A quality assurance protocol for diffusion tensor imaging using the head phantom from American College of Radiology

Abstract

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 ¼ 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.

Assessment of diffusion tensor image quality across sites and vendors using the American College of Radiology head phantom

“…As discussed previously, it is important to establish what one considers satisfactory results for QA test values (9) . At this stage, more phantom data and studies correlating image quality and phantom results are needed in order to establish corrective action criteria for this QA procedure.…”

“…The DICOM data was converted into the Philips par/rec format and registered using Philips vendor proprietary software (Philips Research Imaging Development Environment (PRIDE)). The resulting images were analyzed at Slice 5 (a slice with square grid lines) and Slice 7 (a uniform slice) as defined by ACR (see “Site Scanning Instructions for Use of the MR Phantom for the ACRTM MRI Accreditation Program” in the website mentioned above) to evaluate several aspects of the data quality: (i) SNR of the $\mathrm{b}=0$ image at the center and peripheries of the phantom on Slice 7; (9) (ii) geometric distortion of $\mathrm{b}=0$ images caused by magnetic susceptibility effects on Slice 5; (iii) geometric distortion of averaged diffusion weighted images (9) relative to $\mathrm{b}=0$ image on Slice 5 caused by eddy currents induced by diffusion encoding gradients; (iv) ROI‐based FA and MD measurements on Slice 7; and (v) pixel‐based FA and MD measurement on Slice 7. These analyses closely follow a previous work (9) with minor modifications.…”

“…To address the need for DTI quality assurance (QA) and the lack of a widely available DTI phantom, a QA protocol using the head phantom from ACR has been described recently. (9) We tested this QA protocol for diffusion imaging acquired at 3T scanners from different vendors at multiple sites and describe the results in this study. This study was conducted during the planning of a multicenter study of the neonatal brains.…”

Phantoms for diffusion-weighted imaging and diffusion tensor imaging quality control: a review and new perspectives

“…There are gels, for isotropic or anisotropic diffusion studies, whose magnetic properties are similar to healthy or pathological tissue (Hellerbach et al, 2013;Kato et al, 2005). Some authors propose applying the ACR MRI head phantom to evaluate scanner parameters related to degradation of DWI and DTI images, such as SNR, low contrast detectability and uniformity (Wang et al, 2011). Computational phantoms can also contribute to QC of DWI and DTI image processing algorithms, being useful to evaluate tractography based on High-Resolution Angle Diffusion Imaging (HARDI), Q-Ball and Diffusion Spectral Imaging (DSI), applicable to analysis of crossing fibers in a voxel (Leemans et al, 2005).…”

Design of a fused phantom for quantitative evaluation of brain metabolites and enhanced quality assurance testing for magnetic resonance imaging and spectroscopy

“…The ACR MRI phantom has recently been used for QA of standard and diffusion tensor imaging (DTI) (Wang et al, 2011;Lee et al, 2014). However, the ACR MRI phantom cannot evaluate the performance of advanced MRI, including spectroscopy .…”