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A quality assurance protocol for diffusion tensor imaging using the head phantom from American College of Radiology
Author(s) -
Wang Zhiyue J.,
Seo Youngseob,
Chia Jonathan M.,
Rollins Nancy K.
Publication year - 2011
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.3595111
Subject(s) - imaging phantom , image quality , region of interest , nuclear medicine , diffusion mri , reproducibility , scanner , fractional anisotropy , quality assurance , distortion (music) , pixel , medicine , physics , nuclear magnetic resonance , artificial intelligence , mathematics , optics , computer science , magnetic resonance imaging , radiology , image (mathematics) , statistics , amplifier , external quality assessment , optoelectronics , cmos , pathology
Purpose: To propose a quality assurance procedure for routine clinical diffusion tensor imaging (DTI) using the widely available American College of Radiology (ACR) head phantom. Methods: Analysis was performed on the data acquired at 1.5 and 3.0 T on whole body clinical MRI scanners using the ACR phantom and included the following: (1) the signal‐to‐noise ratio (SNR) at the center and periphery of the phantom, (2) image distortion by EPI readout relative to spin echo imaging, (3) distortion of high‐b images relative to the b = 0 image caused by diffusion encoding, and (4) determination of fractional anisotropy (FA) and mean diffusivity (MD) measured with region‐of‐interest (ROI) and pixel‐based approaches. Reproducibility of the measurements was assessed by five repetitions of data acquisition on each scanner. Results: The SNR at the phantom center was approximately half of that near the periphery at both 1.5 and 3 T. The image distortion by the EPI readout was up to 7 mm at 1.5 T and 10 mm at 3 T. The typical distortion caused by eddy currents from diffusion encoding was on the order of 0.5 mm. The difference between ROI‐based and pixel‐based MD quantification was 1.4% at 1.5 T and 0.3% at 3 T. The ROI‐based MD values were in close agreement (within 2%) with the reference values. The ROI‐based FA values were approximately a factor of 10 smaller than pixel‐based values and less than 0.01. The measurement reproducibility was sufficient for quality assurance (QA) purposes. Conclusions: This QA approach is simple to perform and evaluates key aspects of the scanner performance for DTI data acquisition using a widely available phantom.