Accelerated MRI of the Lumbar Spine Using Compressed Sensing: Quality and Efficiency

Fast imaging of lenticulostriate arteries by high-resolution black-blood T1-weighted imaging with variable flip angles and acceleration by compressed sensitivity encoding

OBJECTIVE

We investigated the feasibility of using compressed sensitivity encoding (CS-SENSE) to accelerate high-resolution black-blood T1-weighted imaging with variable flip angles (T1WI-VFA) for efficient visualization and characterization of lenticulostriate arteries (LSAs) on a 3.0 T MR scanner.

MATERIALS AND METHODS

Twenty-five healthy volunteers and 18 patients with the cerebrovascular disease were prospectively enrolled. Healthy volunteers underwent T1WI-VFA sequences with different acceleration factors (AFs), including conventional sensitivity encoding (SENSE) AF = 3 and CS-SENSE AF = 3, 4, 5, and 6 (SENSE3, CS3, CS4, CS5, CS6, respectively) at 3 Tesla MRI scanner. Objective evaluation (contrast ratio and number, length, and branches of LSAs) and subjective evaluation (overall image quality and LSA visualization scores) were used to assess image quality and LSA visualization. Comparisons were performed among the 5 sequences to select the best AF. All patients underwent both T1WI-VFA with the optimal AF and digital subtraction angiography (DSA) examination, and the number of LSAs observed by T1WI-VFA was compared with that by DSA.

RESULTS

Pair-wise comparisons among CS3, CS4, and SENSE3 revealed no significant differences in both objective measurements and subjective evaluation (all P > 0.05). In patients, there was no significant difference in LSA counts on the same side between T1WI-VFA with CS4 and DSA (3, 3-4 and 3, 3-3, P = 0.243).

CONCLUSIONS

CS3 provided better LSA visualization but a longer scan duration compared to CS4. And, CS4 strikes a good balance between LSA visualization and acquisition time, which is recommended for routine clinical use.

Diagnostic evaluation of deep learning accelerated lumbar spine MRI

BACKGROUND AND PURPOSE

Deep learning (DL) accelerated MR techniques have emerged as a promising approach to accelerate routine MR exams. While prior studies explored DL acceleration for specific lumbar MRI sequences, a gap remains in comprehending the impact of a fully DL-based MRI protocol on scan time and diagnostic quality for routine lumbar spine MRI. To address this, we assessed the image quality and diagnostic performance of a DL-accelerated lumbar spine MRI protocol in comparison to a conventional protocol.

METHODS

We prospectively evaluated 36 consecutive outpatients undergoing non-contrast enhanced lumbar spine MRIs. Both protocols included sagittal T1, T2, STIR, and axial T2-weighted images. Two blinded neuroradiologists independently reviewed images for foraminal stenosis, spinal canal stenosis, nerve root compression, and facet arthropathy. Grading comparison employed the Wilcoxon signed rank test. For the head-to-head comparison, a 5-point Likert scale to assess image quality, considering artifacts, signal-to-noise ratio (SNR), anatomical structure visualization, and overall diagnostic quality. We applied a 15% noninferiority margin to determine whether the DL-accelerated protocol was noninferior.

RESULTS

No significant differences existed between protocols when evaluating foraminal and spinal canal stenosis, nerve compression, or facet arthropathy (all p > .05). The DL-spine protocol was noninferior for overall diagnostic quality and visualization of the cord, CSF, intervertebral disc, and nerve roots. However, it exhibited reduced SNR and increased artifact perception. Interobserver reproducibility ranged from moderate to substantial (κ = 0.50-0.76).

CONCLUSION

Our study indicates that DL reconstruction in spine imaging effectively reduces acquisition times while maintaining comparable diagnostic quality to conventional MRI.

Diagnostic utility of 3D MRI sequences in the assessment of central, recess and foraminal stenoses of the spine: a systematic review

OBJECTIVE

To perform a systematic literature review on the diagnostic utility of 3D MRI sequences in the assessment of central canal, recess and foraminal stenosis in the spine.

METHODS

The databases PubMed, MEDLINE (via OVID) and The Cochrane Central Register of Controlled Trials, were searched for studies that investigated the diagnostic use of 3D MRI to evaluate stenoses in various parts of the spine in humans. Three reviewers examined the literature and conducted systematic review according to PRISMA 2020 guidelines.

RESULTS

Thirty studies were retrieved from 2 595 publications for this systematic review. The overall diagnostic performance of 3D MRI outperformed the conventional 2D MRI with reported sensitivities ranging from 79 to 100% and specificities ranging from 86 to 100% regarding the evaluation of central, recess and foraminal stenoses. In general, high level of agreement (both intra- and interrater) regarding visibility and pathology on 3D sequences was reported. Studies show that well-optimized 3D sequences allow the use of higher spatial resolution, similar scan time and increased SNR and CNR when compared to corresponding 2D sequences. However, the benefit of 3D sequences is in the additional information provided by them and in the possibility to save total protocol scan times.

CONCLUSION

The literature on the spine 3D MRI assessment of stenoses is heterogeneous with varying MRI protocols and diagnostic results. However, the 3D sequences offer similar or superior detection of stenoses with high reliability. Especially, the advantage of 3D MRI seems to be the better evaluation of recess stenoses.

Deep Learning-based Image Enhancement Techniques for Fast MRI in Neuroimaging

Despite its superior soft tissue contrast and non-invasive nature, MRI requires long scan times due to its intrinsic signal acquisition principles, a main drawback which technological advancements in MRI have been focused on. In particular, scan time reduction is a natural requirement in neuroimaging due to detailed structures requiring high resolution imaging and often volumetric (3D) acquisitions, and numerous studies have recently attempted to harness deep learning (DL) technology in enabling scan time reduction and image quality improvement. Various DL-based image reconstruction products allow for additional scan time reduction on top of existing accelerated acquisition methods without compromising the image quality.

Reconstruction of 3D knee MRI using deep learning and compressed sensing: a validation study on healthy volunteers

BACKGROUND

To investigate the potential of combining compressed sensing (CS) and artificial intelligence (AI), in particular deep learning (DL), for accelerating three-dimensional (3D) magnetic resonance imaging (MRI) sequences of the knee.

METHODS

Twenty healthy volunteers were examined using a 3-T scanner with a fat-saturated 3D proton density sequence with four different acceleration levels (10, 13, 15, and 17). All sequences were accelerated with CS and reconstructed using the conventional and a new DL-based algorithm (CS-AI). Subjective image quality was evaluated by two blinded readers using seven criteria on a 5-point-Likert-scale (overall impression, artifacts, delineation of the anterior cruciate ligament, posterior cruciate ligament, menisci, cartilage, and bone). Using mixed models, all CS-AI sequences were compared to the clinical standard (sense sequence with an acceleration factor of 2) and CS sequences with the same acceleration factor.

RESULTS

3D sequences reconstructed with CS-AI achieved significantly better values for subjective image quality compared to sequences reconstructed with CS with the same acceleration factor (p ≤ 0.001). The images reconstructed with CS-AI showed that tenfold acceleration may be feasible without significant loss of quality when compared to the reference sequence (p ≥ 0.999).

CONCLUSIONS

For 3-T 3D-MRI of the knee, a DL-based algorithm allowed for additional acceleration of acquisition times compared to the conventional approach. This study, however, is limited by its small sample size and inclusion of only healthy volunteers, indicating the need for further research with a more diverse and larger sample.

TRIAL REGISTRATION

DRKS00024156.

RELEVANCE STATEMENT

Using a DL-based algorithm, 54% faster image acquisition (178 s versus 384 s) for 3D-sequences may be possible for 3-T MRI of the knee.

KEY POINTS

• Combination of compressed sensing and DL improved image quality and allows for significant acceleration of 3D knee MRI. • DL-based algorithm achieved better subjective image quality than conventional compressed sensing. • For 3D knee MRI at 3 T, 54% faster image acquisition may be possible.

Second-Order Motion-Compensated Echo-Planar Cardiac Diffusion-Weighted MRI: Usefulness of Compressed Sensitivity Encoding

BACKGROUND

Cardiac diffusion-weighted imaging (DWI) using second-order motion-compensated spin echo (M2C) can provide noninvasive in-vivo microstructural assessment, but limited by relatively low signal-to-noise ratio (SNR). Echo-planar imaging (EPI) with compressed sensitivity encoding (EPICS) could address these issues.

PURPOSE

To combine M2C DWI and EPCIS (M2C EPICS DWI), and compare image quality for M2C DWI.

STUDY TYPE

Prospective.

POPULATION

Ten ex-vivo hearts, 10 healthy volunteers (females, 5 [50%]; mean ± SD of age, 25 ± 4 years), and 12 patients with diseased hearts (female, 1 [8.3%]; mean ± SD of age, 44 ± 16 years; including coronary artery heart disease, congenital heart disease, dilated cardiomyopathy, amyloidosis, and myocarditis).

FIELD STRENGTH/SEQUENCE

3-T, M2C EPICS DWI, and M2C DWI.

ASSESSMENT

The apparent SNR (aSNR) and the rating scores were used to evaluate and compared image quality of all three groups. The aSNR was calculated usingaSNR = Mean intensity myocardium / Standard deviation myocardium $$ \mathrm{aSNR}={\mathrm{Mean}\ \mathrm{intensity}}_{\mathrm{myocardium}}/{\mathrm{Standard}\ \mathrm{deviation}}_{\mathrm{myocardium}} $$ , and the myocardium was segmented manually. Three observers independently rated subjective image quality using a 5-point Likert scale.

