Faculty Bibliography

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.

Dual-energy computed tomography (DECT) has emerged as a transformative tool in the past decade. Initially employed in gout within the field of rheumatology to distinguish and quantify monosodium urate crystals through its dual-material discrimination capability, DECT has since broadened its clinical applications. It now encompasses various rheumatic diseases, employing advanced techniques such as bone marrow edema assessment, iodine mapping, and collagen-specific imaging. This review article aims to examine the unique characteristics of DECT, discuss its strengths and limitations, illustrate its applications for accurately evaluating various rheumatic diseases in clinical practice, and propose future directions for DECT in rheumatology.

Background Conventional chemical shift selective (CHESS) fat suppression may fail in distal extremity MRI due to sensitivity to field inhomogeneities. Purpose To develop a patient-specific fat-suppression method for distal extremity 3-T MRI by exploiting the spectral heterogeneity adaptive radiofrequency pulse (SHARP) technique and to compare it to fat suppression with CHESS. Materials and Methods SHARP uses the routinely acquired frequency spectrum at MRI calibration to adapt the frequency range and time-bandwidth product of the fat-suppression pulse. In this prospective study, fat suppression by SHARP was assessed by numerical simulations, phantom experiments, and imaging in 15 asymptomatic participants who underwent ankle, foot, and hand (in superman and hand-by-the-side positions) MRI using SHARP, CHESS, and reference standard (short-tau inversion recovery or Dixon) techniques. Three readers ranked the MRI scans from 1 (best) to 3 (worst) regarding fat-suppression homogeneity. The added value of SHARP was defined as the difference between the proportions of images where SHARP outranked CHESS and where CHESS outranked SHARP. Friedman, Wilcoxon signed rank, and χ² tests were used to compare in vivo data. Results At numerical simulations, SHARP showed 0% water and 62%-70% fat suppression, whereas CHESS showed 2% water and 57% fat suppression. Phantom data demonstrated lower fat-suppression inhomogeneity indexes with Dixon (1.0%) and SHARP (2.4%) compared with CHESS (10.7%). In 15 participants (mean age, 38.5 years ± 12.8 [SD]; six female participants), mean ranking by readers of fat homogeneity in the reference technique (ankle, foot, hand in superman position, and hand-by-the-side position: 1.02, 1.02, 1.03, and 1.06, respectively) was higher than those with SHARP (1.39, 1.46, 1.50, and 1.66, respectively), which were higher than those with CHESS (1.64, 1.80, 1.61, and 1.80, respectively) (all P < .001). The added value of SHARP was highest for images in the foot (389 of 1158; 33.6%; P < .001 vs other joints), followed by the ankle (247 of 971 [25%]; P < .001 vs both hand positions), and lowest for hand-by-the-side and hand in superman positions (158 of 1223; [13%] and 133 of 1193 [11%], respectively; P = .18). Conclusion SHARP provided more homogeneous fat suppression than CHESS. © RSNA, 2024 Supplemental material is available for this article.

OBJECTIVE:To determine the inter-reader reliability and diagnostic performance of classification and severity scales of Neuropathy Score Reporting And Data System (NS-RADS) among readers of differing experience levels after limited teaching of the scoring system. METHODS:This is a multi-institutional, cross-sectional, retrospective study of MRI cases of proven peripheral neuropathy (PN) conditions. Thirty-two radiology readers with varying experience levels were recruited from different institutions. Each reader attended and received a structured presentation that described the NS-RADS classification system containing examples and reviewed published articles on this subject. The readers were then asked to perform NS-RADS scoring with recording of category, subcategory, and most likely diagnosis. Inter-reader agreements were evaluated by Conger's kappa and diagnostic accuracy was calculated for each reader as percent correct diagnosis. A linear mixed model was used to estimate and compare accuracy between trainees and attendings. RESULTS:Across all readers, agreement was good for NS-RADS category and moderate for subcategory. Inter-reader agreement of trainees was comparable to attendings (0.65 vs 0.65). Reader accuracy for attendings was 75% (95% CI 73%, 77%), slightly higher than for trainees (71% (69%, 72%), p = 0.0006) for nerves and comparable for muscles (attendings, 87.5% (95% CI 86.1-88.8%) and trainees, 86.6% (95% CI 85.2-87.9%), p = 0.4). NS-RADS accuracy was also higher than average accuracy for the most plausible diagnosis for attending radiologists at 67% (95% CI 63%, 71%) and for trainees at 65% (95% CI 60%, 69%) (p = 0.036). CONCLUSION/CONCLUSIONS:Non-expert radiologists interpreted PN conditions with good accuracy and moderate-to-good inter-reader reliability using the NS-RADS scoring system. CLINICAL RELEVANCE STATEMENT/CONCLUSIONS:The Neuropathy Score Reporting And Data System (NS-RADS) is an accurate and reliable MRI-based image scoring system for practical use for the diagnosis and grading of severity of peripheral neuromuscular disorders by both experienced and general radiologists. KEY POINTS/CONCLUSIONS:• The Neuropathy Score Reporting And Data System (NS-RADS) can be used effectively by non-expert radiologists to categorize peripheral neuropathy. • Across 32 different experience-level readers, the agreement was good for NS-RADS category and moderate for NS-RADS subcategory. • NS-RADS accuracy was higher than the average accuracy for the most plausible diagnosis for both attending radiologists and trainees (at 75%, 71% and 65%, 65%, respectively).

