Diagnostic Performance of Advanced Metal Artifact Reduction MRI for Periprosthetic Shoulder Infection

How AI May Transform Musculoskeletal Imaging

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.

Imaging approach to prosthetic joint infection

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.

Compressed Sensing SEMAC MRI of Hip, Knee, and Ankle Arthroplasty Implants: A 1.5-T and 3-T Intrapatient Performance Comparison for Diagnosing Periprosthetic Abnormalities

BACKGROUND. The utility of 3-T MRI for diagnosing joint disorders is established, but its performance for diagnosing abnormalities around arthroplasty implants is unclear. OBJECTIVE. The purpose of this study was to compare 1.5-T and 3-T compressed sensing slice encoding for metal artifact correction (SEMAC) MRI for diagnosing peri-prosthetic abnormalities around hip, knee, and ankle arthroplasty implants. METHODS. Forty-five participants (26 women, 19 men; mean age ± SD, 71 ± 14 years) with symptomatic lower extremity arthroplasty (hip, knee, and ankle, 15 each) prospectively underwent consecutive 1.5- and 3-T MRI examinations with intermediate-weighted (IW) and STIR compressed sensing SEMAC sequences. Using a Likert scale, three radiologists evaluated the presence or absence of periprosthetic abnormalities, including bone marrow edema-like signal, osteolysis, stress reaction/fracture, synovitis, and tendon abnormalities and collections; image quality; and visibility of anatomic structures. Statistical analysis included nonparametric comparison and interchangeability testing. RESULTS. For diagnosing periprosthetic abnormalities, 1.5-T and 3-T compressed sensing SEMAC MRI were interchangeable. Across all three joints, 3-T MRI had lower noise than 1.5-T MRI (median IW and STIR scores at 3 T vs 1.5 T, 4 and 4 [range, 2-5 and 3-5] vs 3 and 3 [range, 2-5 and 2-4]; p < .01 for both), sharper edges (median IW and STIR scores at 3 T vs 1.5 T, 4 and 4 [both ranges, 2-5] vs 3 and 3 [range, 2-4 and 2-5]; p < .02 and p < .05), and more effective metal artifact reduction (median IW and STIR scores at 3 T vs 1.5 T, 4 and 4 [range, 3-5 and 2-5] vs 4 and 4 [both ranges, 3-5]; p < .02 and p = .72). Agreement was moderate to substantial for image contrast (IW and STIR, 0.66 and 0.54 [95% CI, 0.41-0.91 and 0.29-0.80]; p = .58 and p = .16) and joint capsule visualization (IW and STIR, 0.57 and 0.70 [range, 0.32-0.81 and 0.51-0.89]; p = .16 and p = .19). The bone-implant interface was more visible at 1.5 T (median IW and STIR scores, 4 and 4 [both ranges, 2-5] at 1.5 T vs 3 and 3 [both ranges, 2-5] at 3 T; p = .08 and p = .58), but periprosthetic tissues had superior visibility at 3 T (IW and STIR, 4 and 4 [both ranges, 3-5] at 3 T vs 4 and 4 [ranges, 2-5 and 3-5] at 1.5 T; p = .07 and p = .19). CONCLUSION. Optimized 1.5-T and 3-T compressed sensing SEMAC MRI are interchangeable for diagnosing periprosthetic abnormalities, although metallic artifacts are larger at 3 T. CLINICAL IMPACT. With compressed sensing SEMAC MRI, lower extremity arthroplasty implants can be imaged at 3 T rather than 1.5 T.

The role of advanced metal artifact reduction MRI in the diagnosis of periprosthetic joint infection

Identification and diagnosis of periprosthetic joint infection (PJI) are challenging, requiring a multi-disciplinary approach involving clinical evaluation, laboratory tests, and imaging studies. MRI is advantageous to alternative imaging techniques due to superior soft tissue contrast and absence of ionizing radiation. However, the presence of metallic implants can cause signal loss and artifacts. Metal artifact suppression (MARS) MRI techniques have been developed that mitigate metal artifacts and improve periprosthetic soft tissue visualization. This paper provides a review of the various MARS MRI techniques, their clinical applicability and accuracy in PJI diagnosis and evaluation, and current challenges and future perspectives.

Magnetic Resonance Imaging of Total Ankle Arthroplasty: State-of-The-Art Assessment of Implant-Related Pain and Dysfunction

Total ankle arthroplasty (TAA) is an effective alternative for treating patients with end-stage ankle degeneration, improving mobility, and providing pain relief. Implant survivorship is constantly improving; however, complications occur. Many causes of pain and dysfunction after total ankle arthroplasty can be diagnosed accurately with clinical examination, laboratory, radiography, and computer tomography. However, when there are no or inconclusive imaging findings, magnetic resonance imaging (MRI) is highly accurate in identifying and characterizing bone resorption, osteolysis, infection, osseous stress reactions, nondisplaced fractures, polyethylene damage, nerve injuries and neuropathies, as well as tendon and ligament tears. Multiple vendors offer effective, clinically available MRI techniques for metal artifact reduction MRI of total ankle arthroplasty. This article reviews the MRI appearances of common TAA implant systems, clinically available techniques and protocols for metal artifact reduction MRI of TAA implants, and the MRI appearances of a broad spectrum of TAA-related complications.

