Keywords: Neurography, MSK

Motivation: In 3-D double-echo steady-state sequence with water excitation, fat suppression may be incomplete due to system imperfections, such as B0 and B1 inhomogeneity.

Goal(s): This study describes implementing an adapted Dixon reconstruction to further suppress residual fat signal.

Approach: The images between default and proposed reconstructions were compared in 16 patients undergoing routine upper extremity MR neurography.

Results: The preliminary results demonstrated the feasibility of using the proposed reconstruction to remove residual fat signals incompletely suppressed by the water excitation.

Impact: A benefit of the further suppressed fat provided by the proposed reconstruction was the improved depiction of small, yet clinically important peripheral nerves (particularly subcutaneous sensory branches surrounded by fat).

Keywords: Muscle, Quantitative Imaging, Analysis/Processing; Software Tools

Motivation: Quantitative magnetic resonance imaging (qMRI) is a common tool for assessing neuromuscular disorders, but its quantitative parameters often lack specificity and generally do not directly relate to muscle function. 

Goal(s): In our ongoing MOTION study, we are collecting whole-leg qMRI data and assessing muscle structure, function, and lifestyle in a large cross-sectional cohort to identify confounding factors in qMRI evaluation. 

Approach: To streamline data analysis for this cohort, we've developed a fully automated muscle-Bids-based data analysis pipeline, including automated muscle segmentation.

Results: Here, we introduce our data analysis pipeline, demonstrated using repeated scans of one volunteer.

Impact: The implementation of fully automated qMRI data processing streamlines large-scale studies and enhances its integration into clinical workflows. This standardization we expect to reduces variability for more dependable and reproducible outcomes.

Keywords: Whole Joint, Bone

Motivation: MRI provides superior soft-tissue contrast, however, cortical bone and ultrashort-T2* tissues are invisible in routine clinical MRI. Multi-echo Ultrashort TE (mecho-UTE) may allow visualization and quantification of bone and ultrashort-T2* tissues, however, its acquisition time is often long.

Goal(s): We used CG-SENSE and Deep Learning Reconstruction (CG-SENSE+DLR) to accelerate mecho-UTE, making it clinically feasible.

Approach: 5-min, 3-min, and 2-min mecho-UTE scans were prospectively acquired and reconstructed with Gridding and CG-SENSE+DLR. Resolution, sharpness, and T2* were measured and compared.

Results: CG-SENSE+DLR allows 2- and 3-min mecho-UTE with improved resolution and sharpness compared to 5-min mecho-UTE with Gridding reconstruction.

Impact: Routine MRI and mecho-UTE enable comprehensive MSK imaging, providing soft-tissue contrast and visualization-and-quantification of bone and ultrashort-T2* tissues. CG-SENSE+DLR allows accelerated 2- and 3-minunte mecho-UTE, which would enable widespread clinical utilization to demonstrate the value of mecho-UTE compared to CT.

Keywords: Cartilage, Machine Learning/Artificial Intelligence, Deep Learning, T1rho

Motivation: Estimating proton density (PD) and T1$$$\rho$$$ maps in the knee joint is time-consuming with nonlinear least squares (NLS) algorithms. Deep learning (DL) methods can do it faster.

Goal(s): Find the best DL model for this task, comparing different DL models.

Approach: We compared UNet, DenseNet, Encoder-Decoder, and Convolutional Neural Network (CNN). The proposed models directly transform k-space data into T1$$$\rho$$$ and PD maps, eliminating the need for traditional exponential fitting.

Results: UNet and Encoder-Decoder-based models obtained the best performance, using short training and prediction times and minimal memory requirements. The proposed models are 129 times faster than the benchmark NLS method.

Impact: This study compared different aspects of four DL models for joint PD and T1$$$\rho$$$ maps in the knee cartilage, indicating the most recommended models for this task.

Keywords: Whole Joint, Quantitative Imaging

Motivation: We seek better validation and QA of musculoskeletal intensive-variable MR biomarkers.

Goal(s): We aimed to devise and evaluate a phantom with suitable form factor and composition for practical use in this setting.

Approach: “Expected” temperature- and B₀-dependent R₁ values were calculated from prior data and verified by inversion recovery (IR). Practical QA use cases for hand and knee trials were exemplified using product-sequence 3D variable flip angle (3DVFA) R₁measurements on three vendors’ scanners.

Results: There was little deviation between “Expected” and IR-measured R₁ (rms 3.8%).  3DVFA R₁ exhibited bias (mean +23%) which must be subtracted during within-study QA.

Impact: This work will improve QA in real-world musculoskeletal clinical trials which use  intensive-variable MR biomarkers, and will help validate such biomarkers.

Keywords: Other Musculoskeletal, MSK, Temporomandibular Joints

Motivation: Patients with temporomandibular joint (TMJ) disorders often cannot endure long MRI examination due to facial pain, thus necessitating accelerated MRI.

