BACKGROUND AND PURPOSE: Spiral MR imaging has several advantages compared with Cartesian MR imaging that can be leveraged for added clinical value. A multicenter multireader study was designed to compare spiral with standard-of-care Cartesian postcontrast structural brain MR imaging on the basis of relative performance in 10 metrics of image quality, artifact prevalence, and diagnostic benefit. MATERIALS AND METHODS: Seven clinical sites acquired 88 total subjects. For each subject, sites acquired 2 postcontrast MR imaging scans: a spiral 2D T1 spin-echo, and 1 of 4 routine Cartesian 2D T1 spin-echo/TSE scans (fully sampled spin-echo at 3T, 1.5T, partial Fourier, TSE). The spiral acquisition matched the Cartesian scan for scan time, geometry, and contrast. Nine neuroradiologists independently reviewed each subject, with the matching pair of spiral and Cartesian scans compared side-by-side, and scored on 10 image-quality metrics (5-point Likert scale) focused on intracranial assessment. The Wilcoxon signed rank test evaluated relative performance of spiral versus Cartesian, while the Kruskal-Wallis test assessed interprotocol differences. RESULTS: Spiral was superior to Cartesian in 7 of 10 metrics (flow artifact mitigation, SNR, GM/WM contrast, image sharpness, lesion conspicuity, preference for diagnosing abnormal enhancement, and overall intracranial image quality), comparable in 1 of 10 metrics (motion artifacts), and inferior in 2 of 10 metrics (susceptibility artifacts, overall extracranial image quality) related to magnetic susceptibility (P , .05). Interprotocol comparison confirmed relatively higher SNR and GM/WM contrast for partial Fourier and TSE protocol groups, respectively (P , .05). CONCLUSIONS: Spiral 2D T1 spin-echo for routine structural brain MR imaging is feasible in the clinic with conventional scanners and was preferred by neuroradiologists for overall postcontrast intracranial evaluation. ABBREVIATIONS: Cart 4 Cartesian; IQ 4 image quality; NA 4 not applicable; SE 4 spin-echo; TSE 4 turbo spin-echo S tructural T1-weighted sequences are a fundamental component of routine postcontrast brain MR imaging examinations. These contrast-enhanced images are used for the diagnostic detection and evaluation of abnormal enhancement, including tumors, infections, and inflammatory diseases. Cartesian 2D T1 spin-echo (SE) is widely used as the standard-of-care, though it is relatively slow due to its single phase-encode per shot k-space coverage, and is not compatible with parallel imaging due to strong free-induction decay artifacts from the refocusing radiofrequency pulse. Two routine speed-up options include Cartesian 2D T1-SE with partial-Fourier k-space coverage, but at the cost of reduced SNR; alternatively, Cartesian 2D T1 turbo spin-echo

Dynamic magnetic field shimming is gaining interest for field sensitive MRI acquisitions. Using slice based or real-time shim updating, significant improvements in static field (B 0 ) uniformity can be obtained. While the ability to rapidly switch shim fields can improve overall B 0 homogeneity, it induces eddy current fields that must be characterized and compensated for. Methods used to achieve this have thus far been based on linear projection spin echo sequences or field probe assemblies. Here, a novel imagebased method is presented to measure and characterize eddy current fields without the need for field probes or projection based measurements. This technique can be extended to characterize very high order spherical harmonic fields, making it a useful tool to calibrate next-generation shim systems implementing dynamic field steering with greater than third order shim terms. Results are used to calibrate a Dynamic Shim Updating unit for pre-emphasis and eddy current compensation. Three-dimensional datasets are acquired at multiple MR facilities containing complete spatiotemporal field information to compensate eddy current field self-and cross-terms for up to third order. Furthermore, simulation studies are performed to investigate the effect of scan resolution and phantom size with respect to accurate eddy current field characterization.

Magnetic resonance (MR) imaging is vulnerable to a variety of artifacts, which potentially degrade the perceived quality of MR images and, consequently, may cause inefficient and/or inaccurate diagnosis. In general, these artifacts can be classified as structured or unstructured depending on the correlation of the artifact with the original content. In addition, the artifact can be white or colored depending on the flatness of the frequency spectrum of the artifact. In current MR imaging applications, design choices allow one type of artifact to be traded off with another type of artifact. Hence, to support these design choices, the relative impact of structured versus unstructured or colored versus white artifacts on perceived image quality needs to be known. To this end, we conducted two subjective experiments. Clinical application specialists rated the quality of MR images, distorted with different types of artifacts at various levels of degradation. The results demonstrate that unstructured artifacts deteriorate quality less than structured artifacts, while colored artifacts preserve quality better than white artifacts.

In current magnetic resonance (MR) imaging systems, design choices are confronted with a trade-off between structured (i.e. artifacts) and unstructured noise. The impact of both types of noise on perceived image quality, however, is so far unknown, while this knowledge would be highly beneficial for further improvement of MR imaging systems. In this paper, we investigate how ghosting artifacts (i.e. structured noise) and random noise, applied at the same energy level in the distortion, affect the perceived quality of MR images. To this end, a perception experiment is conducted with human observers rating the quality of a set of images, distorted with various levels of ghosting and noise. To also understand the influence of professional expertise on the image quality assessment task, two groups of observers with different levels of medical imaging experience participated in the experiment: one group contained fifteen clinical scientists or application specialists, and the other group contained eighteen naïve observers. Experimental results indicate that experts and naïve observers differently assess the quality of MR images degraded with ghosting/noise. Naïve observers consistently rate images degraded with ghosting higher than images degraded with noise, independent of the energy level of the distortion, and of the image content. For experts, the relative impact of ghosting and noise on perceived quality tends to depend on the energy level of the distortion and on the image content, but overall the energy of the distortion is a promising metric to predict perceived image quality.Keywords: MRI, perceived image quality, ghosting, noise, human visual system PURPOSEIn current magnetic resonance (MR) imaging systems, a variety of artifacts and noise, affecting the perceived quality of MR images is generated. Ghosting, which is a cross-talk type of artifact that generates a lower-intensity double image, spatially shifted with respect to the original content, is just one example of such an artifact. In an MR imaging system, there are situations where structured noise (e.g. ghosting) on one hand can be traded off with unstructured noise on the other hand. For example, one of the processing steps to avoid ghosting in the system is to redistribute its energy so that it appears as random noise spread over the entire image. Whether this way of processing changes the perceived quality of MR images, and if so, to what extent is so far unknown. Therefore, it is of fundamental importance to understand the relative impact of structured versus unstructured noise on the perceived quality of MR images, in order to improve MR imaging systems. In addition, it is worthwhile to investigate the influence of professional expertise on image quality perception. The impact of professionalism on diagnostic quality, of course, is known to be huge ([1]-[3]), but in case the impact of professionalism on perceived image quality is limited, larger-size studies could be undertaken without being too much of a burden for the limited number o...

Diffusion-weighted EPI has become an indispensable tool in body MRI. Geometric distortions due to field inhomogeneities are more prominent at large field–of–view and require correction for comparison with T2W TSE. Several known correction methods require acquisition of additional lengthy scans, which are difficult to apply in body imaging. We implement and evaluate a geometry correction method based on the already available non phase-encoded EPI reference data used for Nyquist ghost removal. The method is shown to provide accurate and robust global geometry correction in the absence of strong, local phase offsets. It does not require additional time for calibrations and is directly compatible with parallel imaging methods. The resulting images can serve as improved starting point for additional geometry correction methods relying on feature extraction and registration.