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Designing Clinical MRI for Enhanced Workflow and Value

Lin, Dana J; Doshi, Ankur M; Fritz, Jan; Recht, Michael P
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.
PMID: 37795927
ISSN: 1522-2586
CID: 5664522

SSR white paper: guidelines for utilization and performance of direct MR arthrography

Chang, Eric Y; Bencardino, Jenny T; French, Cristy N; Fritz, Jan; Hanrahan, Chris J; Jibri, Zaid; Kassarjian, Ara; Motamedi, Kambiz; Ringler, Michael D; Strickland, Colin D; Tiegs-Heiden, Christin A; Walker, Richard E A
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.
PMID: 37566148
ISSN: 1432-2161
CID: 5613412

Correction to: SSR white paper: guidelines for utilization and performance of direct MR arthrography

Chang, Eric Y; Bencardino, Jenny T; French, Cristy N; Fritz, Jan; Hanrahan, Chris J; Jibri, Zaid; Kassarjian, Ara; Motamedi, Kambiz; Ringler, Michael D; Strickland, Colin D; Tiegs-Heiden, Christin A; Walker, Richard E A
PMID: 37695344
ISSN: 1432-2161
CID: 5593662

MRI-based Neuropathy Score Reporting And Data System (NS-RADS): multi-institutional wider-experience usability study of peripheral neuropathy conditions among 32 radiology readers

Chhabra, Avneesh; Duarte Silva, Flavio; Mogharrabi, Bayan; Guirguis, Mina; Ashikyan, Oganes; Rasper, Michael; Park, Eunhae; Walter, Sven S.; Umpierrez, Monica; Pezeshk, Parham; Thurlow, Peter C.; Jagadale, Akshaya; Bajaj, Gitanjali; Komarraju, Aparna; Wu, Jim S.; Aguilera, Antonio; Cardoso, Fabiano Nassar; Souza, Felipe; Chaganti, Subba Rao; Antil, Neha; Manzano, Wilfred; Stebner, Alexander; Evers, Jochen; Petterson, Matthew; Geisbush, Thomas; Downing, Chad; Christensen, Diana; Horneber, Elizabeth; Kim, Jun Man; Purushothaman, Rangarajan; Mohanan, Shilpa; Raichandani, Surbhi; Vilanilam, George; Cabrera, Clementina; Manov, John; Maloney, Sean; Deshmukh, Swati D.; Lutz, Amelie M.; Fritz, Jan; Andreisek, Gustav; Chalian, Majid; Wong, Philip K.; Pandey, Tarun; Subhawong, Ty; Xi, Yin
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: 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: 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: "¢ 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).
ISSN: 0938-7994
CID: 5629572

How AI May Transform Musculoskeletal Imaging

Guermazi, Ali; Omoumi, Patrick; Tordjman, Mickael; Fritz, Jan; Kijowski, Richard; Regnard, Nor-Eddine; Carrino, John; Kahn, Charles E; Knoll, Florian; Rueckert, Daniel; Roemer, Frank W; Hayashi, Daichi
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.
PMID: 38165245
ISSN: 1527-1315
CID: 5625952

Imaging approach to prosthetic joint infection

Jardon, Meghan; Fritz, Jan; Samim, Mohammad
The diagnosis of prosthetic joint infection (PJI) remains challenging, despite multiple available laboratory tests for both serum and synovial fluid analysis. The clinical symptoms of PJI are not always characteristic, particularly in the chronic phase, and there is often significant overlap in symptoms with non-infectious forms of arthroplasty failure. Further exacerbating this challenge is lack of a universally accepted definition for PJI, with publications from multiple professional societies citing different diagnostic criteria. While not included in many of the major societies' guidelines for diagnosis of PJI, diagnostic imaging can play an important role in the workup of suspected PJI. In this article, we will review an approach to diagnostic imaging modalities (radiography, ultrasound, CT, MRI) in the workup of suspected PJI, with special attention to the limitations and benefits of each modality. We will also discuss the role that image-guided interventions play in the workup of these patients, through ultrasound and fluoroscopically guided joint aspirations. While there is no standard imaging algorithm that can universally applied to all patients with suspected PJI, we will discuss a general approach to diagnostic imaging and image-guided intervention in this clinical scenario.
PMID: 38133670
ISSN: 1432-2161
CID: 5612252

Soft tissue tumor imaging in adults: European Society of Musculoskeletal Radiology-Guidelines 2023-overview, and primary local imaging: how and where?

