Rapid acquisition of magnetic resonance imaging of the shoulder using three-dimensional fast spin echo sequence with compressed sensing

[Accelerated musculoskeletal magnetic resonance imaging with deep learning-based image reconstruction at 0.55 T-3 T]

CLINICAL/METHODICAL ISSUE

Magnetic resonance imaging (MRI) is a central component of musculoskeletal imaging. However, long image acquisition times can pose practical barriers in clinical practice.

STANDARD RADIOLOGICAL METHODS

MRI is the established modality of choice in the diagnostic workup of injuries and diseases of the musculoskeletal system due to its high spatial resolution, excellent signal-to-noise ratio (SNR), and unparalleled soft tissue contrast.

METHODOLOGICAL INNOVATIONS

Continuous advances in hardware and software technology over the last few decades have enabled four-fold acceleration of 2D turbo-spin-echo (TSE) without compromising image quality or diagnostic performance. The recent clinical introduction of deep learning (DL)-based image reconstruction algorithms helps to minimize further the interdependency between SNR, spatial resolution and image acquisition time and allows the use of higher acceleration factors.

PERFORMANCE

The combined use of advanced acceleration techniques and DL-based image reconstruction holds enormous potential to maximize efficiency, patient comfort, access, and value of musculoskeletal MRI while maintaining excellent diagnostic accuracy.

ACHIEVEMENTS

Accelerated MRI with DL-based image reconstruction has rapidly found its way into clinical practice and proven to be of added value. Furthermore, recent investigations suggest that the potential of this technology does not yet appear to be fully harvested.

PRACTICAL RECOMMENDATIONS

Deep learning-reconstructed fast musculoskeletal MRI examinations can be reliably used for diagnostic work-up and follow-up of musculoskeletal pathologies in clinical practice.

Modern acceleration in musculoskeletal MRI: applications, implications, and challenges

Magnetic resonance imaging (MRI) is crucial for accurately diagnosing a wide spectrum of musculoskeletal conditions due to its superior soft tissue contrast resolution. However, the long acquisition times of traditional two-dimensional (2D) and three-dimensional (3D) fast and turbo spin-echo (TSE) pulse sequences can limit patient access and comfort. Recent technical advancements have introduced acceleration techniques that significantly reduce MRI times for musculoskeletal examinations. Key acceleration methods include parallel imaging (PI), simultaneous multi-slice acquisition (SMS), and compressed sensing (CS), enabling up to eightfold faster scans while maintaining image quality, resolution, and safety standards. These innovations now allow for 3- to 6-fold accelerated clinical musculoskeletal MRI exams, reducing scan times to 4 to 6 min for joints and spine imaging. Evolving deep learning-based image reconstruction promises even faster scans without compromising quality. Current research indicates that combining acceleration techniques, deep learning image reconstruction, and superresolution algorithms will eventually facilitate tenfold accelerated musculoskeletal MRI in routine clinical practice. Such rapid MRI protocols can drastically reduce scan times by 80-90% compared to conventional methods. Implementing these rapid imaging protocols does impact workflow, indirect costs, and workload for MRI technologists and radiologists, which requires careful management. However, the shift from conventional to accelerated, deep learning-based MRI enhances the value of musculoskeletal MRI by improving patient access and comfort and promoting sustainable imaging practices. This article offers a comprehensive overview of the technical aspects, benefits, and challenges of modern accelerated musculoskeletal MRI, guiding radiologists and researchers in this evolving field.

Fast 5-minute shoulder MRI protocol with accelerated TSE-sequences and deep learning image reconstruction for the assessment of shoulder pain at 1.5 and 3 Tesla

Purpose

The objective of this study was to implement a 5-minute MRI protocol for the shoulder in routine clinical practice consisting of accelerated 2D turbo spin echo (TSE) sequences with deep learning (DL) reconstruction at 1.5 and 3 Tesla, and to compare the image quality and diagnostic performance to that of a standard 2D TSE protocol.

