Pseudolesions arising from unfolding artifacts in diffusion imaging with use of parallel acquisition: origin and remedies

The role of input imaging combination and ADC threshold on segmentation of acute ischemic stroke lesion using U-Net

BACKGROUND

To evaluate the effect of the weighting of input imaging combo and ADC threshold on the performance of the U-Net and to find an optimized input imaging combo and ADC threshold in segmenting acute ischemic stroke (AIS) lesion.

METHODS

This study retrospectively enrolled a total of 212 patients having AIS. Four combos, including ADC-ADC-ADC (AAA), DWI-ADC-ADC (DAA), DWI-DWI-ADC (DDA), and DWI-DWI-DWI (DDD), were used as input images, respectively. Three ADC thresholds including 0.6, 0.8 and 1.8 × 10-3 mm2/s were applied. Dice similarity coefficient (DSC) was used to evaluate the segmentation performance of U-Nets. Nonparametric Kruskal-Wallis test with Tukey-Kramer post-hoc tests were used for comparison. A p < .05 was considered statistically significant.

RESULTS

The DSC significantly varied among different combos of images and different ADC thresholds. Hybrid U-Nets outperformed uniform U-Nets at ADC thresholds of 0.6 × 10-3 mm2/s and 0.8 × 10-3 mm2/s (p < .001). The U-Net with imaging combo of DDD had segmentation performance similar to hybrid U-Nets at an ADC threshold of 1.8 × 10-3 mm2/s (p = .062 to 1). The U-Net using the imaging combo of DAA at the ADC threshold of 0.6 × 10-3 mm2/s achieved the highest DSC in the segmentation of AIS lesion.

CONCLUSIONS

The segmentation performance of U-Net for AIS varies among the input imaging combos and ADC thresholds. The U-Net is optimized by choosing the imaging combo of DAA at an ADC threshold of 0.6 × 10-3 mm2/s in segmentating AIS lesion with highest DSC.

KEY POINTS

• Segmentation performance of U-Net for AIS differs among input imaging combos. • Segmentation performance of U-Net for AIS differs among ADC thresholds. • U-Net is optimized using DAA with ADC = 0.6 × 10-3 mm2/s.

Elimination of residual aliasing artifact that resembles brain lesion on multi-oblique diffusion-weighted echo-planar imaging with parallel imaging using virtual coil acquisition

BACKGROUND

Single-shot diffusion-weighted echo-planar imaging (ssDW-EPI) acquired with parallel imaging and a multi-oblique scan plane may suffer from residual aliasing artifacts, resembling lesions on the calculated apparent diffusion coefficient (ADC) map.

PURPOSE

To combine ssDW-EPI and virtual coil acquisition and develop a self-reference reconstruction method to eliminate the residual aliasing artifact on multi-oblique ssDW-EPI sequence with parallel imaging and multiple signal averaging.

STUDY TYPE

Prospective.

SUBJECTS

Three healthy subjects and 50 stroke patients.

FIELD STRENGTH/SEQUENCE

Conventional ssDW-EPI with parallel imaging, and proposed ssDW-EPI with virtual coil acquisition at 1.5T.

ASSESSMENT

The efficacy of the proposed method was evaluated in 50 stroke patients by comparing the ssDW-EPI with conventional parallel imaging reconstructions. The extent of residual aliasing artifacts were rated on a 5-point Likert scale by three independent raters. Only the data without residual aliasing artifacts on conventional ssDW-EPI were included for the assessment of signal-to-noise ratio (SNR), ghost-to-signal ratio (GSR), and ADC.

STATISTICAL TESTS

The interobserver agreements for examining residual aliasing artifacts were measured by the intraclass correlation coefficient (ICC). A two-sample t-test was performed for comparing SNR, GSR, and ADC.

RESULTS

There was a perfect agreement (ICC = 1.00) in the examination of residual aliasing artifacts on images obtained using the proposed method. The incidence rates of the residual aliasing artifact on the ADC maps obtained from the scanner console and proposed method were 60% (ie, 30 out of 50) and 0%, respectively. The proposed method offers significantly lower GSR than conventional parallel imaging reconstruction (P < 0.001). There was no significant difference in SNR (P = 0.20-0.51) and ADC values (P = 0.20-0.94) between conventional parallel imaging reconstructions and the proposed method.

DATA CONCLUSION

It appears that our method could effectively eliminate artifacts and significantly improve the GSR of b = 0 T₂ WI and b > 0 DWI, as well as permit ADC measurement consistent with conventional techniques. Our method may be beneficial to clinical assessment of the brain that utilizes multi-oblique ssDW-EPI.

LEVEL OF EVIDENCE

1 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2020;51:1442-1453.