Noebauer-Huhmann, Iris-Melanie; Vanhoenacker, Filip M; Vilanova, Joan C; Tagliafico, Alberto S; Weber, Marc-André; Lalam, Radhesh K; Grieser, Thomas; Nikodinovska, Violeta Vasilevska; de Rooy, Jacky W J; Papakonstantinou, Olympia; Mccarthy, Catherine; Sconfienza, Luca Maria; Verstraete, Koenraad; Martel-Villagrán, José; Szomolanyi, Pavol; Lecouvet, Frédéric E; Afonso, Diana; Albtoush, Omar M; Aringhieri, Giacomo; Arkun, Remide; Aström, Gunnar; Bazzocchi, Alberto; Botchu, Rajesh; Breitenseher, Martin; Chaudhary, Snehansh; Dalili, Danoob; Davies, Mark; de Jonge, Milko C; Mete, Berna D; Fritz, Jan; Gielen, Jan L M A; Hide, Geoff; Isaac, Amanda; Ivanoski, Slavcho; Mansour, Ramy M; Muntaner-Gimbernat, Lorenzo; Navas, Ana; O Donnell, Paul; Örgüç, Şebnem; Rennie, Winston; Resano, Santiago; Robinson, Philip; Sanal, Hatice T; Ter Horst, Simone A J; van Langevelde, Kirsten; Wörtler, Klaus; Koelz, Marita; Panotopoulos, Joannis; Windhager, Reinhard; Bloem, Johannes L
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.
PMID: 38062268
ISSN: 1432-1084
CID: 5591492

Deep learning applications in osteoarthritis imaging

Kijowski, Richard; Fritz, Jan; Deniz, Cem M
Deep learning (DL) is one of the most exciting new areas in medical imaging. This article will provide a review of current applications of DL in osteoarthritis (OA) imaging, including methods used for cartilage lesion detection, OA diagnosis, cartilage segmentation, and OA risk assessment. DL techniques have been shown to have similar diagnostic performance as human readers for detecting and grading cartilage lesions within the knee on MRI. A variety of DL methods have been developed for detecting and grading the severity of knee OA and various features of knee OA on X-rays using standardized classification systems with diagnostic performance similar to human readers. Multiple DL approaches have been described for fully automated segmentation of cartilage and other knee tissues and have achieved higher segmentation accuracy than currently used methods with substantial reductions in segmentation times. Various DL models analyzing baseline X-rays and MRI have been developed for OA risk assessment. These models have shown high diagnostic performance for predicting a wide variety of OA outcomes, including the incidence and progression of radiographic knee OA, the presence and progression of knee pain, and future total knee replacement. The preliminary results of DL applications in OA imaging have been encouraging. However, many DL techniques require further technical refinement to maximize diagnostic performance. Furthermore, the generalizability of DL approaches needs to be further investigated in prospective studies using large image datasets acquired at different institutions with different imaging hardware before they can be implemented in clinical practice and research studies.
PMID: 36759367
ISSN: 1432-2161
CID: 5626272

Selective MR neurography-guided lumbosacral plexus perineural injections: techniques, targets, and territories

Dalili, Danoob; Isaac, Amanda; Fritz, Jan
The T12 to S4 spinal nerves form the lumbosacral plexus in the retroperitoneum, providing sensory and motor innervation to the pelvis and lower extremities. The lumbosacral plexus has a wide range of anatomic variations and interchange of fibers between nerve anastomoses. Neuropathies of the lumbosacral plexus cause a broad spectrum of complex pelvic and lower extremity pain syndromes, which can be challenging to diagnose and treat successfully. In their workup, selective nerve blocks are employed to test the hypothesis that a lumbosacral plexus nerve contributes to a suspected pelvic and extremity pain syndrome, whereas therapeutic perineural injections aim to alleviate pain and paresthesia symptoms. While the sciatic and femoral nerves are large in caliber, the iliohypogastric and ilioinguinal, genitofemoral, lateral femoral cutaneous, anterior femoral cutaneous, posterior femoral cutaneous, obturator, and pudendal nerves are small, measuring a few millimeters in diameter and have a wide range of anatomic variants. Due to their minuteness, direct visualization of the smaller lumbosacral plexus branches can be difficult during selective nerve blocks, particularly in deeper pelvic locations or larger patients. In this setting, the high spatial and contrast resolution of interventional MR neurography guidance benefits nerve visualization and targeting, needle placement, and visualization of perineural injectant distribution, providing a highly accurate alternative to more commonly used ultrasonography, fluoroscopy, and computed tomography guidance for perineural injections. This article offers a practical guide for MR neurography-guided lumbosacral plexus perineural injections, including interventional setup, pulse sequence protocols, lumbosacral plexus MR neurography anatomy, anatomic variations, and injection targets.
PMID: 37495713
ISSN: 1432-2161
CID: 5597922