Methods

Patients undergoing shoulder MRI between October 2020 and June 2021 were prospectively enrolled. Each patient underwent two MRI examinations: first a standard, fully sampled TSE (TSES) protocol reconstructed with a standard reconstruction followed by a second fast, prospectively undersampled TSE protocol with a conventional parallel imaging undersampling pattern reconstructed with a DL reconstruction (TSEDL). Image quality and visualization of anatomic structures as well as diagnostic performance with respect to shoulder lesions were assessed using a 5-point Likert-scale (5 = best). Interchangeability analysis, Wilcoxon signed-rank test and kappa statistics were performed to compare the two protocols.

Results

A total of 30 participants was included (mean age 50±15 years; 15 men). Overall image quality was evaluated to be superior in TSEDL versus TSES (p<0.001). Noise and edge sharpness were evaluated to be significantly superior in TSEDL versus TSES (noise: p<0.001, edge sharpness: p<0.05). No difference was found concerning qualitative diagnostic confidence, assessability of anatomical structures (p>0.05), and quantitative diagnostic performance for shoulder lesions when comparing the two sequences.

Conclusions

A fast 5-minute TSEDL MRI protocol of the shoulder is feasible in routine clinical practice at 1.5 and 3 T, with interchangeable results concerning the diagnostic performance, allowing a reduction in scan time of more than 50% compared to the standard TSES protocol.

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.

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 MRI Reconstruction for Accelerating Turbo Spin Echo Hand and Wrist Imaging: A Comparison of Image Quality, Visualization of Anatomy, and Detection of Common Pathologies with Standard Imaging

RATIONALE AND OBJECTIVES

Magnetic resonance imaging (MRI) of the hand and wrist is a routine MRI examination and takes about 15-20 minutes, which can lead to problems resulting from the relatively long scan time, such as decreased image quality due to motion artifacts and lower patient throughput. The objective of this study was to evaluate a deep learning (DL) reconstruction for turbo spin echo (TSE) sequences of the hand and wrist regarding image quality, visualization of anatomy, and diagnostic performance concerning common pathologies.

MATERIALS AND METHODS

Twenty-one patients (mean age: 43 ± 19 [19-85] years, 10 men, 11 female) were prospectively enrolled in this study between October 2020 and June 2021. Each participant underwent two MRI protocols: first, standard fully sampled TSE sequences reconstructed with a standard GRAPPA reconstruction (TSES) and second, prospectively undersampled TSE sequences using a conventional parallel imaging undersampling pattern reconstructed with a DL reconstruction (TSEDL). Both protocols were acquired consecutively in one examination. Two experienced MSK-imaging radiologists qualitatively evaluated the images concerning image quality, noise, edge sharpness, artifacts, and diagnostic confidence, as well as the delineation of anatomical structures (triangular fibrocartilage complex, tendon of the extensor carpi ulnaris muscle, extrinsic and intrinsic ligaments, median nerve, cartilage) using a five-point Likert scale and assessed common pathologies. Wilcoxon signed-rank test and kappa statistics were performed to compare the sequences.

RESULTS

Overall image quality, artifacts, delineation of anatomical structures, and diagnostic confidence of TSEDL were rated to be comparable to TSES (p > 0.05). Additionally, TSEDL showed decreased image noise (4.90, median 5, IQR 5-5) compared to TSES (4.52, median 5, IQR 4-5, p < 0.05) and improved edge sharpness (TSEDL: 4.10, median 4, IQR 3.5-5; TSES: 3.57, median 4, IQR 3-4; p < 0.05). Inter- and intrareader agreement was substantial to almost perfect (κ = 0.632-1.000) for the detection of common pathologies. Time of acquisition could be reduced by more than 60% with the protocol using TSEDL.

CONCLUSION

Compared to TSES, TSEDL provided decreased noise and increased edge sharpness, equal image quality, delineation of anatomical structures, detection of pathologies, and diagnostic confidence. Therefore, TSEDL may be clinically relevant for hand and wrist imaging, as it reduces examination time by more than 60%, thus increasing patient comfort and patient throughput.

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.