Goal(s): To investigative the feasibility of AI-assisted compressed sensing (ACS) accelerated MRI technique in TMJ, and compare its performance with parallel imaging (PI) protocol and standard protocol.

Approach: Forty-four participants with 88 TMJs were qualitatively and quantitatively evaluated. Diagnostic agreement of joint effusion and disc displacement were analyzed.

Results: Overall image quality, SNR, and most structures visibility of ACS protocol were significantly higher than standard protocol, and similar to PI protocol. Diagnostic agreement was excellent with kappa values ranging from 0.81 to 1.00.

Impact: This study demonstrated that ACS accelerated MRI is feasible in TMJ with reduced acquisition times, good image quality, and excellent diagnostic precision, which holds great promise in clinical practice and is especially helpful for patients with TMJ disorders.

Keywords: Whole Joint, Machine Learning/Artificial Intelligence

Motivation: The broad clinical application of knee 3D-MRI has been constrained by scanning time.

Goal(s): To investigate the potential of AI-assisted compressed sensing (ACS) in knee MRI to optimize the scanning process.

Approach: 3D-ACS, 3D compressed sensing (CS), and 2D parallel acquisition technology (PAT) scans were performed. The 3D-ACS images underwent 3.5 mm/2.0 mm multiplanar reconstruction (MPR); radiologists evaluated the quality of images and diagnosed diseases.

Results: 3D-ACS provided poorer bone structure visualization, improved cartilage visualization, and less satisfactory axial images with 3.5 mm/2.0 mm MPR than 2D-PAT. High levels of diagnostic agreement and accuracy were observed across all diagnoses.

Impact: 3D-ACS provided poorer bone structure visualization, improved cartilage visualization, and less satisfactory axial images with 3.5 mm/2.0 mm MPR than 2D-PAT. High levels of diagnostic agreement and accuracy were observed across all diagnoses.

Keywords: Bone, MSK, Bone stress, finite element modelling

Motivation: Finite element modeling could help us better understand the role of bone strain in stress fractures. MRI, the standard for diagnosis, characterizes geometry but not bone density.

Goal(s): To evaluate the sensitivity of finite element model-estimated strain to the use of generic material properties.

Approach: Finite element models of the tibia-fibula complex were created with heterogeneous (CT referent) or homogeneous (simulating MR) material properties. Errors in strain and percent changes across running stride length conditions were calculated.

Results: Strains were substantially underestimated by models using homogeneous material properties, but relative changes in peak strain between and within individuals illustrated strong agreement.

Impact: MRI can be used to explore relative changes in bone strain in healthy adults when CT is not available. This option improves the feasibility of using finite element modelling to study bone strain and will enable opportunistic studies. 

Keywords: Whole Joint, Joints

Motivation: The application of 3D SPACE-DIXON techniques for musculoskeletal MRI has advantages in terms of fat suppression capacities, but drawbacks with regard to substantially longer acquisition times compared with SPAIR fat suppressed 3D SPACE.

Goal(s): To reduce the acquisition time of 3D SPACE-DIXON to that of 3D SPACE-SPAIR while maintaining superior fat suppression capabilities.

Approach: Six-fold CAIPIRINHA acceleration was combined with a deep learning-based image reconstruction algorithm to decrease the acquisition time and maintain image quality.

Results: Image quality parameters in volunteer scans were rated equivalent to the conventional 3D SPACE-DIXON sequence and superior to the 3D SPACE-SPAIR sequence.

Impact: We present a 3D SPACE-DIXON technique with improved fat suppression performance and similar acquisition time compared with 3D SPACE-SPAIR for musculoskeletal 3D MRI. Preliminary in vivo results indicate the clinical utility of this technique for proton density-weighted 3D MRI.

Keywords: Whole Joint, Joints

Motivation:  knee injury is common in clinical practice. DTI enables quantitative assessment of tissue changes in pathological joints, but its clinical application is limited due to prolonged scan time.

Goal(s): This study aims to explore the feasibility of using SMS technique in RESOLVE- DTI in knee joint to reduce acquisition time without compromising image quality.

Approach: There protocols, Conventional RESOLVE-DTI with 12 directions, and SMS-RESOLVE-DTI with 12 and 20 directions, were used to fully assess the image quality and quantitative parameters.

Results: The use of SMS technique greatly reduced the acquisition time without compromise image quality and quantitative evaluation accuracy.

Impact: The SMS technique greatly shortens the acquisition time of RESOLVE-DTI and provides similar image quality, allowing clinical doctors to simultaneously evaluate cartilage and ligaments of the knee joint in one scan. SMS-RESOLVE-DTI has high clinical application potential.

Keywords: Whole Joint, Joints, QSM, UTE, UTE-QSM, artifact reduction

Motivation: Quantitative susceptibility mapping (QSM) in MRI is valuable for characterizing tissue composition in the human body. Ultrashort echo time (UTE) is crucial for QSM of short T2 tissues in the musculoskeletal system. 

