Brachial Plexus Magnetic Resonance Neurography: Technical Challenges and Solutions

Hourglass-like constrictions on MRI are common in electromyography-confirmed cases of neuralgic amyotrophy (Parsonage-Turner syndrome): A tertiary referral center experience

INTRODUCTION/AIMS

Hourglass-like constrictions (HGCs) of involved nerves in neuralgic amyotrophy (NA) (Parsonage-Turner syndrome) have been increasingly recognized with magnetic resonance neurography (MRN). This study sought to determine the sensitivity of HGCs, detected by MRN, among electromyography (EMG)-confirmed NA cases.

METHODS

This study retrospectively reviewed records of patients with the clinical diagnosis of NA, and with EMG confirmation, who underwent 3-Tesla MRN within 90 days of EMG at a single tertiary referral center between 2011 and 2021. "Severe NA" positive cases were defined by a clinical diagnosis and specific EMG criteria: fibrillation potentials or positive sharp waves, along with motor unit recruitment (MUR) grades of "discrete" or "none." On MRN, one or more HGCs, defined as focally decreased nerve caliber or diffusely beaded appearance, was considered "imaging-positive." Post hoc inter-rater reliability for HGCs was measured by comparing the original MRN report against subsequent blinded interpretation by a second radiologist.

RESULTS

A total of 123 NA patients with 3-Tesla MRN performed within 90 days of EMG were identified. HGCs were observed in 90.2% of all NA patients. In "severe NA" cases, based on the above EMG criteria, HGC detection resulted in a sensitivity of 91.9%. Nerve-by-nerve analysis (183 nerve-muscle pairs, nerves assessed by MRN, muscles assessed by EMG) showed a sensitivity of 91.0%. The second radiologist largely agreed with the original HGC evaluation, (94.3% by subjects, 91.8% by nerves), with no significant difference between evaluations (subjects: χ2 = 2.27, P = .132, nerves: χ2 = 0.98, P = .323).

DISCUSSION

MRN detection of HGCs is common in NA.

MR Neurography and Quantitative Muscle MRI of Parsonage Turner Syndrome Involving the Long Thoracic Nerve

BACKGROUND

Parsonage-Turner syndrome (PTS) is characterized by severe, acute upper extremity pain and subsequent paresis and most commonly involves the long thoracic nerve (LTN). While MR neurography (MRN) can detect LTN hourglass-like constrictions (HGCs), quantitative muscle MRI (qMRI) can quantify serratus anterior muscle (SAM) neurogenic changes.

PURPOSE/HYPOTHESIS

1) To characterize qMRI findings in LTN-involved PTS. 2) To investigate associations between qMRI and clinical assessments of HGCs/electromyography (EMG).

STUDY TYPE

Prospective.

POPULATION

30 PTS subjects (25 M/5 F, mean/range age = 39/15-67 years) with LTN involvement who underwent bilateral chest wall qMRI and unilateral brachial plexus MRN.

FIELD STRENGTH/SEQUENCES

3.0 Tesla/multiecho spin-echo T2-mapping, diffusion-weighted echo-planar-imaging, multiecho gradient echo.

ASSESSMENT

qMRI was performed to obtain T2, muscle diameter fat fraction (FF), and cross-sectional area of the SAM. Clinical reports of MRN and EMG were obtained; from MRN, the number of HGCs; from EMG, SAM measurements of motor unit recruitment levels, fibrillations, and positive sharp waves. qMRI/MRN were performed within 90 days of EMG. EMG was performed on average 185 days from symptom onset (all ≥2 weeks from symptom onset) and 5 days preceding MRI.

STATISTICAL TESTS

Paired t-tests were used to compare qMRI measures in the affected SAM versus the contralateral, unaffected side (P < 0.05 deemed statistically significant). Kendall's tau was used to determine associations between qMRI against HGCs and EMG.

RESULTS

Relative to the unaffected SAM, the affected SAM had increased T2 (50.42 ± 6.62 vs. 39.09 ± 4.23 msec) and FF (8.45 ± 9.69 vs. 4.03% ± 1.97%), and decreased muscle diameter (74.26 ± 21.54 vs. 88.73 ± 17.61 μm) and cross-sectional area (9.21 ± 3.75 vs. 16.77 ± 6.40 mm2). There were weak to negligible associations (tau = -0.229 to <0.001, P = 0.054-1.00) between individual qMRI biomarkers and clinical assessments of HGCs and EMG.

DATA CONCLUSION

qMRI changes in the SAM were observed in subjects with PTS involving the LTN.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 1.

Optimized 3D brachial plexus MR neurography using deep learning reconstruction

OBJECTIVE

To evaluate whether 'fast,' unilateral, brachial plexus, 3D magnetic resonance neurography (MRN) acquisitions with deep learning reconstruction (DLR) provide similar image quality to longer, 'standard' scans without DLR.