Image Quality and Diagnostic Performance of Accelerated 2D Hip MRI with Deep Learning Reconstruction Based on a Deep Iterative Hierarchical Network

OBJECTIVES

Hip MRI using standard multiplanar sequences requires long scan times. Accelerating MRI is accompanied by reduced image quality. This study aimed to compare standard two-dimensional (2D) turbo spin echo (TSE) sequences with accelerated 2D TSE sequences with deep learning (DL) reconstruction (TSEDL) for routine clinical hip MRI at 1.5 and 3 T in terms of feasibility, image quality, and diagnostic performance.

MATERIAL AND METHODS

In this prospective, monocentric study, TSEDL was implemented clinically and evaluated in 14 prospectively enrolled patients undergoing a clinically indicated hip MRI at 1.5 and 3T between October 2020 and May 2021. Each patient underwent two examinations: For the first exam, we used standard sequences with generalized autocalibrating partial parallel acquisition reconstruction (TSES). For the second exam, we implemented prospectively undersampled TSE sequences with DL reconstruction (TSEDL). Two radiologists assessed the TSEDL and TSES regarding image quality, artifacts, noise, edge sharpness, diagnostic confidence, and delineation of anatomical structures using an ordinal five-point Likert scale (1 = non-diagnostic; 2 = poor; 3 = moderate; 4 = good; 5 = excellent). Both sequences were compared regarding the detection of common pathologies of the hip. Comparative analyses were conducted to assess the differences between TSEDL and TSES.

RESULTS

Compared with TSES, TSEDL was rated to be significantly superior in terms of image quality (p ≤ 0.020) with significantly reduced noise (p ≤ 0.001) and significantly improved edge sharpness (p = 0.003). No difference was found between TSES and TSEDL concerning the extent of artifacts, diagnostic confidence, or the delineation of anatomical structures (p > 0.05). Example acquisition time reductions for the TSE sequences of 52% at 3 Tesla and 70% at 1.5 Tesla were achieved.

CONCLUSION

TSEDL of the hip is clinically feasible, showing excellent image quality and equivalent diagnostic performance compared with TSES, reducing the acquisition time significantly.

Comparison of deep learning-based reconstruction of PROPELLER Shoulder MRI with conventional reconstruction

OBJECTIVE

To compare the image quality and agreement among conventional and accelerated periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) MRI with both conventional reconstruction (CR) and deep learning-based reconstruction (DLR) methods for evaluation of shoulder.

MATERIALS AND METHODS

We included patients who underwent conventional (acquisition time, 8 min) and accelerated (acquisition time, 4 min and 24 s; 45% reduction) PROPELLER shoulder MRI using both CR and DLR methods between February 2021 and February 2022 on a 3 T MRI system. Quantitative evaluation was performed by calculating the signal-to-noise ratio (SNR). Two musculoskeletal radiologists compared the image quality using conventional sequence with CR as the reference standard. Interobserver agreement between image sets for evaluating shoulder was analyzed using weighted/unweighted kappa statistics.

RESULTS

Ninety-two patients with 100 shoulder MRI scans were included. Conventional sequence with DLR had the highest SNR (P < .001), followed by accelerated sequence with DLR, conventional sequence with CR, and accelerated sequence with CR. Comparison of image quality by both readers revealed that conventional sequence with DLR (P = .003 and P < .001) and accelerated sequence with DLR (P = .016 and P < .001) had better image quality than the conventional sequence with CR. Interobserver agreement was substantial to almost perfect for detecting shoulder abnormalities (κ = 0.600-0.884). Agreement between the image sets was substantial to almost perfect (κ = 0.691-1).

CONCLUSION

Accelerated PROPELLER with DLR showed even better image quality than conventional PROPELLER with CR and interobserver agreement for shoulder pathologies comparable to that of conventional PROPELLER with CR, despite the shorter scan time.

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.

Accelerating Knee MRI: 3D Modulated Flip-Angle Technique in Refocused Imaging with an Extended Echo Train and Compressed Sensing

Purpose

The three-dimensional (3D) sequence of magnetic resonance imaging (MRI) plays a critical role in the imaging of musculoskeletal joints; however, its long acquisition time limits its clinical application. In such conditions, compressed sensing (CS) is introduced to accelerate MRI in clinical practice. We aimed to investigate the feasibility of an isotropic 3D variable-flip-angle fast spin echo (FSE) sequence with CS technique (CS-MATRIX) compared to conventional 2D sequences in knee imaging.