Accuracy of turbo spin-echo diffusion-weighted imaging signal intensity measurements for the diagnosis of cholesteatoma

PURPOSE

We aimed to evaluate the diagnostic accuracy of turbo spin-echo diffusion-weighted imaging (TSE-DWI) at 3 T, for cholesteatoma (CS) diagnosis, using qualitative and quantitative methods with numerical assessment of signal intensity (SI), signal intensity ratios (SIR), and apparent diffusion coefficient (ADC) values.

METHODS

In this retrospective study, two blinded observers independently evaluated the preoperative TSE-DWI images of 57 patients who were imaged with a presumed diagnosis of CS. Qualitative assessment with respect to the SI of the adjacent cortex and quantitative measurements of SI, SIR, and ADC values were performed.

RESULTS

Surgery with histopathologic examination revealed 30 CS patients and 27 patients with non-cholesteatoma (NCS) lesions including chronic inflammation and cholesterol granuloma. On TSE-DWI, 96.7% of the CS lesions and none of the NCS lesions appeared hyperintense compared with the cortex. The mean SI and SIR indices of the CS group were significantly higher and the mean ADC values significantly lower compared with those of the NCS group (P < 0.001). Using specific cutoff values for SI (92.5) and SIR (0.9), CS could be diagnosed with 100% sensitivity and specificity. The use of quantitative imaging further increased the sensitivity of the TSE-DWI technique.

CONCLUSION

The quantitative indices of SI, SIR, and ADC of TSE-DWI appear to be highly accurate parameters that can be used to confirm the diagnosis of CS.

Image quality assessment of single-shot turbo spin echo diffusion-weighted imaging with parallel imaging technique: a phantom study

OBJECTIVE

This study aimed to evaluate the image quality and apparent diffusion coefficient (ADC) values of single-shot turbo spin echo (TSE) diffusion-weighted (DW) images obtained using a parallel imaging (PI) technique.

METHODS

All measurements were performed on a 3.0-T whole-body MRI system and 32-channel phased-array coil. Signal-to-noise ratio (SNR) and ADC values were measured with a DW imaging (DWI) phantom comprising granulated sugar and agar. The SNRs were calculated using a subtraction method and compared among TSE-DW images at acceleration factors (AFs) of 1-4. Image blur was visually assessed on TSE-DW images of a pin phantom at AFs of 1-4. The ADC values were calculated using DW images with b = 0 and 1000 s mm(-2). The ADC values of TSE-DW images and echo-planar imaging EPI-DW images were compared.

RESULTS

The SNRs decreased as AFs increased, despite selecting the shortest echo time. A lower AF caused increased image blur in the phase-encoding direction. The ADC values of TSE-DWI tended to be lower than those of EPI-DWI, and AFs of 3 and 4 yielded variable ADC values on TSE-DW images.

CONCLUSION

TSE-DWI with an AF of 3 or 4 yielded reduced SNRs; in addition, the image noise and artefacts associated with PI technique may have affected ADC measurements, despite improving image blur in the phase-encoding direction.

ADVANCES IN KNOWLEDGE

Optimizing the imaging parameters of TSE-DWI is useful for providing good image quality and accurate ADC measurements.

Interleaved EPI based fMRI improved by multiplexed sensitivity encoding (MUSE) and simultaneous multi-band imaging

Functional magnetic resonance imaging (fMRI) is a non-invasive and powerful imaging tool for detecting brain activities. The majority of fMRI studies are performed with single-shot echo-planar imaging (EPI) due to its high temporal resolution. Recent studies have demonstrated that, by increasing the spatial-resolution of fMRI, previously unidentified neuronal networks can be measured. However, it is challenging to improve the spatial resolution of conventional single-shot EPI based fMRI. Although multi-shot interleaved EPI is superior to single-shot EPI in terms of the improved spatial-resolution, reduced geometric distortions, and sharper point spread function (PSF), interleaved EPI based fMRI has two main limitations: 1) the imaging throughput is lower in interleaved EPI; 2) the magnitude and phase signal variations among EPI segments (due to physiological noise, subject motion, and B0 drift) are translated to significant in-plane aliasing artifact across the field of view (FOV). Here we report a method that integrates multiple approaches to address the technical limitations of interleaved EPI-based fMRI. Firstly, the multiplexed sensitivity-encoding (MUSE) post-processing algorithm is used to suppress in-plane aliasing artifacts resulting from time-domain signal instabilities during dynamic scans. Secondly, a simultaneous multi-band interleaved EPI pulse sequence, with a controlled aliasing scheme incorporated, is implemented to increase the imaging throughput. Thirdly, the MUSE algorithm is then generalized to accommodate fMRI data obtained with our multi-band interleaved EPI pulse sequence, suppressing both in-plane and through-plane aliasing artifacts. The blood-oxygenation-level-dependent (BOLD) signal detectability and the scan throughput can be significantly improved for interleaved EPI-based fMRI. Our human fMRI data obtained from 3 Tesla systems demonstrate the effectiveness of the developed methods. It is expected that future fMRI studies requiring high spatial-resolvability and fidelity will largely benefit from the reported techniques.