STATISTICAL TESTS

Bland-Altman analysis and paired t-tests. The threshold for statistical significance was set at P < 0.05.

RESULTS

In healthy volunteers, the aSNR with a b-value of 450 s/mm2 acquired by M2C EPICS DWI was significantly higher than M2C DWI at in-plane resolutions of 3.0 × 3.0, 2.5 × 2.5, and 2.0 × 2.0 mm2. In patients with diseased hearts, the aSNR ofM2C EPICS DWI was also significantly higher than that for M2C DWI (bias of M2C EPICS-M2C = 1.999, 95% limits of agreement, 0.362 to 3.636; mean ± SD, 7.80 ± 1.37 vs. 5.80 ± 0.81). The ADC values of M2C EPICS was significantly higher than M2C DWI in in-vivo hearts. Over 80% of the images with rating scores for M2C EPICS DWI were higher than M2C DWI in in-vivo hearts.

DATA CONCLUSION

Cardiac imaging by M2C EPICS DWI may demonstrate better overall image quality and higher aSNR than M2C DWI.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 1.

Highly compressed SENSE accelerated relaxation-enhanced angiography without contrast and triggering (REACT) for fast non-contrast enhanced magnetic resonance angiography of the neck: Clinical evaluation in patients with acute ischemic stroke at 3 tesla

BACKGROUND AND PURPOSE

Long acquisition times limit the feasibility of established non-contrast-enhanced MRA (non-CE-MRA) techniques. The purpose of this study was to evaluate a highly accelerated flow-independent sequence (Relaxation-Enhanced Angiography without Contrast and Triggering [REACT]) for imaging of the extracranial arteries in acute ischemic stroke (AIS).

MATERIALS AND METHODS

Compressed SENSE (CS) accelerated (factor 7) 3D isotropic REACT (fixed scan time: 01:22 min, reconstructed voxel size 0.625 × 0.625 × 0.75 mm3) and CE-MRA (CS factor 6, scan time: 1:08 min, reconstructed voxel size 0.5 mm3) were acquired in 76 AIS patients (69.4 ± 14.3 years, 33 females) at 3 Tesla. Two radiologists assessed scans for the presence of internal carotid artery (ICA) stenosis and stated their diagnostic confidence using a 5-point scale (5 = excellent). Vessel quality of cervical arteries as well as the impact of artifacts and image noise were scored on 5-point scales (5 = excellent/none). Apparent signal- and contrast-to-noise ratios (aSNR/aCNR) were measured for the common carotid artery (CCA) and ICA (C1-segment).

RESULTS

REACT provided a sensitivity of 88.5% and specificity of 100% for clinically relevant (≥50%) ICA stenosis with substantial concordance to CE-MRA regarding stenosis grading (Cohen's kappa 0.778) and similar diagnostic confidence (REACT: mean 4.5 ± 0.4 vs. CE-MRA: 4.5 ± 0.6; P = 0.674). Presence of artifacts (3.6 ± 0.5 vs. 3.5 ± 0.7; P = 0.985) and vessel quality (all segments: 3.6 ± 0.7 vs. 3.8 ± 0.7; P = 0.004) were comparable between both techniques with REACT showing higher scores at the CCA (4.3 ± 0.6 vs. 3.8 ± 0.9; P < 0.001) and CE-MRA at V2- (3.3 ± 0.5 vs. 3.9 ± 0.8; P < 0.001) and V3-segments (3.3 ± 0.5 vs. 4.0 ± 0.8; P < 0.001). For all vessels, REACT showed a lower impact of image noise (3.8 ± 0.6 vs. 3.6 ± 0.7; P = 0.024) while yielding higher aSNR (52.5 ± 15.1 vs. 37.9 ± 12.5; P < 0.001) and aCNR (49.4 ± 15.0 vs. 34.7 ± 12.3; P < 0.001) for all vessels combined.

CONCLUSIONS

In patients with acute ischemic stroke, highly accelerated REACT provides an accurate detection of ICA stenosis with vessel quality and scan time comparable to CE-MRA.

Five-minute knee MRI: An AI-based super resolution reconstruction approach for compressed sensing. A validation study on healthy volunteers

PURPOSE

To investigate the potential of combining Compressed Sensing (CS) and a newly developed AI-based super resolution reconstruction prototype consisting of a series of convolutional neural networks (CNN) for a complete five-minute 2D knee MRI protocol.

METHODS

In this prospective study, 20 volunteers were examined using a 3T-MRI-scanner (Ingenia Elition X, Philips). Similar to clinical practice, the protocol consists of a fat-saturated 2D-proton-density-sequence in coronal, sagittal and transversal orientation as well as a sagittal T1-weighted sequence. The sequences were acquired with two different resolutions (standard and low resolution) and the raw data reconstructed with two different reconstruction algorithms: a conventional Compressed SENSE (CS) and a new CNN-based algorithm for denoising and subsequently to interpolate and therewith increase the sharpness of the image (CS-SuperRes). Subjective image quality was evaluated by two blinded radiologists reviewing 8 criteria on a 5-point Likert scale and signal-to-noise ratio calculated as an objective parameter.

RESULTS

The protocol reconstructed with CS-SuperRes received higher ratings than the time-equivalent CS reconstructions, statistically significant especially for low resolution acquisitions (e.g., overall image impression: 4.3 ± 0.4 vs. 3.4 ± 0.4, p < 0.05). CS-SuperRes reconstructions for the low resolution acquisition were comparable to traditional CS reconstructions with standard resolution for all parameters, achieving a scan time reduction from 11:01 min to 4:46 min (57 %) for the complete protocol (e.g. overall image impression: 4.3 ± 0.4 vs. 4.0 ± 0.5, p < 0.05).

CONCLUSION

The newly-developed AI-based reconstruction algorithm CS-SuperRes allows to reduce scan time by 57% while maintaining unchanged image quality compared to the conventional CS reconstruction.

Evaluation of Compressed SENSE on Image Quality and Reduction of MRI Acquisition Time: A Clinical Validation Study

RATIONALE AND OBJECTIVES

To evaluate the effect of compressed SENSE (CS) in clinical settings on scan time reduction and image quality.

MATERIALS AND METHODS

Ninety-five magnetic resonance imaging (MRI) scans from different anatomical regions were acquired, consisting of a standard protocol sequence (SS) and sequence accelerated with CS. Anonymized paired sequences were randomly displayed and rated by six blinded subspecialty radiologists. Side-by-side evaluation on perceived sharpness, perceived signal-to-noise-ratio (SNR), lesion conspicuity, and artifacts were compared and scored on a five-point Likert scale, and individual image quality was evaluated on a four-point Likert scale.

RESULTS

CS reduced overall scan time by 32% while maintaining acceptable MRI quality for all regions. The largest time savings were seen in the spine (mean = 68 seconds, 44% reduction) followed by the brain (mean = 86 seconds, 37% reduction). The sequence with maximum time savings was intracranial 3D-time-of-flight magnetic resonance angiography (202 seconds, 56% reduction). CS was mildly inferior to SS on perceived sharpness, perceived SNR, and lesion conspicuity (mean scores = 2.32-2.96, P < .001 [1: SS superior; 3: equivalent; 5: CS superior]). CS was equivalent to SS for joint and body scans on overall image quality (CS = 3.02-3.37, SS = 3.04-3.68, P > .05, [1: lowest quality and 4: highest quality]). The overall image quality of CS was slightly less for brain and spine scans (mean CS = 2.79-3.05, mean SS = 3.13-3.43, P = .021) but still diagnostic. Good overall clinical acceptance for CS (88%) was noted with full clinical acceptance for body scans (100%) and high acceptance for other regions (68%-95%).

CONCLUSION

CS significantly reduced MR acquisition time while maintaining acceptable image quality. The implementation of CS may improve departmental workflows and enhance patient care.

Fast high-quality MRI protocol of the lumbar spine with deep learning-based algorithm: an image quality and scanning time comparison with standard protocol

OBJECTIVE

The objective of this study is to prospectively compare quantitative and subjective image quality, scanning time, and diagnostic confidence between a new deep learning-based reconstruction(DLR) algorithm and standard MRI protocol of lumbar spine.

MATERIALS AND METHODS

Eighty healthy volunteers underwent 1.5T MRI examination of lumbar spine from September 2021 to May 2023. Protocol acquisition comprised sagittal T1- and T2-weighted fast spin echo and short-tau inversion recovery images and axial multislices T2-weighted fast spin echo images. All sequences were acquired with both DLR algorithm and standard protocols. Two radiologists, blinded to the reconstruction technique, performed quantitative and qualitative image quality analysis in consensus reading; diagnostic confidence was also assessed. Quantitative image quality analysis was assessed by calculating signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Qualitative image quality analysis and diagnostic confidence were assessed with a five-point Likert scale. Scanning times were also compared.

RESULTS

DLR SNR was higher in all sequences (all p<0.001). CNR of the DLR was superior to conventional dataset only for axial and sagittal T2-weighted fast spin echo images (p<0.001). Qualitative analysis showed DLR had higher overall quality in all sequences (all p<0.001), with an inter-rater agreement of 0.83 (0.78-0.86). DLR total protocol scanning time was lower compared to standard protocol (6:26 vs 12:59 min, p<0.001). Diagnostic confidence for DLR algorithm was not inferior to standard protocol.