Methods

Images from different sequences of both the accelerated CS-MATRIX and the corresponding conventional acquisitions were prospectively analyzed and compared. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of the structures within the knees were measured for quantitative analysis. The subjective image quality and diagnostic agreement were compared between CS-MATRIX and conventional 2D sequences. Quantitative and subjective image quality scores were statistically analyzed with the paired t-test and Wilcoxon signed-rank test, respectively. Diagnostic agreements of knee substructure were assessed using Cohen’s weighted kappa statistic.

Results

For quantitative analysis, images from the CS-MATRIX sequence showed a significantly higher SNR than T2-fs 2D sequences for visualizing cartilage, menisci, and ligaments, as well as a higher SNR than proton density (pd) 2D sequences for visualizing menisci and ligaments. There was no significant difference between CS-MATRIX and 2D T2-fs sequences in subjective image quality assessment. The diagnostic agreement was rated as moderate to very good between CS-MATRIX and 2D sequences.

Conclusion

This study demonstrates the feasibility and clinical potential of the CS-MATRIX sequence technique for detecting knee lesions The CS-MATRIX sequence allows for faster knee imaging than conventional 2D sequences, yielding similar image quality to 2D sequences.

3D MRI of the Shoulder

Magnetic resonance imaging provides a comprehensive evaluation of the shoulder including the rotator cuff muscles and tendons, glenoid labrum, long head biceps tendon, and glenohumeral and acromioclavicular joint articulations. Most institutions use two-dimensional sequences acquired in all three imaging planes to accurately evaluate the many important structures of the shoulder. Recently, the addition of three-dimensional (3D) acquisitions with 3D reconstructions has become clinically feasible and helped improve our understanding of several important pathologic conditions, allowing us to provide added value for referring clinicians. This article briefly describes techniques used in 3D imaging of the shoulder and discusses applications of these techniques including measuring glenoid bone loss in anterior glenohumeral instability. We also review the literature on routine 3D imaging for the evaluation of common shoulder abnormalities as 3D imaging will likely become more common as imaging software continues to improve.

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.

Comparison of CAIPIRINHA-accelerated 3D fat-saturated-SPACE MRI with 2D MRI sequences for the assessment of shoulder pathology

OBJECTIVES

To compare the performance of 6-min MRI with a fat-saturated 3D-controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA) Sampling perfection with application-optimized contrast using different flip angle evolution (SPACE) TSE protocol with 10-min 2D TSE MRI protocol for assessment of abnormalities of the shoulder.

METHODS

Forty-nine subjects underwent both 3D fat-saturated-CAIPIRINHA SPACE and 2D TSE sequences of the shoulder on a 3.0-T system. Following randomization and anonymization, two musculoskeletal radiologists evaluated the 2D and 3D images independently for image quality and diagnostic capability. Descriptive statistics, inter-observer, and inter-method concordance were investigated. p values < 0.05 were considered significant.

RESULTS

For image quality assessment, 2D images were similar to 3D CAIPIRINHA SPACE images (p = 0.05). 3D had lower noise standard deviation (SD) and higher fluid CNR than 2D images (p = 0.00). For diagnostic capability assessment, using 2D TSE as a standard of reference, sensitivity, specificity, and accuracy of 3D SPACE were, respectively, 94.81%, 94.12%, and 94.39% for tendon abnormalities; 97.06%, 80.00%, and 91.84% for acromioclavicular joint abnormalities; 88.89%, 100.00%, and 93.89% for adjacent bone alterations; and 97.30%, 100%, and 97.96% for joint fluid/effusion assessment. The inter-method concordance was moderate to almost perfect. The inter-observer-concordance of the shoulder assessment was also moderate to almost perfect, with SSP lesions demonstrating the greatest concordance.

CONCLUSIONS

The performance of 6-min 3D fat-saturated-CAIPIRINHA SPACE MRI for shoulder MRI is similar to that of 10-min 2D TSE MRI. 3D fat-saturated-CAIPIRINHA SPACE MRI can be utilized to reduce scan time without degradation in image quality.

