Citations

AbstractObjectiveTo evaluate the magnetic resonance (MR) image artifact and image distortion associated with the two transcutaneous bone conduction implants currently available in the United States.Study DesignCadaveric study.MethodsTwo cadaveric head specimens (1 male, 1 female) were unilaterally implanted according to manufacturer guidelines and underwent MR imaging (General Electric and Siemens 1.5 T scanners) under the following device conditions: (1) no device, (2) Cochlear Osia with magnet and headwrap, (3) Cochlear Osia without magnet, and (4) MED‐EL Bonebridge with magnet. Maximum metal mitigation techniques were employed in all conditions, and identical sequences were obtained. Blinded image scoring (diagnostic vs nondiagnostic image) was performed by experienced neuroradiologists according to anatomical subsites.ResultsAll device conditions produced artifact and image distortion. The Osia with magnet produced diagnostic T1‐ and T2‐weighted images of the ipsilateral temporal bone, however, non‐echo planar imaging diffusion‐weighted imaging (DWI) was nondiagnostic. The Osia without magnet scanned on the Siemens MR imaging demonstrated the least amount of artifact and was the only condition that allowed for diagnostic imaging of the ipsilateral temporal bone on DWI. The Bonebridge produced a large area of artifact and distortion with the involvement of the ipsilateral and contralateral temporal bones.ConclusionIn summary, of the three device conditions (Osia with magnet, Osia without magnet, and Bonebridge), Osia without magnet offered the least amount of artifact and distortion and was the only condition in which diagnostic DWI was available for the middle ear and mastoid regions on the Siemens MR imaging scanner.

In blood-oxygen-level-dependent (BOLD)-based resting-state functional (RS-fMRI) studies, usage of multi-echo echo-planar-imaging (ME-EPI) is limited due to unacceptable late echo times when high spatial resolution is used. Equipped with high-performance gradients, the compact 3T MRI system (C3T) enables a three-echo whole-brain ME-EPI protocol with smaller than 2.5 mm isotropic voxel and shorter than 1 s repetition time, as required in landmark fMRI studies. The performance of the ME-EPI was comprehensively evaluated with signal variance reduction and region-of-interest-, seed- and independent-component-analysis-based functional connectivity analyses and compared with a counterpart of single-echo EPI with the shortest TR possible. Through the multi-echo combination, the thermal noise level is reduced. Functional connectivity, as well as signal intensity, are recovered in the medial orbital sulcus and anterior transverse collateral sulcus in ME-EPI. It is demonstrated that ME-EPI provides superior sensitivity and accuracy for detecting functional connectivity and/or brain networks in comparison with single-echo EPI. In conclusion, the high-performance gradient enabled high-spatial-temporal resolution ME-EPI would be the method of choice for RS-fMRI study on the C3T.

Abstract Objective . Interleaved reverse-gradient fMRI (RG-fMRI) with a point-spread-function (PSF) mapping-based distortion correction scheme has the potential to minimize signal loss in echo-planar-imaging (EPI). In this work, the RG-fMRI is further improved by imaging protocol optimization and application of reverse Fourier acquisition. Approach . Multi-band imaging was adapted for RG-fMRI to improve the temporal and spatial resolution. To better understand signal dropouts in forward and reverse EPIs, a simple theoretical relationship between echo shift and geometric distortion was derived and validated by the reliable measurements using PSF mapping method. After examining practical imaging protocols for RG-fMRI in three subjects on both a conventional whole-body and a high-performance compact 3 T, the results were compared and the feasibility to further improve the RG-fMRI scheme were explored. High-resolution breath-holding RG-fMRI was conducted with nine subjects on the compact 3 T and the fMRI reliability improvement in high susceptibility brain regions was demonstrated. Finally, reverse Fourier acquisition was applied to RG-fMRI, and its benefit was assessed by a simulation study based on the breath-holding RG-fMRI data. Main results . The temporal and spatial resolution of the multi-band RG-fMRI became feasible for whole-brain fMRI. Echo shift measurements from PSF mapping well estimated signal dropout effects in the EPI pair and were useful to further improve the RG-fMRI scheme. Breath-holding RG-fMRI demonstrated improved fMRI reliability in high susceptibility brain regions. Reverse partial Fourier acquisition omitting the late echoes could further improve the temporal or spatial resolution for RG-fMRI without noticeable signal degradation and spatial resolution loss. Significance . With the improved imaging scheme, RG-fMRI could reliably investigate the functional mechanisms of the human brain in the temporal and frontal areas suffering from susceptibility-induced functional sensitivity loss.