CONCLUSION

DLR applied to 1.5T MRI is a feasible method for lumbar spine imaging providing morphologic sequences with higher image quality and similar diagnostic confidence compared with standard protocol, enabling a remarkable time saving (up to 50%).

Accelerated Musculoskeletal Magnetic Resonance Imaging

With a substantial growth in the use of musculoskeletal MRI, there has been a growing need to improve MRI workflow, and faster imaging has been suggested as one of the solutions for a more efficient examination process. Consequently, there have been considerable advances in accelerated MRI scanning methods. This article aims to review the basic principles and applications of accelerated musculoskeletal MRI techniques including widely used conventional acceleration methods, more advanced deep learning-based techniques, and new approaches to reduce scan time. Specifically, conventional accelerated MRI techniques, including parallel imaging, compressed sensing, and simultaneous multislice imaging, and deep learning-based accelerated MRI techniques, including undersampled MR image reconstruction, super-resolution imaging, artifact correction, and generation of unacquired contrast images, are discussed. Finally, new approaches to reduce scan time, including synthetic MRI, novel sequences, and new coil setups and designs, are also reviewed. We believe that a deep understanding of these fast MRI techniques and proper use of combined acceleration methods will synergistically improve scan time and MRI workflow in daily practice. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 1.

Deep learning-based reconstruction for acceleration of lumbar spine MRI: a prospective comparison with standard MRI

OBJECTIVE

To compare the image quality and diagnostic performance between standard turbo spin-echo MRI and accelerated MRI with deep learning (DL)-based image reconstruction for degenerative lumbar spine diseases.

MATERIALS AND METHODS

Fifty patients who underwent both the standard and accelerated lumbar MRIs at a 1.5-T scanner for degenerative lumbar spine diseases were prospectively enrolled. DL reconstruction algorithm generated coarse (DL_coarse) and fine (DL_fine) images from the accelerated protocol. Image quality was quantitatively assessed in terms of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) and qualitatively assessed using five-point visual scoring systems. The sensitivity and specificity of four radiologists for the diagnosis of degenerative diseases in both protocols were compared.

RESULTS

The accelerated protocol reduced the average MRI acquisition time by 32.3% as compared to the standard protocol. As compared with standard images, DL_coarse and DL_fine showed significantly higher SNRs on T1-weighted images (T1WI; both p < .001) and T2-weighted images (T2WI; p = .002 and p < 0.001), higher CNRs on T1WI (both p < 0.001), and similar CNRs on T2WI (p = .49 and p = .27). The average radiologist assessment of overall image quality for DL_coarse and DL_fine was higher on sagittal T1WI (p = .04 and p < .001) and axial T2WI (p = .006 and p = .01) and similar on sagittal T2WI (p = .90 and p = .91). Both DL_coarse and DL_fine had better image quality of cauda equina and paraspinal muscles on axial T2WI (both p = .04 for cauda equina; p = .008 and p = .002 for paraspinal muscles). Differences in sensitivity and specificity for the detection of central canal stenosis and neural foraminal stenosis between standard and DL-reconstructed images were all statistically nonsignificant (p ≥ 0.05).

CONCLUSION

DL-based protocol reduced MRI acquisition time without degrading image quality and diagnostic performance of readers for degenerative lumbar spine diseases.

CLINICAL RELEVANCE STATEMENT

The deep learning (DL)-based reconstruction algorithm may be used to further accelerate spine MRI imaging to reduce patient discomfort and increase the cost efficiency of spine MRI imaging.

KEY POINTS

• By using deep learning (DL)-based reconstruction algorithm in combination with the accelerated MRI protocol, the average acquisition time was reduced by 32.3% as compared with the standard protocol. • DL-reconstructed images had similar or better quantitative/qualitative overall image quality and similar or better image quality for the delineation of most individual anatomical structures. • The average radiologist's sensitivity and specificity for the detection of major degenerative lumbar spine diseases, including central canal stenosis, neural foraminal stenosis, and disc herniation, on standard and DL-reconstructed images, were similar.

Reconstruction of shoulder MRI using deep learning and compressed sensing: a validation study on healthy volunteers

BACKGROUND

To investigate the potential of combining compressed sensing (CS) and deep learning (DL) for accelerated two-dimensional (2D) and three-dimensional (3D) magnetic resonance imaging (MRI) of the shoulder.

METHODS

Twenty healthy volunteers were examined using at 3-T scanner with a fat-saturated, coronal, 2D proton density-weighted sequence with four acceleration levels (2.3, 4, 6, and 8) and a 3D sequence with three acceleration levels (8, 10, and 13), all accelerated with CS and reconstructed using the conventional algorithm and a new DL-based algorithm (CS-AI). Subjective image quality was evaluated by two blinded readers using 6 criteria on a 5-point Likert scale (overall impression, artifacts, and delineation of the subscapularis tendon, bone, acromioclavicular joint, and glenoid labrum). Objective image quality was measured by calculating signal-to-noise-ratio, contrast-to-noise-ratio, and a structural similarity index measure. All reconstructions were compared to the clinical standard (CS 2D acceleration factor 2.3; CS 3D acceleration factor 8). Additionally, subjective and objective image quality were compared between CS and CS-AI with the same acceleration levels.

RESULTS

Both 2D and 3D sequences reconstructed with CS-AI achieved on average significantly better subjective and objective image quality compared to sequences reconstructed with CS with the same acceleration factor (p ≤ 0.011). Comparing CS-AI to the reference sequences showed that 4-fold acceleration for 2D sequences and 13-fold acceleration for 3D sequences without significant loss of quality (p ≥ 0.058).

CONCLUSIONS

For MRI of the shoulder at 3 T, a DL-based algorithm allowed additional acceleration of acquisition times compared to the conventional approach.

RELEVANCE STATEMENT

The combination of deep-learning and compressed sensing hold the potential for further scan time reduction in 2D and 3D imaging of the shoulder while providing overall better objective and subjective image quality compared to the conventional approach.

TRIAL REGISTRATION

DRKS00024156.

KEY POINTS

• Combination of compressed sensing and deep learning improved image quality and allows for significant acceleration of shoulder MRI. • Deep learning-based algorithm achieved better subjective and objective image quality than conventional compressed sensing. • For shoulder MRI at 3 T, 40% faster image acquisition for 2D sequences and 38% faster image acquisition for 3D sequences may be possible.

Synthetic T2-weighted fat sat based on a generative adversarial network shows potential for scan time reduction in spine imaging in a multicenter test dataset

OBJECTIVES

T2-weighted (w) fat sat (fs) sequences, which are important in spine MRI, require a significant amount of scan time. Generative adversarial networks (GANs) can generate synthetic T2-w fs images. We evaluated the potential of synthetic T2-w fs images by comparing them to their true counterpart regarding image and fat saturation quality, and diagnostic agreement in a heterogenous, multicenter dataset.

METHODS

A GAN was used to synthesize T2-w fs from T1- and non-fs T2-w. The training dataset comprised scans of 73 patients from two scanners, and the test dataset, scans of 101 patients from 38 multicenter scanners. Apparent signal- and contrast-to-noise ratios (aSNR/aCNR) were measured in true and synthetic T2-w fs. Two neuroradiologists graded image (5-point scale) and fat saturation quality (3-point scale). To evaluate whether the T2-w fs images are indistinguishable, a Turing test was performed by eleven neuroradiologists. Six pathologies were graded on the synthetic protocol (with synthetic T2-w fs) and the original protocol (with true T2-w fs) by the two neuroradiologists.

RESULTS

aSNR and aCNR were not significantly different between the synthetic and true T2-w fs images. Subjective image quality was graded higher for synthetic T2-w fs (p = 0.023). In the Turing test, synthetic and true T2-w fs could not be distinguished from each other. The intermethod agreement between synthetic and original protocol ranged from substantial to almost perfect agreement for the evaluated pathologies.

DISCUSSION

The synthetic T2-w fs might replace a physical T2-w fs. Our approach validated on a challenging, multicenter dataset is highly generalizable and allows for shorter scan protocols.

KEY POINTS

• Generative adversarial networks can be used to generate synthetic T2-weighted fat sat images from T1- and non-fat sat T2-weighted images of the spine. • The synthetic T2-weighted fat sat images might replace a physically acquired T2-weighted fat sat showing a better image quality and excellent diagnostic agreement with the true T2-weighted fat images. • The present approach validated on a challenging, multicenter dataset is highly generalizable and allows for significantly shorter scan protocols.

Evaluating prostate cancer bone metastasis using accelerated whole-body isotropic 3D T1-weighted Dixon MRI with compressed SENSE: a feasibility study

OBJECTIVES

The study aimed to assess the efficiency of whole-body high-resolution compressed sensing-sensitivity encoding isotropic T1-Weighted Dixon (CSI-T1W-Dixon) scans in evaluating bone metastasis.

METHODS

Forty-five high-risk prostate cancer patients with bone metastases were enrolled prospectively and underwent whole-body MRI sequences, which included the following: pre- and post-contrast CSI-T1W-Dixon and conventional multi-planar T1-Weighted Dixon (CMP-T1W-Dixon) (coronal, sagittal, and axial scans), short tau inversion recovery (STIR), and DWI. Comparison between the CMP-T1W-Dixon and CSI-T1W-Dixon images was done for the subjective image quality, the quantitative contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR). Furthermore, the diagnostic performance based on per-lesion and per-patient basis utilizing non-contrast T1-weighted (T1)/T1+ contrasted T1-weighted (T1C)/T1 + T1C + STIR + DWI sequences was compared between the CSI-T1W-Dixon and CMP-T1W-Dixon methods using reference standards (combining biopsy data and 6-month imaging follow-up).

