Faculty Bibliography

Knee MRI plays a central role in musculoskeletal diagnostics but has traditionally been associated with relatively long acquisition times. Recent technological advances have fundamentally changed this paradigm. Parallel imaging (PI), simultaneous multi-slice acquisition (SMS), compressed sensing (CS), and combinations thereof have substantially reduced scan times without compromising diagnostic image quality. The introduction of deep learning (DL)-based reconstruction further elevates this transformative breakthrough, as it can reconstruct high-quality diagnostic MR images at higher acceleration factors, where conventional image reconstruction methods have traditionally struggled to succeed. Sixfold PIxSMS-accelerated DL protocols have demonstrated excellent diagnostic performance and image quality, allowing comprehensive knee MRI examinations to be completed in under five minutes. Accelerated three-dimensional (3D) TSE techniques, such as CAIPIRINHA-accelerated SPACE sequences, further expand the potential of knee MRI by enabling high-resolution isotropic 3D imaging at acquisition times that are increasingly practical for routine clinical use. Ongoing improvements in DL-based reconstruction and denoising may soon bridge the remaining gap, promising to enable the acquisition of isotropic 3D datasets with multiple contrasts within minutes. Beyond technical acceleration, the successful implementation of fast MRI requires careful workflow optimization and consideration of architectural and economic factors. This review outlines the technical principles underlying modern acceleration strategies, summarizes evidence from validation studies, discusses practical aspects of clinical implementation and protocol optimization, and highlights future opportunities and challenges.

This article provides a practice-oriented overview of current concepts in rapid musculoskeletal MRI of central and peripheral joints, focusing on echo train optimization and the application of modern acceleration techniques. Parallel imaging, simultaneous multislice acquisition, and compressed sensing-based undersampling can be applied independently or in combination to expedite MRI of the joints. Clinically available three- to eightfold acceleration of two-dimensional (2D) and three-dimensional turbo spin-echo (TSE) pulse sequences enables comprehensive 5-10-minute MRI protocols of joints. This acceleration allows for the efficient integration of advanced metal artifact reduction techniques into clinical MRI protocols. When conventional image reconstruction techniques fail, clinically available deep learning-based image reconstruction and superresolution augmentation methods effectively reconstruct images from highly accelerated acquisitions. Together, moderate acceleration and advanced image reconstruction techniques provide high diagnostic image quality of heavily undersampled MRI data, enabling three- to sixfold accelerated 2D TSE MRI of multiple joints in 4-6 minutes. Recent studies indicate that specially designed and trained deep learning methods may achieve 10-fold accelerated musculoskeletal MRI, with acquisition times under 3 minutes. Although further research and data are necessary, these promising developments are poised to enhance the value of musculoskeletal MRI.

Knee injuries are one of the most common complaints in sports medicine. Magnetic resonance imaging is an essential adjunct to clinical evaluation for many traumatic injuries and overuse conditions. Given the heavy use of knee magnetic resonance imaging, developing faster magnetic resonance imaging acquisition methods and deployment in clinical practice would be valuable. In this article, we illustrate a spectrum of knee abnormalities from our clinical practice, utilizing a recently developed, publicly available sub-5-minute knee magnetic resonance imaging protocol with super-resolution image reconstruction based on deep learning. We review common traumatic injuries and overuse conditions of the knee and illustrate cases with this novel fast knee magnetic resonance imaging protocol.

PURPOSE/OBJECTIVE:To develop expert consensus recommendations for patient selection and procedural techniques in cryoneurolysis for chronic pain management using a Delphi process. MATERIALS AND METHODS/METHODS:A panel of 22 international interventionists participated in a two-round Delphi process. Participants rated 42 statements on a 10-point Likert scale (1 = strongly disagree, 10 = strongly agree). Consensus was predefined as ≥ 75% of ratings ≥ 7. Descriptive statistics (n, mean ± SD, % ≥ 7) were calculated. RESULTS:High agreement supported cryoneurolysis for localized chronic pain refractory to conservative therapies (mean 8.55 ± 0.60; 100% ≥ 7) and cases with identifiable peripheral nerve targets (8.45 ± 0.74; 100% ≥ 7). Imaging guidance was deemed essential for nerve identification and probe placement (8.91 ± 0.29; 100% ≥ 7). The panel endorsed individualized freeze-thaw cycles to achieve Sunderland II injury (8.27 ± 0.83; 91% ≥ 7) and emphasized thorough patient education (9.0 ± 0.0; 100% ≥ 7). Experts recommended repeat cryoneurolysis within weeks if initial response was incomplete (8.64 ± 0.65; 100% ≥ 7) and alternative therapies after two unsuccessful sessions (8.36 ± 0.73; 95% ≥ 7). No consensus was reached on restricting treatment to a single anatomical region (5.82 ± 2.91; 50% ≥ 7) or routine prophylactic antibiotics (6.27 ± 2.57; 54% ≥ 7). CONCLUSION/CONCLUSIONS:This Delphi study establishes expert-derived consensus standards for cryoneurolysis, highlighting careful patient selection, mandatory imaging guidance, and flexible freeze protocols while identifying areas requiring further research.