KEY POINTS

• CAIPIRINHA acceleration 3D fat-saturated-MRI of the shoulder is achievable in 6 min with high spatial resolution. • 3D fat-saturated CAIPIRINHA MRI is similar to 2D MRI in the shoulder assessment. • 3D CAIPIRINHA MRI images enable rapid diagnosis of shoulder abnormalities without image quality degradation.

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.

Combined signal averaging and compressed sensing: impact on quality of contrast-enhanced fat-suppressed 3D turbo field-echo imaging for pharyngolaryngeal squamous cell carcinoma

PURPOSE

To determine whether combined signal averaging and compressed sensing (CS averaging) improves the image quality of contrast-enhanced fat-suppressed T1-weighted three-dimensional turbo field-echo (FS T1W 3D-TFE) for evaluation of pharyngolaryngeal squamous cell carcinoma (PLSCC).

METHODS

This retrospective study included 27 patients with PLSCC. In all patients, contrast-enhanced FS T1W 3D-TFE imaging with CS averaging (number of excitations, 7) and that without CS averaging (number of excitations, 1) were obtained during the same acquisition time. Overall image quality, mucosal enhancement, vessel clarity, motion artifact, lesion conspicuity, and lesion edge sharpness were qualitatively evaluated using a 5-point scale. Images with and without CS averaging were compared using the Wilcoxon signed-rank test. Signal-to-noise ratio (SNR) of the lesion and the muscle structure were compared between the two imaging methods using a paired t-test.

RESULTS

Compared with the images without CS averaging, those with CS averaging showed significantly better overall image quality (p = 0.002), mucosal enhancement (p = 0.009), vessel clarity (p = 0.003), muscle edge clarity (p = 0.002), lesion conspicuity (p = 0.002), and lesion edge sharpness (p = 0.001); and less motion artifact (p < 0.001). The SNRs of the lesion and of the muscle structure were significantly higher for images with CS averaging than those without CS averaging (p < 0.001).

CONCLUSION

CS averaging improves the image quality of contrast-enhanced FS T1W 3D-TFE MR images for evaluation of PLSCC without requiring additional acquisition time.

Tibial bone stress injury: diagnostic performance and inter-reader agreement of an abbreviated 5-min magnetic resonance protocol

OBJECTIVE

To compare the diagnostic performance and inter-reader agreement of an abbreviated (5 min) MR protocol compared to a complete (25 min) protocol, for evaluation of suspected tibial bone stress injury.

MATERIALS AND METHODS

This IRB-approved retrospective study consisted of 95 consecutive MR examinations in 88 patients with suspected tibial bone stress injury. Three musculoskeletal radiologists independently classified all examinations utilizing both an abbreviated protocol consisting only of axial T2-weighted images with fat suppression, and after a washout period again classified the complete examinations. Accuracy was calculated as proportion of cases classified exactly, within 1 grade, within 2 grades, and also utilizing a simplified "clinically relevant" classification combining grades 2, 3, and 4A into a single group. Significance testing was performed with the chi-test, and a post-hoc power analysis was performed. Inter-reader agreement was calculated with Kendall's coefficient of concordance, with significance testing performed utilizing the z-test after bootstrapping to obtain the standard error.

RESULTS AND CONCLUSIONS

There was no significant difference in accuracy of grading tibial bone stress injuries between complete and abbreviated examinations. For complete exams, pooled exact accuracy was 47.8%; accuracy within 1 grade was 82.8%; and accuracy within 2 grades was 96.1%. For the abbreviated protocol, corresponding accuracies were 50.2, 82.0, and 93.9%. With the "clinically relevant" simplified classification, accuracy was 58.6% for complete exams and 64.2% for abbreviated exams. There was no significant difference in inter-reader agreement, with substantial agreement demonstrated for both complete (Kendall coefficient of concordance 0.805) and abbreviated examinations (coefficient of 0.767).

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

BACKGROUND

Decreasing MRI scan time is a key factor to increase patient comfort and compliance as well as the productivity of MRI scanners.