RESULT

The CSI-T1W-Dixon images produced fewer image artifacts in the axial and coronal planes compared to the CMP-T1W-Dixon images. Also, the CSI-T1W-Dixon images provided better a CNR in fat-only images of all three planes and water-only images of the axial plane (p < 0.05). The CSI-T1W-Dixon showed a higher sensitivity than the CMP-T1W-Dixon techniques in analyzing T1-only images on a per-lesion basis (82.7% vs. 53.8% for sensitivity, p = 0.03). On a per-patient basis, no difference was found in the diagnostic capacity between the CSI-T1W-Dixon and CMP-T1W-Dixon sequences either alone or in combinations (p = 0.57-1).

CONCLUSION

High-resolution CSI-T1W-Dixon with higher image quality and diagnostic capacity can replace the CMP-T1W-Dixon method in evaluating bone metastasis in clinical practice.

KEY POINTS

• Compressed sensing isotropic acquisition for 3D T1-weighted Dixon images can improve the image quality with fewer artifacts compared to the anisotropic multiplanar acquisition. • Compressed sensing isotropic acquisition can save 67% of scanning time compared to anisotropic multiplanar acquisition. • Compressed sensing isotropic 3D T1-weighted Dixon images can offer better diagnostic performance with higher sensitivity compared to anisotropic multiplanar images.

Magnetic resonance shoulder imaging using deep learning-based algorithm

OBJECTIVE

To investigate the feasibility of deep learning-based MRI (DL-MRI) in its application in shoulder imaging and compare its performance with conventional MR imaging (non-DL-MRI).

METHODS

This retrospective study was approved by the local ethics committee. Seventy consecutive patients who had been examined with both DL-MRI and non-DL-MRI were enrolled for the image quality and lesion diagnosis comparison. Another 400 patients had been examined only with DL-MRI. Their images' quality was assessed by 20 radiologists using a satisfaction survey. The Kendall W test was performed to assess interobserver agreement. The Wilcoxon test was performed to compare the image quality. For lesion diagnosis, the interobserver and interstudy agreement were evaluated by kappa analysis.

RESULTS

The scan time of DL-MRI (6 min 1 s) was nearly 50% decreased compared with that of non-DL-MRI (11 min 25 s). The image quality was higher in both PDWI (4.85 ± 0.31 for DL, and 4.73 ± 0.29 for non-DL) and T2WI (4.95 ± 0.2 for DL, and 4.74 ± 0.41 for non-DL) of DL-MRI. Good interobserver agreement was found for the image quality of all the MR sequences on both DL-MRI (Kendall W: 0.588~0.902) and non-DL-MRI (Kendall W: 0751~0.865). Both the SNRs and |CNR| were significantly higher in PDWI and T2WI of DL-MRI. High interobserver and interstudy agreements for the lesions in non-DL-MRI and DL-MRI (kappa value = 0.913 to 1.000) were observed. The results of the image quality satisfaction survey in 400 patients receiving DL-MRI in the shoulder obtained 5 scores among all the radiologists.

CONCLUSION

Shoulder DL-MRI can greatly reduce the scan time, while improve imaging quality of PDWI and T2WI compared to non-DL-MRI.

KEY POINTS

• Shoulder 2D DL-MRI can greatly reduce the whole scan time and improve imaging quality of both PDWI and T2WI compared to conventional parallel MRI. • Shoulder 2D DL-MRI could be a clinical routine with greatly improved work efficiency in the future.

Comparison of Artificial Intelligence-Assisted Compressed Sensing (ACS) and Routine Two-Dimensional Sequences on Lumbar Spine Imaging

Purpose

To evaluate and compare the image quality and diagnostic accuracy of Artificial Intelligence-assisted Compressed Sensing (ACS) sequences for lumbar disease, as an acceleration method for MRI combining parallel imaging, half-Fourier, compressed sensing and neural network and routine 2D sequences for lumbar spine.

Methods

We collected data from 82 healthy subjects and 213 patients who used 2D ACS accelerated sequences to examine the lumbar spine while 95 healthy subjects and 234 patients used routine 2D sequences. Acquisitions included axial T2WI, sagittal T2WI, T1WI, and T2-fs sequences. All obtained images of these subjects were analyzed in the light of calculating image quality factors such as signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) for selected regions of interest. The lumbar image quality, artifacts and visibility of lesion structure were assessed by two radiologists independently. Differences between the evaluation values above were tested for statistical significance by the Wilcoxon signed-ranks test. Inter-observer agreements of image quality between two radiologists were measured using Cohen's kappa correlation coefficient.

Results

The ACS accelerated sequences not only reduced the scanning time by 18.9%, but also retained basically the same image quality as the routine 2D sequences in both healthy subjects and patients. Artifacts are less produced on ACS accelerated sequences compared with routine 2D sequences (p < 0.05). Apart from this, there were no significant differences in quantitative SNR, CNR measurements and qualitative scores within reviewing radiologists for each group (p > 0.05). Moreover, inter-observer agreement between two radiologists in scoring image quality was substantial consistently for ACS accelerated sequences and routine sequences (kappa = 0.622-0.986).

Conclusion

Compared with routine 2D sequences, ACS accelerated sequences allow for faster lumbar spine imaging with similar imaging quality and present reliable diagnostic accuracy, which can potentially improve workflow and patient comfort in musculoskeletal examinations.

Conventional and Deep-Learning-Based Image Reconstructions of Undersampled K-Space Data of the Lumbar Spine Using Compressed Sensing in MRI: A Comparative Study on 20 Subjects

Compressed sensing accelerates magnetic resonance imaging (MRI) acquisition by undersampling of the k-space. Yet, excessive undersampling impairs image quality when using conventional reconstruction techniques. Deep-learning-based reconstruction methods might allow for stronger undersampling and thus faster MRI scans without loss of crucial image quality. We compared imaging approaches using parallel imaging (SENSE), a combination of parallel imaging and compressed sensing (COMPRESSED SENSE, CS), and a combination of CS and a deep-learning-based reconstruction (CS AI) on raw k-space data acquired at different undersampling factors. 3D T2-weighted images of the lumbar spine were obtained from 20 volunteers, including a 3D sequence (standard SENSE), as provided by the manufacturer, as well as accelerated 3D sequences (undersampling factors 4.5, 8, and 11) reconstructed with CS and CS AI. Subjective rating was performed using a 5-point Likert scale to evaluate anatomical structures and overall image impression. Objective rating was performed using apparent signal-to-noise and contrast-to-noise ratio (aSNR and aCNR) as well as root mean square error (RMSE) and structural-similarity index (SSIM). The CS AI 4.5 sequence was subjectively rated better than the standard in several categories and deep-learning-based reconstructions were subjectively rated better than conventional reconstructions in several categories for acceleration factors 8 and 11. In the objective rating, only aSNR of the bone showed a significant tendency towards better results of the deep-learning-based reconstructions. We conclude that CS in combination with deep-learning-based image reconstruction allows for stronger undersampling of k-space data without loss of image quality, and thus has potential for further scan time reduction.

Practical Aspects of novel MRI Techniques in Neuroradiology: Part 2 - Acceleration Methods and Implications for Individual Regions

BACKGROUND

 Recently introduced MRI techniques facilitate accelerated examinations or increased resolution with the same duration. Further techniques offer homogeneous image quality in regions with anatomical transitions. The question arises whether and how these techniques can be adopted for routine diagnostic imaging.

METHODS

 Narrative review with an educational focus based on current literature research and practical experiences of different professions involved (physicians, MRI technologists/radiographers, physics/biomedical engineering). Different hardware manufacturers are considered.

RESULTS AND CONCLUSIONS

 Compressed sensing and simultaneous multi-slice imaging are novel acceleration techniques with different yet complimentary applications. They do not suffer from classical signal-to-noise-ratio penalties. Combining 3 D and acceleration techniques facilitates new broader examination protocols, particularly for clinical brain imaging. In further regions of the nervous systems mainly specific applications appear to benefit from recent technological improvements.

KEY POINTS

  · New acceleration techniques allow for faster or higher resolution examinations.. · New brain imaging approaches have evolved, including more universal examination protocols.. · Other regions of the nervous system are dominated by targeted applications of recently introduced MRI techniques..

CITATION FORMAT

· Sundermann B, Billebaut B, Bauer J et al. Practical Aspects of novel MRI Techniques in Neuroradiology: Part 2 - Acceleration Methods and Implications for Individual Regions. Fortschr Röntgenstr 2022; DOI: 10.1055/a-1800-8789.

Spiral gradient echo versus cartesian turbo spin echo imaging for sagittal contrast-enhanced fat-suppressed T1 weighted spine MRI: an inter-individual comparison study

OBJECTIVES

To compare a novel 3D spiral gradient echo (GRE) sequence with a conventional 2D cartesian turbo spin echo (TSE) sequence for sagittal contrast-enhanced (CE) fat-suppressed (FS) T1 weighted (T1W) spine MRI.