PurposeThe purpose is to develop a model‐based image‐reconstruction method using wavelet sparsity regularization for maintaining restoration of through‐plane resolution but with improved retention of SNR versus linear reconstruction using Tikhonov (TK) regularization in high through‐plane resolution (1 mm) T2‐weighted spin‐echo (T2SE) images of the prostate.MethodsA wavelet sparsity (WS)–regularized image reconstruction was developed that takes as input a set of ≈80 overlapped 3‐mm‐thick slices acquired using a T2SE multislice scan and typically 30 coil elements. After testing in contrast and resolution phantoms and calibration in 6 subjects, the WS reconstruction was evaluated in 16 consecutive prostate T2SE MRI exams. Results reconstructed with nominal 1‐mm thickness were compared with those from the TK reconstruction with the same raw data. Results were evaluated radiologically. The ratio of magnitude of prostate signal to periprostatic muscle signal was used to assess the presence of noise reduction. Technical performance was also compared with a commercial 3D‐T2SE sequence.ResultsThe new WS reconstruction was assessed as superior statistically to TK for overall SNR, contrast, and multiple evaluation criteria related to sharpness while retaining the high (1 mm) through‐plane resolution. Wavelet sparsity tended to provide improved overall diagnostic quality versus TK, but not significantly so. In all 16 studies, the prostate‐to‐muscle signal ratio increased.ConclusionsModel‐based WS‐regularized reconstruction consistently provides improved SNR in high (1 mm) through‐plane resolution images of prostate T2SE MRI versus linear reconstruction using TK regularization.

Objective This study investigates a locally low-rank (LLR) denoising algorithm applied to source images from a clinical task-based functional MRI (fMRI) exam before post-processing for improving statistical confidence of task-based activation maps. Methods Task-based motor and language fMRI was obtained in eleven healthy volunteers under an IRB approved protocol. LLR denoising was then applied to raw complex-valued image data before fMRI processing. Activation maps generated from conventional non-denoised (control) data were compared with maps derived from LLR-denoised image data. Four board-certified neuroradiologists completed consensus assessment of activation maps; region-specific and aggregate motor and language consensus thresholds were then compared with nonparametric statistical tests. Additional evaluation included retrospective truncation of exam data without and with LLR denoising; a ROI-based analysis tracked t-statistics and temporal SNR (tSNR) as scan durations decreased. A test-retest assessment was performed; retest data were matched with initial test data and compared for one subject. Results fMRI activation maps generated from LLR-denoised data predominantly exhibited statistically significant ( p = 4.88×10 –4 to p = 0.042; one p = 0.062) increases in consensus t-statistic thresholds for motor and language activation maps. Following data truncation, LLR data showed task-specific increases in t-statistics and tSNR respectively exceeding 20 and 50% compared to control. LLR denoising enabled truncation of exam durations while preserving cluster volumes at fixed thresholds. Test-retest showed variable activation with LLR data thresholded higher in matching initial test data. Conclusion LLR denoising affords robust increases in t-statistics on fMRI activation maps compared to routine processing, and offers potential for reduced scan duration while preserving map quality.

PurposeInversion algorithms used to convert acquired MR elastography wave data into material property estimates often assume that the underlying materials are locally homogeneous. Here we evaluate the impact of that assumption on stiffness estimates in gray‐matter regions of interest in brain MR elastography.MethodsWe describe an updated neural network inversion framework using finite‐difference model–derived data to train convolutional neural network inversion algorithms. Neural network inversions trained on homogeneous simulations (homogeneous learned inversions [HLIs]) or inhomogeneous simulations (inhomogeneous learned inversions [ILIs]) are generated with a variety of kernel sizes. These inversions are evaluated in a brain MR elastography simulation experiment and in vivo in a test–retest repeatability experiment including 10 healthy volunteers.ResultsIn simulation and in vivo, HLI and ILI with small kernels produce similar results. As kernel size increases, the assumption of homogeneity has a larger effect, and HLI and ILI stiffness estimates show larger differences. At each inversion's optimal kernel size in simulation (7 × 7 × 7 for HLI, 11 × 11 × 11 for ILI), ILI is more sensitive to true changes in stiffness in gray‐matter regions of interest in simulation. In vivo, there is no difference in the region‐level repeatability of stiffness estimates between the inversions, although ILI appears to better maintain the stiffness map structure as kernel size increases, while decreasing the spatial variance in stiffness estimates.ConclusionsThis study suggests that inhomogeneous inversions provide small but significant benefits even when large stiffness gradients are absent.