PURPOSE/HYPOTHESIS

Compressed sensing (CS) should significantly accelerate 3D scans. This study evaluated the clinical application and cost effectiveness of accelerated 3D T₂ sequences of the lumbar spine.

STUDY TYPE

Prospective, cross-sectional, observational.

POPULATION

Twenty healthy volunteers and 10 patients.

FIELD STRENGTH/SEQUENCE

A 3D T₂ TSE sequence, identical 3D sequences with three different parallel imaging and CS accelerating factors, and 2D TSE sequences as a clinical reference were obtained on a 3T scanner.

ASSESSMENT

Three readers evaluated the sequences for delineation of anatomical structures and image quality. A quantitative analysis consisting of root mean square error, structural similarity index, signal-to-noise ratio, and contrast-to-noise ratio were performed. The scan times were used to calculate cost differences for each sequence.

STATISTICAL TESTS

An analysis of variance with repeated measurements and the Friedman test were used to test for potential differences between the sequences. Post-hoc analysis was made with the chi-squared and Tukey-Kramer test.

RESULTS

CS with factor 4.5 results in unchanged image quality compared to the T₂ TSE for volunteers and patients (overall image impression: 4.75 vs. 4.20 [P = 0.73] and 4.90 vs. 4.47 [P = 0.44]). The CS 4.5 scan is 167 seconds (-39%) faster than the 3D and 216.5 seconds (-45%) faster than the 2D sequences. No significant differences was found for the diagnostic certainty in the volunteers and patients between 2D TSE and 3D CS 4.5 (P = 0.89 and P = 0.43). A reduction of scan time to 148 seconds (CS 8) was still rated acceptable for most diagnosis.

DATA CONCLUSION

CS accelerates the 3D T₂ without compromising image quality. The 3D sequences offer comparable diagnostic quality to the clinical 2D standard with less scan time (-45%), potentially increasing the productivity of MRI scanners.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 6 J. Magn. Reson. Imaging 2019;49:e164-e175.

Diagnostic performance of shoulder magnetic resonance arthrography for labral tears having surgery as reference: comparison of high-resolution isotropic 3D sequence (THRIVE) with standard protocol

PURPOSE

To compare the diagnostic performance of T1 high-resolution isotropic volume excitation (THRIVE) sequence with that of a standard protocol for direct shoulder magnetic resonance arthrography (MRA) for the diagnosis of superior labral anterior-to-posterior (SLAP) and Bankart lesions, using arthroscopy findings as a reference standard.

MATERIALS AND METHODS

We retrospectively studied 84 patients who underwent direct shoulder 3T MRA using THRIVE and two-dimensional three-plane proton-density fat-suppressed (2D-PD-FS) sequences. One reviewer evaluated the contrast-to-noise ratio (CNR) as a quantitative image quality. Other two reviewers independently evaluated the subjective image noise, image sharpness, and radiologic diagnosis as qualitative image quality. Arthroscopic surgical findings were considered the reference standard. Wilcoxon rank sum, Chi-square/Fisher's exact, and DeLong's tests, as well as intraclass correlation coefficients (ICCs) were used to evaluate differences between THRIVE and 2D-PD-FS images.

RESULTS

THRIVE images had significantly higher CNR (p < 0.001), and subjective ratings of image noise (p = 0.009) and sharpness (p = 0.039) than 2D-PD-FS images (p < 0.001). THRIVE images had similar (p ≥ 0.18) diagnostic performance (sensitivity, 93.0-97.2%; specificity, 95.8-100%; accuracy, 95.2-97.6%) for the diagnosis of SLAP and Bankart lesions with excellent agreement (ICC = 0.898-0.942) when compared to 2D-PD-FS images (sensitivity, 86.1-91.7%; specificity, 93.8-95.8%; accuracy, 90.5-92.9%; agreement, ICC = 0.782-0.858). The scan time was reduced by 69% for THRIVE sequence compared to 2D-PD-FS sequence (2 min 40 s vs. 8 min 40 s).

CONCLUSION

The THRIVE sequence may be helpful in the diagnosis of SLAP and Bankart lesions, and may be routinely used during direct shoulder 3T MRA.