METHODS

In this inter-individual comparison study, 128 patients prospectively underwent sagittal CE FS T1W spine MRI with either a 2D cartesian TSE ("TSE", 285 s, 64 patients) or a 3D spiral GRE sequence ("Spiral", 93 s, 64 patients). Between both groups, patients were matched in terms of anatomical region (cervical/thoracic/lumbar spine and sacrum). Three readers used 4-point Likert scales to assess images qualitatively in terms of overall image quality, presence of artifacts, spinal cord visualization, lesion conspicuity and quality of fat suppression.

RESULTS

Spiral achieved a 67.4% scan time reduction compared to TSE. Interreader agreement was high (alpha=0.868-1). Overall image quality (4;[3,4] vs 3;[3,4], p<0.001 - p=0.002 for all readers), presence of artifacts (4;[3,4] vs 3;[3,4] p=0.027 - p=0.046 for all readers), spinal cord visualization (4;[4,4] vs 4;[3,4], p<0.001 for all readers), lesion conspicuity (4;[4,4] vs 4;[4,4], p=0.016 for all readers) and quality of fat suppression (4;[4,4] vs 4;[4,4], p=0.027 - p=0.033 for all readers), were all deemed significantly improved by all three readers on Spiral images as compared to TSE images.

CONCLUSION

We demonstrate the feasibility of a novel 3D spiral GRE sequence for improved and rapid sagittal CE FS T1W spine MRI.

ADVANCES IN KNOWLEDGE

A 3D spiral GRE sequence allows for improved sagittal CE FS T1W spine MRI at very short scan times.

Imaging of the extracranial internal carotid artery in acute ischemic stroke: assessment of stenosis, plaques, and image quality using relaxation-enhanced angiography without contrast and triggering (REACT)

BACKGROUND

In stroke magnetic resonance imaging (MRI), contrast-enhanced magnetic resonance angiography (CE-MRA) is the clinical standard to depict extracranial arteries but native MRA techniques are of increased interest to facilitate clinical practice. The purpose of this study was to assess the detection of extracranial internal carotid artery (ICA) stenosis and plaques as well as the image quality of cervical carotid arteries between a novel flow-independent relaxation-enhanced angiography without contrast and triggering (REACT) sequence and CE-MRA in acute ischemic stroke (AIS).

METHODS

In this retrospective, single-center study, 105 consecutive patients (65.27±18.74 years, 63 males) were included, who received a standard stroke protocol at 3T in clinical routine including Compressed SENSE (CS) accelerated (factor 4) 3D isotropic REACT (fixed scan time: 02:46 min) and CS accelerated (factor 6) 3D isotropic CE-MRA. Three radiologists independently assessed scans for the presence of extracranial ICA stenosis and plaques (including hyper-/hypointense signal) with concomitant diagnostic confidence using 3-point scales (3= excellent). Vessel quality, artifacts, and image noise of extracranial carotid arteries were subjectively scored on 5-point scales (5= excellent/none). Wilcoxon tests were used for statistical comparison.

RESULTS

Considering CE-MRA as the standard of reference, REACT provided a sensitivity of 89.8% and specificity of 95.2% for any and of 93.5% and 95.8% for clinically relevant (≥50%) extracranial ICA stenosis and yielded a to CE-MRA comparable diagnostic confidence [mean ± standard deviation (SD), median (interquartile range): 2.8±0.5, 3 (3-3) vs. 2.7±0.5, 3 (2-3), P=0.03]. Using REACT, readers detected more plaques overall (n=57.3 vs. 47.7, P<0.001) and plaques of hyperintense signal (n=12.3 vs. 5.7, P=0.02) with higher diagnostic confidence [2.8±0.5, 3 (3-3) vs. 2.6±0.7, 3 (2-3), P<0.001] than CE-MRA. After analyzing a total of 1,260 segments, the vessel quality of all segments combined [4.61±0.66 vs. 4.58±0.68, 5 (4-5) vs. 5 (4-5), P=0.0299] and artifacts [4.51±0.70 vs. 4.44±0.73, 5 (4-5) vs. 5 (4-5), P>0.05] were comparable between the sequences with REACT showing a lower image noise [4.43±0.67 vs. 4.25±0.71, 5 (4-5) vs. 4 (4-5), P<0.001].

CONCLUSIONS

Without the use of gadolinium-based contrast agents or triggering, REACT provides a high sensitivity and specificity for extracranial ICA stenosis and a potential improved depiction of adjacent plaques while yielding to CE-MRA comparable vessel quality in a large patient cohort with AIS.

Comparison of utility of deep learning reconstruction on 3D MRCPs obtained with three different k-space data acquisitions in patients with IPMN

OBJECTIVE

To compare the utility of deep learning reconstruction (DLR) for improving acquisition time, image quality, and intraductal papillary mucinous neoplasm (IPMN) evaluation for 3D MRCP obtained with parallel imaging (PI), multiple k-space data acquisition for each repetition time (TR) technique (Fast 3D mode multiple: Fast 3Dm) and compressed sensing (CS) with PI.

MATERIALS AND METHODS

A total of 32 IPMN patients who had undergone 3D MRCPs obtained with PI, Fast 3Dm, and CS with PI and reconstructed with and without DLR were retrospectively included in this study. Acquisition time, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) obtained with all protocols were compared using Tukey's HSD test. Results of endoscopic ultrasound, ERCP, surgery, or pathological examination were determined as standard reference, and distribution classifications were compared among all 3D MRCP protocols by McNemar's test.

RESULTS

Acquisition times of Fast 3Dm and CS with PI with and without DLR were significantly shorter than those of PI with and without DLR (p < 0.05). Each MRCP sequence with DLR showed significantly higher SNRs and CNRs than those without DLR (p < 0.05). IPMN distribution accuracy of PI with and without DLR and Fast 3Dm with DLR was significantly higher than that of Fast 3Dm without DLR and CS with PI without DLR (p < 0.05).

CONCLUSION

DLR is useful for improving image quality and IPMN evaluation capability on 3D MRCP obtained with PI, Fast 3Dm, or CS with PI. Moreover, Fast 3Dm and CS with PI may play as substitution to PI for MRCP in patients with IPMN.

KEY POINTS

• Mean examination times of multiple k-space data acquisitions for each TR and compressed sensing with parallel imaging were significantly shorter than that of parallel imaging (p < 0.0001). • When comparing image quality of 3D MRCPs with and without deep learning reconstruction, deep learning reconstruction significantly improved signal-to-noise ratio and contrast-to-noise ratio (p < 0.05). • IPMN distribution accuracies of parallel imaging with and without deep learning reconstruction (with vs. without: 88.0% vs. 88.0%) and multiple k-space data acquisitions for each TR with deep learning reconstruction (86.0%) were significantly higher than those of others (p < 0.05).

An Investigation of 2D Spine Magnetic Resonance Imaging (MRI) with Compressed Sensing (CS)

OBJECTIVE

To investigate the feasibility of compressed sensing MRI (CS-MRI) in the application of 2D spinal imaging and compare its performance with conventional MR imaging (non-CS-MRI).

METHODS

The CS imaging protocol was optimized on 5 volunteers. Non-CS-MRI and CS-MRI of 2D sagittal T1 weighted imaging (WI), Sag T2WI, and axial T2WI were performed for 71 patients (22 cervical, 8 thoracic, 41 lumbar MRI). Paired t tests were conducted to compare the total scan time. Three radiologists assessed image quality and lesion diagnosis independently. A Kendall W test was performed to assess interobserver agreement of the image quality scores and lesion diagnosis between readers. A nonparametric test (Wilcoxon test) was performed to compare the image quality. For lesion diagnosis, the interobserver and interstudy agreements were evaluated by kappa analysis. Paired t tests were conducted for SNR and CNR comparison.

RESULTS

The mean scan time for spine CS-MRI (4 min 28.7 s ± 34.6 s) was significantly shorter than that with non-CS-MRI (7 min 21.3 s ± 38.7 s, t =  - 47.464, P < 0.0001). CS-MRI achieved higher SNR and CNR than Non-CS-MRI in image quality assessment. Interobserver agreements of lesion diagnosis were excellent between non-CS-MRI and CS-MRI (kappa value from 0.913 to 1.000, P < 0.001). Interstudy agreements of lesion assessments were also excellent (kappa value = 1.000, with P < 0.001).

CONCLUSION

CS-MRI spine imaging can significantly reduce the scan time, while maintaining comparable imaging quality to non-CS-MRI.

Acceleration of pCASL-Based Cerebral 4D MR Angiography Using Compressed SENSE: A Comparison With SENSE

Objectives

The objectives of this study were to accelerate the non-contrast-enhanced four-dimensional magnetic resonance angiography (4D MRA) based on pseudocontinuous arterial spin labeling combined with the Keyhole and View-sharing (4D-PACK) procedure using the Compressed SENSE (C-SENSE) and to improve intracranial vasculopathy evaluations for clinical purposes.

Methods

4D-PACK acquisition with different C-SENSE and SENSE acceleration factors was performed on 29 healthy volunteers and six patients by means of a 3.0 T MR system. Two radiologists used a 4-grade scale to qualitatively assess the vessel visualization of the middle cerebral artery (MCA) and used a 5-grade scale to qualitatively examine the image quality of 4D-PACK axial source images. Interobserver agreement was assessed by determining the weighted kappa statistic. The contrast-to-noise ratio (CNR) and arterial transmit time (ATT) were calculated in four segments of the MCA. The repeated measures one-way ANOVA for CNR and the Friedman test for source images and vessel visualization were used to analyse the differences in five sequences.