MATERIALS AND METHODS

An IRB-approved prospective cohort of 30 subjects (13F; mean age = 50.3 ± 17.8y) underwent clinical brachial plexus 3.0 T MRN with 3D oblique-coronal STIR-T2-weighted-FSE. 'Standard' and 'fast' scans (time reduction = 23-48%, mean = 33%) were reconstructed without and with DLR. Evaluation of signal-to-noise ratio (SNR) and edge sharpness was performed for 4 image stacks: 'standard non-DLR,' 'standard DLR,' 'fast non-DLR,' and 'fast DLR.' Three raters qualitatively evaluated 'standard non-DLR' and 'fast DLR' for i) bulk motion (4-point scale), ii) nerve conspicuity of proximal and distal suprascapular and axillary nerves (5-point scale), and iii) nerve signal intensity, size, architecture, and presence of a mass (binary). ANOVA or Wilcoxon signed rank test compared differences. Gwet's agreement coefficient (AC2) assessed inter-rater agreement.

RESULTS

Quantitative SNR and edge sharpness were superior for DLR versus non-DLR (SNR by + 4.57 to + 6.56 [p < 0.001] for 'standard' and + 4.26 to + 4.37 [p < 0.001] for 'fast;' sharpness by + 0.23 to + 0.52/pixel for 'standard' [p < 0.018] and + 0.21 to + 0.25/pixel for 'fast' [p < 0.003]) and similar between 'standard non-DLR' and 'fast DLR' (SNR: p = 0.436-1, sharpness: p = 0.067-1). Qualitatively, 'standard non-DLR' and 'fast DLR' had similar motion artifact, as well as nerve conspicuity, signal intensity, size and morphology, with high inter-rater agreement (AC2: 'standard' = 0.70-0.98, 'fast DLR' = 0.69-0.97).

CONCLUSION

DLR applied to faster, 3D MRN acquisitions provides similar image quality to standard scans. A faster, DL-enabled protocol may replace currently optimized non-DL protocols.

Accelerated 3D MR neurography of the brachial plexus using deep learning-constrained compressed sensing

OBJECTIVES

To explore the use of deep learning-constrained compressed sensing (DLCS) in improving image quality and acquisition time for 3D MRI of the brachial plexus.

METHODS

Fifty-four participants who underwent contrast-enhanced imaging and forty-one participants who underwent unenhanced imaging were included. Sensitivity encoding with an acceleration of 2 × 2 (SENSE4x), CS with an acceleration of 4 (CS4x), and DLCS with acceleration of 4 (DLCS4x) and 8 (DLCS8x) were used for MRI of the brachial plexus. Apparent signal-to-noise ratios (aSNRs), apparent contrast-to-noise ratios (aCNRs), and qualitative scores on a 4-point scale were evaluated and compared by ANOVA and the Friedman test. Interobserver agreement was evaluated by calculating the intraclass correlation coefficients.

RESULTS

DLCS4x achieved higher aSNR and aCNR than SENSE4x, CS4x, and DLCS8x (all p < 0.05). For the root segment of the brachial plexus, no statistically significant differences in the qualitative scores were found among the four sequences. For the trunk segment, DLCS4x had higher scores than SENSE4x (p = 0.04) in the contrast-enhanced group and had higher scores than SENSE4x and DLCS8x in the unenhanced group (all p < 0.05). For the divisions, cords, and branches, DLCS4x had higher scores than SENSE4x, CS4x, and DLCS8x (all p ≤ 0.01). No overt difference was found among SENSE4x, CS4x, and DLCS8x in any segment of the brachial plexus (all p > 0.05).

CONCLUSIONS

In three-dimensional MRI for the brachial plexus, DLCS4x can improve image quality compared with SENSE4x and CS4x, and DLCS8x can maintain the image quality compared to SENSE4x and CS4x.

CLINICAL RELEVANCE STATEMENT

Deep learning-constrained compressed sensing can improve the image quality or accelerate acquisition of 3D MRI of the brachial plexus, which should be benefit in evaluating the brachial plexus and its branches in clinical practice.

KEY POINTS

•Deep learning-constrained compressed sensing showed higher aSNR, aCNR, and qualitative scores for the brachial plexus than SENSE and CS at the same acceleration factor with similar scanning time. •Deep learning-constrained compressed sensing at acceleration factor of 8 had comparable aSNR, aCNR, and qualitative scores to SENSE4x and CS4x with approximately half the examination time. •Deep learning-constrained compressed sensing may be helpful in clinical practice for improving image quality and acquisition time in three-dimensional MRI of the brachial plexus.

