highest deviation and overall standard deviation were 9.3% and 3.5%, respectively. Short-term repeatability of ADC measurement was found <2.5% for all MR scanners. CONCLUSION: A specific and widely accepted protocol for quality controls in DWI is still lacking. The DWI quality assurance protocol proposed in this study can be applied in order to assess the reliability of DWI-derived indices before tackling single- as well as multicenter studies.


Subject(s)
Diffusion Magnetic Resonance Imaging/instrumentation , Diffusion Magnetic Resonance Imaging/standards , Image Interpretation, Computer-Assisted/instrumentation , Image Interpretation, Computer-Assisted/standards , Quality Assurance, Health Care/standards , Diffusion Magnetic Resonance Imaging/methods , Equipment Design , Equipment Failure Analysis , Image Interpretation, Computer-Assisted/methods , Italy , Phantoms, Imaging , Quality Assurance, Health Care/methods , Reproducibility of Results , Sensitivity and Specificity
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