Interleaved diffusion-weighted improved by adaptive partial-Fourier and multiband multiplexed sensitivity-encoding reconstruction

PURPOSE

We report a series of techniques to reliably eliminate artifacts in interleaved echo-planar imaging (EPI) based diffusion-weighted imaging (DWI).

METHODS

First, we integrate the previously reported multiplexed sensitivity encoding (MUSE) algorithm with a new adaptive Homodyne partial-Fourier reconstruction algorithm, so that images reconstructed from interleaved partial-Fourier DWI data are free from artifacts even in the presence of either (a) motion-induced k-space energy peak displacement, or (b) susceptibility field gradient induced fast phase changes. Second, we generalize the previously reported single-band MUSE framework to multiband MUSE, so that both through-plane and in-plane aliasing artifacts in multiband multishot interleaved DWI data can be effectively eliminated.

RESULTS

The new adaptive Homodyne-MUSE reconstruction algorithm reliably produces high-quality and high-resolution DWI, eliminating residual artifacts in images reconstructed with previously reported methods. Furthermore, the generalized MUSE algorithm is compatible with multiband and high-throughput DWI.

CONCLUSION

The integration of the multiband and adaptive Homodyne-MUSE algorithms significantly improves the spatial-resolution, image quality, and scan throughput of interleaved DWI. We expect that the reported reconstruction framework will play an important role in enabling high-resolution DWI for both neuroscience research and clinical uses.

Potential long-term effects of MDMA on the basal ganglia-thalamocortical circuit: a proton MR spectroscopy and diffusion-tensor imaging study

PURPOSE

To investigate the effects of 3,4-methylenedioxymethamphetamine (MDMA, commonly known as "ecstasy") on the alterations of brain metabolites and anatomic tissue integrity related to the function of the basal ganglia-thalamocortical circuit by using proton magnetic resonance (MR) spectroscopy and diffusion-tensor MR imaging.

MATERIALS AND METHODS

This study was approved by a local institutional review board, and written informed consent was obtained from all subjects. Thirty-one long-term (>1 year) MDMA users and 33 healthy subjects were enrolled. Proton MR spectroscopy from the middle frontal cortex and bilateral basal ganglia and whole-brain diffusion-tensor MR imaging were performed with a 3.0-T system. Absolute concentrations of metabolites were computed, and diffusion-tensor data were registered to the International Consortium for Brain Mapping template to facilitate voxel-based group comparison.

RESULTS

The mean myo-inositol level in the basal ganglia of MDMA users (left: 4.55 mmol/L ± 2.01 [standard deviation], right: 4.48 mmol/L ± 1.33) was significantly higher than that in control subjects (left: 3.25 mmol/L ± 1.30, right: 3.31 mmol/L ± 1.19) (P < .001). Cumulative lifetime MDMA dose showed a positive correlation with the levels of choline-containing compounds (Cho) in the right basal ganglia (r = 0.47, P = .02). MDMA users also showed a significant increase in fractional anisotropy (FA) in the bilateral thalami and significant changes in water diffusion in several regions related to the basal ganglia-thalamocortical circuit as compared with control subjects (P < .05; cluster size, >50 voxels).

CONCLUSION

Increased myo-inositol and Cho concentrations in the basal ganglia of MDMA users are suggestive of glial response to degenerating serotonergic functions. The abnormal metabolic changes in the basal ganglia may consequently affect the inhibitory effect of the basal ganglia to the thalamus, as suggested by the increased FA in the thalamus and abnormal changes in water diffusion in the corresponding basal ganglia-thalamocortical circuit.

Diffusion tensor MR imaging and fiber tractography: technical considerations

This second article of the 2-part review builds on the theoretic background provided by the first article to cover the major technical factors that affect image quality in diffusion imaging, including the acquisition sequence, magnet field strength, gradient amplitude, and slew rate as well as multichannel radio-frequency coils and parallel imaging. The sources of many common diffusion image artifacts are also explored in detail. The emphasis is on optimizing these technical factors for state-of-the-art diffusion-weighted imaging and diffusion tensor imaging (DTI) based on the best available evidence in the literature. An overview of current methods for quantitative analysis of DTI data and fiber tractography in clinical research is also provided.