Results

(1) At the M4 segment, C-SENSE5 acquisition (scores, 2.72 ± 0.53) and C-SENSE6.5 (scores, 2.55 ± 0.57) provided similar vessel visualization compared with SENSE4.5 (scores, 2.72 ± 0.46); however, C-SENSE8 (scores, 1.79 ± 0.49) and C-SENSE10 (scores, 1.52 ± 0.51) had lower scores (P < 0.050). (2) The source image quality of C-SENSE5 (scores, 4.55 ± 0.51), C-SENSE6.5 (scores, 4.03 ± 0.33), and C-SENSE8 (scores, 3.48 ± 0.51) acquisition was higher than that of SENSE4.5 (scores, 3.07 ± 0.26) (P < 0.001). (3) CNRs of different MCA segments for C-SENSE5 and C-SENSE6.5 acquisitions were not significantly different compared with that of SENSE4.5 acquisition. However, the CNRs were significantly lower for C-SENSE8 (M1: 45.85 ± 13.91, M2: 27.08 ± 9.92, M4: 7.93 ± 4.49) and C-SENSE10 (M1: 37.94 ± 9.92, M2: 23.51 ± 9.0, M4: 6.78 ± 4.12) than for SENSE4.5 (M1: 55.49 ± 13.39, M2: 36.94 ± 11.02, M4: 10.18 ± 5.15) in each corresponding segment (P < 0.050). ATTs in all MCA segments within different accelerating C-SENSE factors were obviously correlated with SENSE4.5.

Conclusion

C-SENSE6.5 acquisition could be used to evaluate both the intracranial macrovascular and distal arteries, which could reduce the acquisition time by 18% (5 min 5 s) compared with SENSE4.5. Moreover, C-SENSE8 acquisition (37% acceleration, 3 min 54 s) could be used for routine screening and clinical diagnosis of intracranial macrovascular disease with balanced image quality.

High-Resolution 3D versus Standard-Resolution 2D T2-Weighted Turbo Spin Echo MRI for the Assessment of Lumbar Nerve Root Compromise

Radiculopathy can be caused by nerve root irritation and nerve root compression at the level of the lateral recess or at the level of the intervertebral foramen. T2-weighted (T2w) MRI is considered essential to evaluate the nerve root and its course, starting at the lateral recess through the intervertebral foramen to the extraforaminal space. With the introduction of novel MRI acceleration techniques such as compressed SENSE, standard-resolution 2D T2w turbo spin echo (TSE) sequences with a slice-thickness of 3–4 mm can be replaced with high-resolution isotropic 3D T2w TSE sequences with sub-millimeter resolution without prolonging scan time. With high-resolution 3D MRI, the course of the nerve root can be visualized more precisely due to a detailed depiction of the anatomical situation and less partial volume effects, potentially allowing for a better detection of nerve root compromise. In this intra-individual comparison study, 55 patients with symptomatic unilateral singular nerve root radiculopathy underwent MRI with both 2D standard- and 3D high-resolution T2w TSE MRI sequences. Two readers graded the degree of lumbar lateral recess stenosis and lumbar foraminal stenosis twice on both image sets using previously validated grading systems in an effort to quantify the inter-readout and inter-sequence agreement of scores. Inter-readout agreement was high for both grading systems and for 2D and 3D imaging (Kappa = 0.823–0.945). Inter-sequence agreement was moderate for both lumbar lateral recess stenosis (Kappa = 0.55–0.577) and lumbar foraminal stenosis (Kappa = 0.543–0.572). The percentage of high degree stenosis with nerve root deformity increased from 16.4%/9.8% to 41.8–43.6%/34.1% from 2D to 3D images for lateral recess stenosis/foraminal stenosis, respectively. Therefore, we show that while inter-readout agreement of grading systems is high for both standard- and high-resolution imaging, the latter outperforms standard-resolution imaging for the visualization of lumbar nerve root compromise.

Using the Compressed Sensing Technique for Lumbar Vertebrae Imaging: Comparison with Conventional Parallel Imaging

OBJECTIVE

To compare conventional sensitivity encoding turbo spin-echo (SENSE-TSE) with compressed sensing plus SENSE turbo spin-echo (CS-TSE) in lumbar vertebrae magnetic resonance imaging (MRI).

METHODS

This retrospective study of lumbar vertebrae MRI included 600 patients; 300 patients received SENSE-TSE and 300 patients received CS-TSE. The SENSE acceleration factor was 1.4 for T1WI, 1.7 for T2WI, and 1.7 for PDWI. The CS total acceleration factor was 2.4, 3.6, 4.0, and 4.0 for T1WI, T2WI, PDWI sagittal, and T2WI transverse, respectively. The image quality of each MRI sequence was evaluated objectively by the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) and subjectively on a five-point scale. Two radiologists independently reviewed the MRI sequences of the 300 patients receiving CS-TSE, and their diagnostic consistency was evaluated. The degree of intervertebral foraminal stenosis and nerve root compression was assessed using the T1WI sagittal and T2WI transverse images.

RESULTS

The scan time was reduced from 7 min 28 s to 4 min 26 s with CS-TSE. The median score of nerve root image quality was 5 (p > 0.05). The diagnostic consistency using CS-TSE images between the two radiologists was high for diagnosing lumbar diseases (κ > 0.75) and for evaluating the degree of lumbar foraminal stenosis and nerve root compression (κ = 0.882). No differences between SENSE-TSE and CS-TSE were observed for sensitivity, specificity, positive predictive value, or negative predictive value.

CONCLUSION

CS-TSE has the potential for diagnosing lumbar vertebrae and disc disorders.

Diffusion-weighted imaging of the abdomen using echo planar imaging with compressed SENSE: Feasibility, image quality, and ADC value evaluation

OBJECTIVE

To evaluate the feasibility, image quality, and apparent diffusion coefficient (ADC) values of diffusion-weighted imaging (DWI) using echo planar imaging (EPI) with Compressed SENSE (EPICS-DWI) of the abdomen and to compare them with conventional single-shot EPI with parallel imaging (PI) technique (PI-DWI).

MATERIALS AND METHODS

This prospective study included 46 participants with known or suspected upper abdominal diseases (19 men and 27 women, mean age, 68 years) who underwent MRI. DWI acquisition was performed using free-breathing two-dimensional fat-suppressed PI-DWI and EPICS-DWI with SENSE or compressed sensing (CS) factor, 3.0. Moreover, image noise and contour of liver and pancreas were qualitatively evaluated using a five-point scale. The mean ADC value and standard deviation (SD) of the liver, pancreas, and spleen were measured, and the coefficient of variation (CV) was calculated. Qualitative and quantitative parameters were compared between PI-DWI and EPICS-DWI using the Wilcoxon test.

RESULTS

The mean image quality scores for image noise and contour of liver and pancreas were higher in EPICS-DWI compared with PI-DWI (P < 0.0001). Moreover, the mean ADC values of the liver and pancreas were higher in EPICS-DWI compared with PI-DWI (P < 0.0001), but that of spleen was not significantly different. The mean SD and CV of the liver, pancreas, and spleen were lower in EPICS-DWI compared with PI-DWI (P < 0.0001-0.032).

CONCLUSION

EPICS-DWI could be feasible in MRI of the abdomen and significantly improve image quality compared with PI-DWI in aggressive setting. ADC value measurements were higher in EPICS-DWI compared with PI-DWI.

Introduction and reproducibility of an updated practical grading system for lumbar foraminal stenosis based on high-resolution MR imaging

In this paper we sought to develop and assess the reproducibility of an updated 6-point grading system for lumbar foraminal stenosis based on the widely used Lee classification that more accurately describes lumbar foraminal stenosis as seen on high-resolution MRI. Grade A indicates absence of foraminal stenosis. Grades B, C, D and E indicate presence of foraminal stenosis with contact of the nerve root with surrounding anatomical structures (on one, two, three or four sides for B, C, D and E respectively) yet without morphological change of the nerve root. To each grade, a number code indicating the location of contact between the nerve root and surrounding anatomical structure(s) is appended. 1, 2, 3 and 4 indicate contact of the nerve root at superior, posterior, inferior and anterior position of the borders of the lumbar foramen. Grade F indicates presence of foraminal stenosis with morphological change of the nerve root. Three readers graded the lumbar foramina of 101 consecutive patients using high-resolution T2w (and T1w) MR images with a spatial resolution of beyond 0.5 mm³. Interreader agreement was excellent (Cohen’s Kappa = 0.866–1). Importantly, 30.6%/31.6%/32.2% (reader 1/reader 2/ reader 3) of foramina were assigned grades that did not appear in the original Lee grading system (grades B and D). The readers found no foramen that could not be described accurately with the updated grading system. Thus, an updated 6-point grading system for lumbar foraminal stenosis is reproducible and comprehensively describes lumbar foraminal stenosis as seen on high-resolution MRI.

Speeding up the clinical routine: Compressed sensing for 2D imaging of lumbar spine disc herniation

PURPOSE

Increasing economic pressure and patient demands for comfort require an ever-increasing acceleration of scan times without compromising diagnostic certainty. This study tested the new acceleration technique Compressed SENSE (CS-SENSE) as well as different reconstruction methods for the lumbar spine.