Abstract Objective . Ultrasound attenuation coefficient estimation (ACE) has diagnostic potential for clinical applications such as quantifying fat content in the liver. Previously, we have proposed a system-independent ACE technique based on spectral normalization of different frequencies, called the reference frequency method (RFM). This technique does not require a well-calibrated reference phantom for normalization. However, this method may be vulnerable to severe reverberation clutter introduced by the body wall. The clutter superimposed on liver echoes may bias the estimation. Approach . We proposed to use robust principal component analysis, combined with wavelet-based sparsity promotion, to suppress the severe reverberation clutters. The capability to mitigate the reverberation clutters was validated through phantom and in vivo studies. Main Results . In the phantom studies with added reverberation clutters, higher normalized cross-correlation and smaller mean absolute errors were attained as compared to RFM results without the proposed method, demonstrating the capability to reconstruct tissue signals from reverberations. In a pilot patient study, the correlation between ACE and proton density fat fraction (PDFF), a measurement of liver fat by MRI as a reference standard, was investigated. The proposed method showed an improvement of the correlation (coefficient of determination, R = 0.82) as compared with the counterpart without the proposed method ( R = 0.69). Significance : The proposed method showed the feasibility of suppressing the reverberation clutters, providing an important basis for the development of a robust ACE with large reverberation clutters.

BackgroundLocalized regions of left–right image intensity asymmetry (LRIA) were incidentally observed on T2‐weighted (T2‐w) and T1‐weighted (T1‐w) diagnostic magnetic resonance imaging (MRI) images. Suspicion of herpes encephalitis resulted in unnecessary follow‐up imaging. A nonbiological imaging artifact that can lead to diagnostic uncertainty was identified.PurposeTo investigate whether systematic LRIA exist for a range of scanner models and to determine if LRIA can introduce diagnostic uncertainty.Study TypeA retrospective study using the Alzheimer's Disease Neuroimaging Initiative (ADNI) data base.SubjectsOne thousand seven hundred fifty‐three (median age: 72, males/females: 878/875) unique participants with longitudinal data were included.Field Strength3T.SequencesT1‐w three‐dimensional inversion‐recovery spoiled gradient‐echo (IR‐SPGR) or magnetization‐prepared rapid gradient‐echo (MP‐RAGE) and T2‐w fluid‐attenuated inversion recovery (FLAIR) long tau fast spin echo inversion recovery (LT‐FSE‐IR). Only General Electric, Philips, and Siemens' product sequences were used.AssessmentLRIA was calculated as the left–right percent difference with respect to the mean intensity from automated anatomical atlas segmented regions. Three neuroradiologists with 37 (**), 32 (**), and 3 (**) years of experience rated the clinical impact of 30 T2‐w three‐dimensional FLAIR exams with LRIA to determine the diagnostic uncertainty. Statistical comparisons between retrospective intensity normalized T1m and original T1‐w images were made.Statistical TestsFor each image type, a linear mixed effects model was fit using LRIA scores from all scanners, regions, and participants as the outcome and age and sex as predictors. Statistical significance was defined as having a P‐value <0.05.ResultsLRIA scores were significantly different from zero on most scanners. All clinicians were uncertain or recommended definite diagnostic follow‐up in 62.5% of cases with LRIA >10%. Individuals with acute brain pathology or focal neurologic deficits are not enrolled in ADNI; therefore, focal signal abnormalities were considered false positives.Data ConclusionLRIA is system specific, systematic, creates diagnostic uncertainty, and impacts IR‐SPGR, MP‐RAGE, and LT‐FSE‐IR product sequences.Level of Evidence: 2Technical Efficacy Stage: 3