OBJECTIVE:To assess whether accelerated knee MRI protocols using simultaneous multi-slice (SMS) and deep learning reconstruction (DLR) are non-inferior to a conventional parallel imaging protocol for detecting internal derangement injuries. METHODS:This retrospective cohort study included 1055 patients who underwent knee MRI followed by arthroscopy within 180 days. Patients were scanned using either a conventional protocol (n = 226), an accelerated SMS protocol (n = 406), or a SMS with DLR protocol (n = 423). Each group included consecutive exams. Imaging was performed on 3 T MRI using five standardized two-dimensional turbo spin echo sequences. Radiology interpretations were compared with arthroscopy (reference standard) for anterior cruciate ligament (ACL), medial meniscus (MM), and lateral meniscus (LM) tears. Sensitivity and specificity were calculated with 95% confidence intervals using non-parametric bootstrapping. Non-inferiority was concluded if the upper bound of the 95% confidence interval for the difference in sensitivity and specificity was ≤ 0.05. RESULTS:Among all patients, 666 had MM tears, 417 had LM tears, and 220 had ACL tears. Sensitivity for ACL tears was higher with accelerated protocols (0.96 and 0.98) than the conventional (0.85), with non-inferiority confirmed. Specificity was ≥ 0.98 across all protocols. MM sensitivity (0.94-0.95) met non-inferiority criteria. MM specificity (0.88-0.91) and LM sensitivity (0.63-0.68) were not statistically different across protocols but did not meet the non-inferiority margin. LM specificity (0.94) met non-inferiority criteria. CONCLUSION/CONCLUSIONS:Accelerated MRI protocols using SMS and DLR demonstrated comparable diagnostic performance to the reference protocol. Although not all metrics met the strict non-inferiority margin, none showed statistically significant reductions in sensitivity or specificity. These findings support the clinical adoption of accelerated protocols for faster, high-throughput knee imaging.

The past decade has witnessed remarkable advancements in musculoskeletal radiology, driven by increasing demand for medical imaging and rapid technological innovations. Contrary to early concerns about artificial intelligence (AI) replacing radiologists, AI has instead enhanced imaging capabilities, aiding in automated abnormality detection and workflow efficiency. MRI has benefited from acceleration techniques that significantly reduce scan times while maintaining high-quality imaging. In addition, novel MRI methodologies now support precise anatomic and quantitative imaging across a broad spectrum of field strengths. In CT, dual-energy and photon-counting technologies have expanded diagnostic possibilities for musculoskeletal applications. This review explores these key developments, examining their impact on clinical practice and the future trajectory of musculoskeletal radiology.

OBJECTIVES/OBJECTIVE:Metal artifact reduction MRI can exceed specific absorption rate (SAR) limits due to high-bandwidth radiofrequency pulses, causing scan interruptions and prolonged acquisition times. The aim of the current study is to reduce SAR and potentially scan time in metal artifact reduction MRI using an optimized variable refocusing flip angle (VRFA) scheme compared with the standard constant refocusing flip angle (CRFA). MATERIALS AND METHODS/METHODS:Three VRFA variants (VRFA1 to VRFA3) were developed to maximize tissue signal and contrast while minimizing SAR and image blur. The optimal variant was selected through quantification of metal artifacts and image blur in phantoms and tissue signal in a volunteer. Patients with hip arthroplasty underwent CRFA and optimal VRFA imaging using high-bandwidth turbo-spin-echo (HBW-TSE) and compressed-sensing slice-encoding-for-metal-artifact-correction (CS-SEMAC) sequences. Three readers ranked paired CRFA and VRFA scans for quality. Analyses included repeated measures ANOVA, noninferiority testing, and paired t/Wilcoxon signed-rank tests. RESULTS:CRFA and VRFA1 to VRFA3 showed no significant differences in image blur (full-width-at-half-maximum, mean ± SD, 1.9 ± 0.2 vs 1.9 ± 0.2 vs 1.9 ± 0.3 vs 1.9 ± 0.3 pixels, P = 0.06) or metal artifacts (8.2 ± 2.8 vs 8.4 ± 2.7 vs 8.4 ± 2.6 vs 8.4 ± 2.7 pixels, P = 0.57). The optimal VRFA variant (VRFA3) preserved 81% of CRFA fat-muscle contrast at 77% SAR and 70% scan time on proton-density (PD), and 94% of fluid-muscle contrast at 80% SAR and 67% scan time on short-tau-inversion-recovery (STIR). In 23 patients [mean age, 67.3 y ± 12.2 (SD); 14 females], the optimal VRFA was noninferior to CRFA in all quality metrics (all 95% CI < noninferiority margin = 0.1) and significantly reduced SAR (mean, PD-HBW-TSE/STIR-HBW-TSE/PD-CS-SEMAC/STIR-CS-SEMAC: 1.11/1.35/1.17/1.18 vs 1.85/1.83/1.49/1.46 W/kg, all P ≤ 0.001). In HBW-TSE, reduced SAR allowed longer echo trains and 15% to 32% shorter scan times. CONCLUSION/CONCLUSIONS:Metal artifact reduction MRI with VRFA reduces SAR without compromising image quality. It allows shorter acquisitions in HBW-TSE.