METHODS

In this prospective study, 10 volunteers and 14 patients with lumbar disc herniation were scanned using a sagittal 2D T2 turbo spin echo (TSE) sequence applying different acceleration factors of SENSE and CS-SENSE. Gradient echo (GRE), autocalibration (CS-Auto) and TSE prescans were tested for reconstruction. Images were analysed by two readers regarding anatomical delineation, diagnostic certainty (for patients only) and image quality as well as objectively calculating the root mean square error (RMSE), structural similarity index (SSIM), SNR and CNR. The Friedman test and Chi-squared were used for ordinal, ANOVA for repeated measurements and Tukey Kramer test for continuous data. Cohen's kappawas calculated for interreader reliability.

RESULTS

CS-SENSE outperformed SENSE and CS-Auto regarding RMSE (e.g. CS-SENSE 1.5: 43.03 ± 11.64 versus SENSE 1.5: 80.41 ± 17.66; p = 0.0038) and SSIM as well as in the subjective rating for CS-SENSE 3 TSE. In the patient setting image quality was unchanged in all subjective criteria up to CS-SENSE 3 TSE (all p > 0.05) compared to standard T2 with 43 % less scan time while the GRE prescan only allowed a reduction of 32 %.

CONCLUSION

Combining a TSE prescan with CS-SENSE enables significant scan time reductions with unchanged ratings for lumbar spine disc herniation making this superior to the currently used SENSE acceleration or GRE reconstructions.

Acceleration of Brain TOF-MRA with Compressed Sensitivity Encoding: A Multicenter Clinical Study

BACKGROUND AND PURPOSE

The clinical practice of three-dimensional TOF-MRA, despite its capability in brain artery assessment, has been hampered by the relatively long scan time, while recent developments in fast imaging techniques with random undersampling has shed light on an improved balance between image quality and imaging speed. Our aim was to evaluate the effectiveness of TOF-MRA accelerated by compressed sensitivity encoding and to identify the optimal acceleration factors for routine clinical use.

MATERIALS AND METHODS

One hundred subjects, enrolled at 5 centers, underwent 8 brain TOF-MRA sequences: 5 sequences using compressed sensitivity encoding with acceleration factors of 2, 4, 6, 8, and 10 (CS2, CS4, CS6, CS8, and CS10), 2 using sensitivity encoding with factors of 2 and 4 (SF2 and SF4), and 1 without acceleration as a reference sequence (RS). Five large arteries, 6 medium arteries, and 6 small arteries were evaluated quantitatively (reconstructed signal intensity, structural similarity, contrast ratio) and qualitatively (scores on arteries, artifacts, overall image quality, and diagnostic confidence for aneurysm and stenosis). Comparisons were performed among the 8 sequences.

RESULTS

The quantitative measurements showed that the reconstructed signal intensities of the assessed arteries and the structural similarity consistently decreased as the compressed sensitivity encoding acceleration factor increased, and no significant difference was found for the contrast ratios in pair-wise comparisons among SF2, CS2, and CS4. Qualitative evaluations showed no significant difference in pair-wise comparisons among RS, SF2, and CS2 (P > .05). The visualization of all the assessed arteries was acceptable for CS2 and CS4, while 2 small arteries in images of CS6 were not reliably displayed, and the visualization of large arteries was acceptable in images of CS8 and CS10.

CONCLUSIONS

CS4 is recommended for routine brain TOF-MRA with balanced image quality and acquisition time; CS6, for examinations when small arteries are not evaluated; and CS10, for fast visualization of large arteries.

Optimal acceleration factor for image acquisition in turbo spin echo: diffusion-weighted imaging with compressed sensing

In this study, the change in the image quality and apparent diffusion coefficient (ADC) with increase in the acceleration factor (AF) was analyzed and the most optimal AF was determined to reduce the scan time while preserving the image quality. The AF was changed from 2 to 20 in the MR acquisitions. The similarities between the accelerated and reference images were determined based on the structural similarity (SSIM) index for DWI image and coefficient of variation (%CV) for ADC. The SSIM index decreased significantly when the AF ≥ 8 compared with when the AF = 2 (p < 0.05). In the reference image, the %CV of the ADC increased significantly when the AF ≥ 10 (p < 0.01). In conclusion, a remarkable decrease in the image quality and ADC was observed when the AF was > 8. Thus, an AF < 8 would be optimal for reducing the scan time while preserving the image quality.

Compressed sensing and parallel imaging accelerated T2 FSE sequence for head and neck MR imaging: Comparison of its utility in routine clinical practice

PURPOSE

To directly compare the capability of compressed sensing (CS) and parallel imaging (PI) accelerated T2 FSE (Fast Spin Echo) sequence with PI for head and neck MR imaging.

METHODS

Thirty consecutive patients with various head and neck diseases (15 men and 15 women, mean age 53 ± 22 years) underwent MR imaging by PI with CS and by PI. Reduction factors were as follows: PI with CS, 3 and PI, 1.5. Examination times for PI with CS and PI were all recorded. For quantitative image quality assessment, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. For qualitative assessment, two investigators assessed overall image quality, artifacts and diagnostic confidence level using a 5-point scoring system, and final scores were determined by consensus of two readers. Mean examination time and all indexes were compared by means of paired t-test and Wilcoxon signed-rank test. Inter-observer agreement for each qualitative index was assessed in terms of kappa statistics.

RESULTS

Mean examination time for PI with CS (83.5 ± 11.0 s) was significantly shorter than that for PI (173.0 ± 54.4 s, p < 0.0001). SNR and CNR of PI with CS were significantly better than those with PI (mean SNR; 11.2 ± 3.6 vs 8.9 ± 2.6, median of CNR; 7.4 vs. 6.1, p < 0.0001). All inter-observer agreements were assessed as significant and substantial (0.62 < κ < 0.81).

CONCLUSION

PI with CS accelerated T2 weighted sequence performs equally well or even slightly better than its PI accelerated, conventional counterpart at reduced scan times in the context of head and neck MR imaging.

Clinical application of free-breathing 3D whole heart late gadolinium enhancement cardiovascular magnetic resonance with high isotropic spatial resolution using Compressed SENSE

BACKGROUND

Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) represents the gold standard for assessment of myocardial viability. The purpose of this study was to investigate the clinical potential of Compressed SENSE (factor 5) accelerated free-breathing three-dimensional (3D) whole heart LGE with high isotropic spatial resolution (1.4 mm3 acquired voxel size) compared to standard breath-hold LGE imaging.

METHODS

This was a retrospective, single-center study of 70 consecutive patients (45.8 ± 18.1 years, 27 females; February-November 2019), who were referred for assessment of left ventricular myocardial viability and received free-breathing and breath-hold LGE sequences at 1.5 T in clinical routine. Two radiologists independently evaluated global and segmental LGE in terms of localization and transmural extent. Readers scored scans regarding image quality (IQ), artifacts, and diagnostic confidence (DC) using 5-point scales (1 non-diagnostic-5 excellent/none). Effects of heart rate and body mass index (BMI) on IQ, artifacts, and DC were evaluated with ordinal logistic regression analysis.

RESULTS

Global LGE (n = 33) was identical for both techniques. Using free-breathing LGE (average scan time: 04:33 ± 01:17 min), readers detected more hyperenhanced lesions (28.2% vs. 23.5%, P < .05) compared to breath-hold LGE (05:15 ± 01:23 min, P = .0104), pronounced at subepicardial localization and for 1-50% of transmural extent. For free-breathing LGE, readers graded scans with good/excellent IQ in 80.0%, with low-impact/no artifacts in 78.6%, and with good/high DC in 82.1% of cases. Elevated BMI was associated with increased artifacts (P = .0012) and decreased IQ (P = .0237). Increased heart rate negatively influenced artifacts (P = .0013) and DC (P = .0479) whereas IQ (P = .3025) was unimpaired.

CONCLUSIONS

In a clinical setting, free-breathing Compressed SENSE accelerated 3D high isotropic spatial resolution whole heart LGE provides good to excellent image quality in 80% of scans independent of heart rate while enabling improved depiction of small and particularly non-ischemic hyperenhanced lesions in a shorter scan time than standard breath-hold LGE.

Evaluation of an accelerated 3D modulated flip-angle technique in refocused imaging with an extended echo-train sequence with compressed sensing for imaging of the knee: comparison with routine 2D MRI sequences

AIM

To accelerate the acquisition of high-resolution magnetic resonance imaging (MRI) by using the three-dimensional (3D) matrix sequence with compressed sensing and to compare it with conventional two-dimensional (2D) proton-density (PD) and fast spin-echo (FSE) sequences.

MATERIALS AND METHODS

3D matrix, 2D FSE, and PD sequences were acquired from 68 participants using 3 T magnetic resonance imaging (MRI). Two radiologists scored image quality independently on a four-point scale. The structural similarity index (SSIM), and signal- (SNRs) and contrast-to-noise ratios (CNRs) of different anatomical structures of the knee were assessed and compared between sequences using Wilcoxon signed-rank tests and Cohen's kappa.

RESULTS

The median acquisition time reduction was 44.5%. There was a substantial to perfect agreement for the rating between the 3D matrix FSE and 2D FSE or PD sequences when evaluating cartilage, subchondral bone, and ligaments (κ=0.783-872, p>0.05). The mean SSIM values between the 3D matrix FSE and 2D FSE, and between the 3D matrix PD and 2D PD sequences was 0.994 and 0.971, respectively, which are acceptable. No significant differences were found in SNR between the 3D matrix FSE and 2D FSE, and between the 3D matrix PD and 2D PD sequences, even though the SNR appeared to be higher on routine 2D sequences. The CNR of subchondral bone-meniscus, subchondral bone-joint fluid, and meniscus-joint fluid did not differentiate significantly between the 3D matrix sequence and routine 2D sequences.