Goal(s): As UTE-QSM is susceptible to motion-related streaking artifacts, our study aimed at reducing those artifacts.

Approach: A novel approach called Streaking Artifact Reduction using Edge Detection (SARED) is proposed to mitigate such artifacts. The method involves edge detection, exclusion of pixels near edges, and two-step QSM processing. 

Results: Experimental results from knee and ankle joint imaging showed that SARED significantly reduces streaking artifacts, improving the accuracy of UTE-QSM.

Impact: The proposed Streaking Artifact Reduction using Edge Detection (SARED) approach significantly reduced motion-induced streaking artifacts in ultrashort echo time quantitative susceptibility mapping (UTE-QSM), enhancing accuracy in characterizing musculoskeletal tissues.

Keywords: Whole Joint, MSK

Motivation: Ankle MRI usually requires a long examination time. A faster scan with adequate image qualities is desired in clinical practice.

Goal(s): To evaluate a deep-learning reconstruction accelerated turbo spin echo (DLR-TSE) sequence in ankle application.

Approach: Four radiologists independently assessed the image quality and reviewed structural abnormalities of 56 consecutive patients on DLR-TSE and compared these results with those of conventional TSE.

Results: Overall, DLR-TSE achieved superior image qualities with a 57.4% reduction in total acquisition time compared with conventional TSE images. There were no differences in the differentiation of anatomic details, diagnostic confidence, or assessments of structural abnormalities between the two techniques.

Impact: Deep learning reconstruction can accelerate the turbo spin echo imaging without compromising the image quality or lesion detectability in ankle MRI.

Keywords: Cartilage, MSK

Motivation: High-resolution T1ρ mapping is desired to improve the early diagnosis of diseases such as osteoarthritis; however, it suffers from long acquisition times.

Goal(s): To accelerate high-resolution T1ρ mapping using compressed-sensing reconstruction in a multi-site multi-vendor setting.

Approach: We standardized the T1ρ imaging protocol between three sites using three MR platforms (GE/Philips/Siemens). Accelerated high-resolution T1ρ mapping with accelerator factors (AF) ranging 8-12 were performed using both retrospective and prospective downsamplings with compressed-sensing reconstruction.

Results: The coefficients-of-variation between reference and accelerated maps were <5% for all sites. Reliable high-resolution T1ρ mapping of the whole knee can be acquired within 7 mins.

Impact: Standardization of the acquisition and reconstruction of accelerated high-resolution T1ρ mapping across sites and MR platforms will greatly facilitate its future use in clinical trials and clinical practice, significantly improving diagnosis and evaluation of responses to interventions/treatments for OA.

Keywords: Muscle, Muscle, Perfusion, Reactive Hyperemia, BOLD

Motivation: Lower extremity reactive hyperemia BOLD have been used to evaluate the skeletal muscle perfusion status. The existing methods, such as multi-echo GRE and single-echo EPI, have limitations in terms of spatial coverage and signal quantification.

Goal(s): The study aims to apply dual-echo multi-band EPI to achieve high temporal and spatial resolution, and large coverage in BOLD experiment.

Approach: The study applied dual-echo EPI to sample the T2* along the reactive hyperemia experiment. Images at TE of zero were synthesized to investigate the intrinsic signal change.

Results: The proposed method can provide semi-quantitative indicators of the perfusion status of the lower extremity skeletal muscle.

Impact: This work demonstrates the advantages of dual echo EPI acquisition for lower extremity reactive hyperemia experiments. Compared to the commonly used acquisition strategies, the proposed one can be used to enhance the quality and efficiency of lower extremity perfusion imaging.

Keywords: Cartilage, MSK

Motivation: To accelerate knee imaging for T1ρ mapping in clinical practice

Goal(s): To evaluate deep learning reconstruction from undersampled knee imaging

Approach: Three different sampling strategies were proposed to further decrease scan time and reconstruct images with deep learning

Results: Deep learning reconstruction results are in good agreement with reference images. 

Impact: This work will allow use of novel contrasts including T1ρ to be performed within clinical workflow and improve patient diagnosis

Keywords: Bone, Perfusion, Hip, avascular necrosis, blood flow

Motivation: Avascular necrosis of the hip is due to disturbed blood supply related to various causes. Early evaluation currently requires contrast enhanced MR perfusion imaging.

Goal(s): Evaluate human hip perfusion using non-contrast MR perfusion technique.

Approach: Bilateral hips of healthy volunteers were imaged coronally at 3-T using a 2D spin labeling MR perfusion technique using tag-on tag-off acquisition at varying TI and processing to determine tagged blood signal into the acetabulum, femoral head, and femoral neck. 

Results: We found distinct perfusion signal in the acetabulum but the signal in the femoral head and neck were more subdued. 

Impact: This study demonstrates the feasibility of non-contrast MR perfusion imaging of the human hip, with future application in evaluation of avascular necrosis.