The guiding value of the cinematic volume rendering technique in the preoperative diagnosis of brachial plexus schwannoma

This study aimed to explore and compare the guiding value of Maximum Intensity Projection (MIP) and Cinematic Volume Rendering Technique (cVRT) in the preoperative diagnosis of brachial plexus schwannomas. We retrospectively analyzed the clinical and imaging data of 45 patients diagnosed with brachial plexus schwannomas at the First Affiliated Hospital of Zhengzhou University between January 2020 and December 2022. The enhanced three-dimensional short recovery time inversion-recovery fast spin-echo imaging (3D-STIR-SPACE) sequence served as source data for the reconstruction of MIP and cVRT. Two independent observers scored the image quality and evaluated the location of the tumor and the relationship between the tumor and the brachial plexus. The image quality scores of the two reconstruction methods were compared using the nonparametric Wilcoxon signed-rank test, and the consistency between the image and surgical results was assessed using the weighted kappa. Compared to MIP images, cVRT images had a better performance of overall image quality (p < 0.001), nerve and lump visualization (p < 0.001), spatial positional relationship conspicuity (p < 0.001), and diagnostic confidence (p < 0.001). Additionally, the consistency between the cVRT image results and surgical results (kappa =0.913, P<0.001) was higher than that of the MIP images (kappa =0.829, P<0.001). cVRT provides a high guiding value in the preoperative diagnosis of brachial plexus schwannomas and is an important basis for formulating surgical plans.

An Updated Review of Magnetic Resonance Neurography for Plexus Imaging

Magnetic resonance neurography (MRN) is increasingly used to visualize peripheral nerves in vivo. However, the implementation and interpretation of MRN in the brachial and lumbosacral plexi are challenging because of the anatomical complexity and technical limitations. The purpose of this article was to review the clinical context of MRN, describe advanced magnetic resonance (MR) techniques for plexus imaging, and list the general categories of utility of MRN with pertinent imaging examples. The selection and optimization of MR sequences are centered on the homogeneous suppression of fat and blood vessels while enhancing the visibility of the plexus and its branches. Standard 2D fast spin-echo sequences are essential to assess morphology and signal intensity of nerves. Moreover, nerve-selective 3D isotropic images allow improved visualization of nerves and multiplanar reconstruction along their course. Diffusion-weighted and diffusion-tensor images offer microscopic and functional insights into peripheral nerves. The interpretation of MRN in the brachial and lumbosacral plexi should be based on a thorough understanding of their anatomy and pathophysiology. Anatomical landmarks assist in identifying brachial and lumbosacral plexus components of interest. Thus, understanding the varying patterns of nerve abnormalities facilitates the interpretation of aberrant findings.

Flexible array coil for cervical and extraspinal (FACE) MRI at 3.0 Tesla

Objective.High-resolution MRI of the cervical spine (c-spine) and extraspinal neck region requires close-fitting receiver coils to maximize the signal-to-noise ratio (SNR). Conventional, rigid C-spine receiver coils do not adequately contour to the neck to accommodate varying body shapes, resulting in suboptimal SNR. Recent innovations in flexible surface coil array designs may provide three-dimensional (3D) bendability and conformability to optimize SNR, while improving capabilities for higher acceleration factors.Approach.This work describes the design, implementation, and preliminaryin vivotesting of a novel, conformal 23-channel receive-only flexible array for cervical and extraspinal (FACE) MRI at 3-Tesla (T), with use of high-impedance elements to enhance the coil's flexibility. Coil performance was tested by assessing SNR and geometry factors (g-factors) in a phantom compared to a conventional 21-channel head-neck-unit (HNU).In vivoimaging was performed in healthy human volunteers and patients using high-resolution c-spine and neck MRI protocols at 3T, including MR neurography (MRN).Main results.Mean SNR with the FACE was 141%-161% higher at left, right, and posterior off-isocenter positions and 4% higher at the isocenter of the phantom compared to the HNU. Parallel imaging performance was comparable for an acceleration factor (R) = 2 × 2 between the two coils, but improved forR= 3 × 3 with meang-factors ranging from 1.46-2.15 with the FACE compared to 2.36-3.62 obtained with the HNU. Preliminary human volunteer and patient testing confirmed that equivalent or superior image quality could be obtained for evaluation of osseous and soft tissue structures of the cervical region with the FACE.Significance.A conformal and highly flexible cervical array with high-impedance coil elements can potentially enable higher-resolution imaging for cervical imaging.

Scientific Advances and Technical Innovations in Musculoskeletal Radiology

ABSTRACT

Decades of technical innovations have propelled musculoskeletal radiology through an astonishing evolution. New artificial intelligence and deep learning methods capitalize on many past innovations in magnetic resonance imaging (MRI) to reach unprecedented speed, image quality, and new contrasts. Similarly exciting developments in computed tomography (CT) include clinically applicable molecular specificity and substantially improved spatial resolution of musculoskeletal structures and diseases. This special issue of Investigative Radiology comprises a collection of expert summaries and reviews on the most impactful innovations and cutting-edge topics in musculoskeletal radiology, including radiomics and deep learning methods for musculoskeletal disease detection, high-resolution MR neurography, deep learning-driven ultra-fast musculoskeletal MRI, MRI-based synthetic CT, quantitative MRI, modern low-field MRI, 7.0 T MRI, dual-energy CT, cone beam CT, kinematic CT, and synthetic contrast generation in musculoskeletal MRI.