MRI is an expensive and traditionally time-intensive modality in imaging. With the paradigm shift toward value-based healthcare, radiology departments must examine the entire MRI process cycle to identify opportunities to optimize efficiency and enhance value for patients. Digital tools such as "frictionless scheduling" prioritize patient preference and convenience, thereby delivering patient-centered care. Recent advances in conventional and deep learning-based accelerated image reconstruction methods have reduced image acquisition time to such a degree that so-called nongradient time now constitutes a major percentage of total room time. For this reason, architectural design strategies that reconfigure patient preparation processes and decrease the turnaround time between scans can substantially impact overall throughput while also improving patient comfort and privacy. Real-time informatics tools that provide an enterprise-wide overview of MRI workflow and Picture Archiving and Communication System (PACS)-integrated instant messaging can complement these efforts by offering transparent, situational data and facilitating communication between radiology team members. Finally, long-term investment in training, recruiting, and retaining a highly skilled technologist workforce is essential for building a pipeline and team of technologists committed to excellence. Here, we highlight various opportunities for optimizing MRI workflow and enhancing value by offering many of our own on-the-ground experiences and conclude by anticipating some of the future directions for process improvement and innovation in clinical MR imaging. EVIDENCE LEVEL: N/A TECHNICAL EFFICACY: Stage 1.

OBJECTIVES/OBJECTIVE:Early, accurate diagnosis is crucial for the prognosis of patients with soft tissue sarcomas. To this end, standardization of imaging algorithms, technical requirements, and reporting is therefore a prerequisite. Since the first European Society of Musculoskeletal Radiology (ESSR) consensus in 2015, technical achievements, further insights into specific entities, and the revised WHO-classification (2020) and AJCC staging system (2017) made an update necessary. The guidelines are intended to support radiologists in their decision-making and contribute to interdisciplinary tumor board discussions. MATERIALS AND METHODS/METHODS:A validated Delphi method based on peer-reviewed literature was used to derive consensus among a panel of 46 specialized musculoskeletal radiologists from 12 European countries. Statements were scored online by level of agreement (0 to 10) during two iterative rounds. Either "group consensus," "group agreement," or "lack of agreement" was achieved. RESULTS:Eight sections were defined that finally contained 145 statements with comments. Overall, group consensus was reached in 95.9%, and group agreement in 4.1%. This communication contains the first part consisting of the imaging algorithm for suspected soft tissue tumors, methods for local imaging, and the role of tumor centers. CONCLUSION/CONCLUSIONS:Ultrasound represents the initial triage imaging modality for accessible and small tumors. MRI is the modality of choice for the characterization and local staging of most soft tissue tumors. CT is indicated in special situations. In suspicious or likely malignant tumors, a specialist tumor center should be contacted for referral or teleradiologic second opinion. This should be done before performing a biopsy, without exception. CLINICAL RELEVANCE/CONCLUSIONS:The updated ESSR soft tissue tumor imaging guidelines aim to provide best practice expert consensus for standardized imaging, to support radiologists in their decision-making, and to improve examination comparability both in individual patients and in future studies on individualized strategies. KEY POINTS/CONCLUSIONS:• Ultrasound remains the best initial triage imaging modality for accessible and small suspected soft tissue tumors. • MRI is the modality of choice for the characterization and local staging of soft tissue tumors in most cases; CT is indicated in special situations. Suspicious or likely malignant tumors should undergo biopsy. • In patients with large, indeterminate or suspicious tumors, a tumor reference center should be contacted for referral or teleradiologic second opinion; this must be done before a biopsy.

OBJECTIVE:Direct magnetic resonance arthrography (dMRA) is often considered the most accurate imaging modality for the evaluation of intra-articular structures, but utilization and performance vary widely without consensus. The purpose of this white paper is to develop consensus recommendations on behalf of the Society of Skeletal Radiology (SSR) based on published literature and expert opinion. MATERIALS AND METHODS/METHODS:The Standards and Guidelines Committee of the SSR identified guidelines for utilization and performance of dMRA as an important topic for study and invited all SSR members with expertise and interest to volunteer for the white paper panel. This panel was tasked with determining an outline, reviewing the relevant literature, preparing a written document summarizing the issues and controversies, and providing recommendations. RESULTS:Twelve SSR members with expertise in dMRA formed the ad hoc white paper authorship committee. The published literature on dMRA was reviewed and summarized, focusing on clinical indications, technical considerations, safety, imaging protocols, complications, controversies, and gaps in knowledge. Recommendations for the utilization and performance of dMRA in the shoulder, elbow, wrist, hip, knee, and ankle/foot regions were developed in group consensus. CONCLUSION/CONCLUSIONS:Although direct MR arthrography has been previously used for a wide variety of clinical indications, the authorship panel recommends more selective application of this minimally invasive procedure. At present, direct MR arthrography remains an important procedure in the armamentarium of the musculoskeletal radiologist and is especially valuable when conventional MRI is indeterminant or results are discrepant with clinical evaluation.

While musculoskeletal imaging volumes are increasing, there is a relative shortage of subspecialized musculoskeletal radiologists to interpret the studies. Will artificial intelligence (AI) be the solution? For AI to be the solution, the wide implementation of AI-supported data acquisition methods in clinical practice requires establishing trusted and reliable results. This implementation will demand close collaboration between core AI researchers and clinical radiologists. Upon successful clinical implementation, a wide variety of AI-based tools can improve the musculoskeletal radiologist's workflow by triaging imaging examinations, helping with image interpretation, and decreasing the reporting time. Additional AI applications may also be helpful for business, education, and research purposes if successfully integrated into the daily practice of musculoskeletal radiology. The question is not whether AI will replace radiologists, but rather how musculoskeletal radiologists can take advantage of AI to enhance their expert capabilities.