Metal Artifact Reduction MRI in the Diagnosis of Periprosthetic Hip Joint Infection

A 54-year-old woman presented with progressive right hip pain after hip arthroplasty 9 years earlier. The emerging role of metal artifact reduction MRI in the noninvasive diagnosis of infectious synovitis as the surrogate marker for periprosthetic hip joint infection and differentiation from other synovitis types is discussed.

MR Imaging of Acute Knee Injuries: Systematic Evaluation and Reporting

Acute knee injury ranges among the most common joint injuries in professional and recreational athletes. Radiographs can detect joint effusion, fractures, deformities, and malalignment; however, MR imaging is most accurate for radiographically occult fractures, chondral injury, and soft tissue injuries. Using a structured checklist approach for systematic MR imaging evaluation and reporting, this article reviews the MR imaging appearances of the spectrum of traumatic knee injuries, including osteochondral injuries, cruciate ligament tears, meniscus tears and ramp lesions, anterolateral complex and collateral ligament injuries, patellofemoral translation, extensor mechanism tears, and nerve and vascular injuries.

[Shoulder periprosthetic infections-what to do? : Diagnosis and treatment]

Treatment of an infected shoulder prosthesis differs significantly from other joint infections because of the unique microbiome, dominated by Cutibacterium acnes. The cause of an infection, its time of onset, the bacterial spectrum and comorbidities have to be considered for evaluation and treatment. The diagnostic workup is sometimes complex, and the recognition of a chronic and low-grade infection is often difficult because typical clinical and laboratory markers may be normal. Treatment is surgical; the therapeutic spectrum ranges from arthroscopic irrigation and open debridement with the exchange of components to one- and two-stage revisions using antibiotic-loaded spacers. Early detection and a targeted, appropriate therapy are crucial to avoid extensive soft tissue and bone damage.

Artificial Intelligence-Driven Ultra-Fast Superresolution MRI: 10-Fold Accelerated Musculoskeletal Turbo Spin Echo MRI Within Reach

ABSTRACT

Magnetic resonance imaging (MRI) is the keystone of modern musculoskeletal imaging; however, long pulse sequence acquisition times may restrict patient tolerability and access. Advances in MRI scanners, coil technology, and innovative pulse sequence acceleration methods enable 4-fold turbo spin echo pulse sequence acceleration in clinical practice; however, at this speed, conventional image reconstruction approaches the signal-to-noise limits of temporal, spatial, and contrast resolution. Novel deep learning image reconstruction methods can minimize signal-to-noise interdependencies to better advantage than conventional image reconstruction, leading to unparalleled gains in image speed and quality when combined with parallel imaging and simultaneous multislice acquisition. The enormous potential of deep learning-based image reconstruction promises to facilitate the 10-fold acceleration of the turbo spin echo pulse sequence, equating to a total acquisition time of 2-3 minutes for entire MRI examinations of joints without sacrificing spatial resolution or image quality. Current investigations aim for a better understanding of stability and failure modes of image reconstruction networks, validation of network reconstruction performance with external data sets, determination of diagnostic performances with independent reference standards, establishing generalizability to other centers, scanners, field strengths, coils, and anatomy, and building publicly available benchmark data sets to compare methods and foster innovation and collaboration between the clinical and image processing community. In this article, we review basic concepts of deep learning-based acquisition and image reconstruction techniques for accelerating and improving the quality of musculoskeletal MRI, commercially available and developing deep learning-based MRI solutions, superresolution, denoising, generative adversarial networks, and combined strategies for deep learning-driven ultra-fast superresolution musculoskeletal MRI. This article aims to equip radiologists and imaging scientists with the necessary practical knowledge and enthusiasm to meet this exciting new era of musculoskeletal MRI.

Advances in Bone Joint Imaging-Metal Artifact Reduction

Numerous types of metal implants have been introduced in orthopedic surgery and are used in everyday practice. To precisely evaluate the postoperative condition of arthroplasty or trauma surgery, periprosthetic infection, and the loosening of implants, it is important to reduce artifacts induced by metal implants. In this review, we focused on technical advances in metal artifact reduction using digital tomosynthesis, computed tomography, and magnetic resonance imaging. We discussed new developments in diagnostic imaging methods and the continuous introduction of novel technologies to reduce metal artifacts; however, these innovations have not yet completely removed metal artifacts. Different algorithms need to be selected depending on the size, shape, material and implanted body parts of an implant. Future advances in metal artifact reduction algorithms and techniques and the development of new sequences may enable further reductions in metal artifacts even on original images taken previously. Moreover, the combination of different imaging modalities may contribute to further reductions in metal artifacts. Clinicians must constantly update their knowledge and work closely with radiologists to select the best diagnostic imaging method for each metal implant.