Interdisciplinary consensus statements on imaging of DRUJ instability and TFCC injuries

Cerezal, Luis; Del Piñal, Francisco; Atzei, Andrea; Schmitt, Rainer; Becce, Fabio; Klich, Maciej; Bień, Maciej; de Jonge, Milko C; Teh, James; Boutin, Robert Downey; Toms, Andoni Paul; Omoumi, Patrick; Fritz, Jan; Bazzocchi, Alberto; Shahabpour, Maryam; Zanetti, Marco; Llopis, Eva; Blum, Alain; Lalam, Radhesh Krishna; Reto, Sutter; Afonso, P Diana; Mascarenhas, Vasco V; Cotten, Anne; Drapé, Jean-Luc; Bierry, Guillaume; Pracoń, Grzegorz; Dalili, Danoob; Mespreuve, Marc; Garcia-Elias, Marc; Bain, Gregory Ian; Mathoulin, Christophe L; Van Overstraeten, Luc; Szabo, Robert M; Camus, Emmanuel J; Luchetti, Riccardo; Chojnowski, Adrian Julian; Gruenert, Joerg G; Czarnecki, Piotr; Corella, Fernando; Nagy, Ladislav; Yamamoto, Michiro; Golubev, Igor O; van Schoonhoven, Jörg; Goehtz, Florian; Sudoł-Szopińska, Iwona; Dietrich, Tobias Johannes
OBJECTIVES/OBJECTIVE:The purpose of this agreement was to establish evidence-based consensus statements on imaging of distal radioulnar joint (DRUJ) instability and triangular fibrocartilage complex (TFCC) injuries by an expert group using the Delphi technique. METHODS:Nineteen hand surgeons developed a preliminary list of questions on DRUJ instability and TFCC injuries. Radiologists created statements based on the literature and the authors' clinical experience. Questions and statements were revised during three iterative Delphi rounds. Delphi panelists consisted of twenty-seven musculoskeletal radiologists. The panelists scored their degree of agreement to each statement on an 11-item numeric scale. Scores of "0," "5," and "10" reflected complete disagreement, indeterminate agreement, and complete agreement, respectively. Group consensus was defined as a score of "8" or higher for 80% or more of the panelists. RESULTS:Three of fourteen statements achieved group consensus in the first Delphi round and ten statements achieved group consensus in the second Delphi round. The third and final Delphi round was limited to the one question that did not achieve group consensus in the previous rounds. CONCLUSIONS:Delphi-based agreements suggest that CT with static axial slices in neutral rotation, pronation, and supination is the most useful and accurate imaging technique for the work-up of DRUJ instability. MRI is the most valuable technique in the diagnosis of TFCC lesions. The main indication for MR arthrography and CT arthrography are Palmer 1B foveal lesions of the TFCC. CLINICAL RELEVANCE STATEMENT/CONCLUSIONS:MRI is the method of choice for assessing TFCC lesions, with higher accuracy for central than peripheral abnormalities. The main indication for MR arthrography is the evaluation of TFCC foveal insertion lesions and peripheral non-Palmer injuries. KEY POINTS/CONCLUSIONS:• Conventional radiography should be the initial imaging technique in the assessment of DRUJ instability. CT with static axial slices in neutral rotation, pronation, and supination is the most accurate method for evaluating DRUJ instability. • MRI is the most useful technique in diagnosing soft-tissue injuries causing DRUJ instability, especially TFCC lesions. • The main indications for MR arthrography and CT arthrography are foveal lesions of the TFCC.
PMID: 37191922
ISSN: 1432-1084
CID: 5503532