CONCLUSIONS

3D matrix reduced the acquisition time in routine clinical knee MRI without the loss in image quality, SNR, and CNR.

Compressed sensing and deep learning reconstruction for women's pelvic MRI denoising: Utility for improving image quality and examination time in routine clinical practice

PURPOSE

To demonstrate the utility of compressed sensing with parallel imaging (Compressed SPEEDER) and AiCE compared with that of conventional parallel imaging (SPEEDER) for shortening examination time and improving image quality of women's pelvic MRI.

METHOD

Thirty consecutive patients with women's pelvic diseases (mean age 50 years) underwent T2-weighted imaging using Compressed SPEEDER as well as conventional SPEEDER reconstructed with and without AiCE. The examination times were recorded, and signal-to-noise ratio (SNR) was calculated for every patient. Moreover, overall image quality was assessed using a 5-point scoring system, and final scores for all patients were determined by consensus of two readers. Mean examination time, SNR and overall image quality were compared among the four data sets by Wilcoxon signed-rank test.

RESULTS

Examination times for Compressed SPEEDER with and without AiCE were significantly shorter than those for conventional SPEEDER with and without AiCE (with AiCE: p < 0.0001, without AiCE: p < 0.0001). SNR of Compressed SPEEDER and of SPEEDER with AiCE was significantly superior to that of Compressed SPEEDER without AiCE (vs. Compressed SPEEDER, p = 0.01; vs. SPEEDER, p = 0.009). Overall image quality of Compressed SPEEDER with AiCE and of SPEEDER with and without AiCE was significantly higher than that of Compressed SPEEDER without AiCE (vs. Compressed SPEEDER with AiCE, p < 0.0001; vs. SPEEDER with AiCE, p < 0.0001; SPEEDER without AiCE, p = 0.0003).

CONCLUSION

Image quality and shorten examination time for T2-weighted imaging in women's pelvic MRI can be significantly improved by using Compressed SPEEDER with AiCE in comparison with conventional SPEEDER, although other sequences were not tested.

Relaxation-Enhanced Angiography Without Contrast and Triggering (REACT) for Fast Imaging of Extracranial Arteries in Acute Ischemic Stroke at 3 T

Purpose

To evaluate a novel flow-independent 3D isotropic REACT sequence compared with CE-MRA for the imaging of extracranial arteries in acute ischemic stroke (AIS).

Methods

This was a retrospective study of 35 patients who underwent a stroke protocol at 3 T including REACT (fixed scan time: 2:46 min) and CE-MRA of the extracranial arteries. Three radiologists evaluated scans regarding vessel delineation, signal, and contrast and assessed overall image noise and artifacts using 5-point scales (5: excellent delineation/no artifacts). Apparent signal- and contrast-to-noise ratios (aSNR/aCNR) were measured for the common carotid artery (CCA), internal carotid artery (ICA, C1 segment), and vertebral artery (V2 segment). Two radiologists graded the degree of proximal ICA stenosis.

Results

Compared to REACT, CE-MRA showed better delineation for the CCA and ICA (C1 and C2 segments) (median 5, range 2–5 vs. 4, range 3–5; P < 0.05). For the ICA (C1 and C2 segments), REACT provided a higher signal (5, range 3–5; P < 0.05/4.5, range 3–5; P > 0.05 vs. 4, range 2–5) and contrast (5, range 3–5 vs. 4, range 2–5; P > 0.05) than CE-MRA. The remaining segments of the blood-supplying vessels showed equal medians. There was no significant difference regarding artifacts, whereas REACT provided significantly lower image noise (4, range 3–5 vs. 4 range 2–5; P < 0.05) with a higher aSNR (P < 0.05) and aCNR (P < 0.05) for all vessels combined. For clinically relevant (≥50%) ICA stenosis, REACT achieved a detection sensitivity of 93.75% and a specificity of 100%.

Conclusion

Given its fast acquisition, comparable image quality to CE-MRA and high sensitivity and specificity for the detection of ICA stenosis, REACT was proven to be a clinically applicable method to assess extracranial arteries in AIS.

Electronic supplementary material

The online version of this article (10.1007/s00062-020-00963-6) contains supplementary material, which is available to authorized users.

Improving Quantitative Magnetic Resonance Imaging Using Deep Learning

Deep learning methods have shown promising results for accelerating quantitative musculoskeletal (MSK) magnetic resonance imaging (MRI) for T2 and T1ρ relaxometry. These methods have been shown to improve musculoskeletal tissue segmentation on parametric maps, allowing efficient and accurate T2 and T1ρ relaxometry analysis for monitoring and predicting MSK diseases. Deep learning methods have shown promising results for disease detection on quantitative MRI with diagnostic performance superior to conventional machine-learning methods for identifying knee osteoarthritis.

Diffusion tensor magnetic resonance imaging of the postoperative spine with metallic implants

There has been a growing need to understand the mechanism of development of acute spinal cord injury (SCI) and to optimize treatment. The paramagnetic nature of metallic implants has hampered the application of diffusion tensor imaging (DTI) in postsurgical SCI monitoring. We describe here a successful implementation of spinal DTI in postsurgical SCI patients. Data were acquired using a single-shot turbo-spin-echo sequence, where an extra gradient is applied before the refocusing pulse train to eliminate contributions from the non-Carr-Purcell-Meiboom-Gill components following a diffusion preparation block where a single-spin echo scheme is deployed. The DTI images were acquired in axial orientation with a 2 x 2 x 4 mm³ resolution and a total of 18 slices. Diffusion gradients were applied in six directions with b values of 0 and 600 seconds/mm² . The whole scan took ~10 minutes. The sequence was compared with SENSE-DW-EPI and ZOOM-DW-EPI on a phantom, eight patients with either anterior or posterior titanium alloy implants, and a pork loin with a similar implant. The protocol resulted in dramatically reduced geometric distortions compared with routine imaging sequences, however, the SNR efficiency was compromised. The spinal cord signal displacement was 0.68±1.00 mm (mean±SD, n = 8) for the proposed protocol, and 5.14±3.07 and 2.82±1.60 mm for the SENSE-DW-EPI and ZOOM-DW-EPI sequences, respectively. Fiber tracking was achieved in the presence of implants, which in one case was accompanied by central spinal cord caviation. Mathematical analysis concluded that the proposed protocol would be generally applicable in the spinal cord when the titanium alloy implant is ~15 mm away (<0.5 kHz B₀ field drift). The protocol described is capable of DTI in postsurgery SCI patients with metallic implants at sufficient resolution and SNR.

Magnetic Resonance Imaging of the Brain Using Compressed Sensing - Quality Assessment in Daily Clinical Routine

PURPOSE

To assess the effect of compressed sensing (CS) on image quality and acquisition speed in routine brain magnetic resonance imaging (MRI).

METHODS

During a 2-month implementation period of CS, two senior neuroradiologists, one MRI physicist and one application specialist optimized the CS acceleration factor to reduce scan time and improve spatial resolution, while maintaining image quality. Afterwards, two neuroradiologists independently scored image quality on a 5-point Likert scale in 3‑dimensional (3D) fluid attenuation inversion recovery (FLAIR), 3D double inversion recovery (DIR), 3D T2, 3D T1, 3D T1 + gadoteric acid, axial T2, axial FLAIR, axial T2*, and 3D arterial time-of-flight MR angiography (art. TOF) sequences acquired during 1 week before (CS-) and after (CS+) the implementation of CS. Time of acquisition was recorded for all sequences.

RESULTS

A total of 51 CS- and 48 CS+ patients were included. The median scan time reduction was 29.3% (range 0.0-58.4%), median voxel size reduction was 10.5% (0.0-33.3%). The CS+ image quality was rated superior for 3D FLAIR (p < 0.001), 3D T2 (p = 0.001), and axial T2* sequences (p = 0.024). For all other sequences, no statistical difference in image quality was observed. Interreader agreement regarding image quality was good for all sequences (weighted Cohen's κ > 0.5).

CONCLUSION

The use of CS saves considerable imaging time while allowing to increase spatial resolution in routine clinical brain MRI without loss in image quality.

Reduction of procedure times in routine clinical practice with Compressed SENSE magnetic resonance imaging technique

Objectives

Acceleration of MR sequences beyond current parallel imaging techniques is possible with the Compressed SENSE technique that has recently become available for 1.5 and 3 Tesla scanners, for nearly all image contrasts and for 2D and 3D sequences. The impact of this technique on examination timing parameters and MR protocols in a clinical setting was investigated in this retrospective study.

Material and methods

A numerical analysis of the examination timing parameters (scan time, exam time, procedure time, interscan delay time, changeover time, nonscan time) based on the MR protocols of 6 different body regions (brain, knee, lumbar spine, breast, shoulder) using MR log files was performed and the total number of examinations acquired from January to April both in 2017 and 2018 on a 1.5 T MR scanner was registered. Percentages, box plots and unpaired two-sided t tests were obtained for statistical evaluation.

Results

All examination timing parameters of the six anatomical regions analysed were significantly shortened after implementation of Compressed SENSE. On average, scan times were accelerated by 20.2% (p<0.0001) while procedure times were shortened by 16% (p<0.0001). Considering all anatomical regions and all MR protocols, 27% more examinations were performed over the same 4 month period in 2018 compared to 2017.

Conclusion

Compressed SENSE allows for a significant acceleration of MR examinations and a considerable increase in the total number of MR examinations is possible.