Faculty Bibliography

Chronic recurrent multifocal osteomyelitis is a rare noninfectious inflammatory bone disease diagnosed based on the synthesis of clinical, radiological, and pathological findings. The differential diagnostic considerations are led by multifocal infectious osteomyelitis and multifocal neoplasms. We report a case of a 9-year-old girl who emergently presented with worsening back pain, inability to walk, and normal vital signs. C-reactive protein and erythrocyte sedimentation rate were elevated, whereas the white blood cell count was normal. Initial radiographs and MRI of the spine showed multiple edematous vertebral body lesions. Subsequent whole-body MRI demonstrated multiple additional edematous bone lesions in the right half of the body, including the scapula, femur, and tibia. The lack of symmetrical bone lesion distribution indicated image-guided percutaneous core biopsy to exclude neoplastic disease. Pathological examination of an osseous core biopsy specimen showed a noninfectious osteomyelitis pattern with no findings of Langerhans cell histiocytosis, malignancy, or infectious osteomyelitis. The synthesis of clinical, radiological, and pathological findings was diagnostic of asymmetric right-sided chronic recurrent multifocal osteomyelitis, representing an atypical presentation that deviates from the typically symmetrical bilateral chronic recurrent multifocal osteomyelitis pattern.

BACKGROUND:The diagnosis of periprosthetic shoulder infection (PSI) in patients with a painful arthroplasty is challenging. Magnetic resonance imaging (MRI) may be helpful, but shoulder implant-induced metal artifacts degrade conventional MRI. Advanced metal artifact reduction (MARS) improves the visibility of periprosthetic bone and soft tissues. The purpose of our study was to determine the reliability, repeatability, and diagnostic performance of advanced MARS-MRI findings for diagnosing PSI. METHODS:Between January 2015 and December 2019, we enrolled consecutive patients suspected of having PSI at our academic hospital. All 89 participants had at least 1-year clinical follow-up and underwent standardized clinical, radiographic, and laboratory evaluations and advanced MARS-MRI. Two fellowship-trained musculoskeletal radiologists retrospectively evaluated the advanced MARS-MRI studies for findings associated with PSI in a blinded and independent fashion. Both readers repeated their evaluations after a 2-month interval. Interreader reliability and intrareader repeatability were assessed with κ coefficients. The diagnostic performance of advanced MARS-MRI for PSI was quantified using sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC). When applying the International Consensus Meeting (ICM) 2018 criteria, of the 89 participants, 22 (25%) were deemed as being infected and 67 (75%) were classified as being not infected (unlikely to have PSA and not requiring a surgical procedure during 1-year follow-up). RESULTS:The interreader reliability and intrareader repeatability of advanced MARS-MRI findings, including lymphadenopathy, joint effusion, synovitis, extra-articular fluid collection, a sinus tract, rotator cuff muscle edema, and periprosthetic bone resorption, were good (κ = 0.61 to 0.80) to excellent (κ > 0.80). Lymphadenopathy, complex joint effusion, and edematous synovitis had sensitivities of >85%, specificities of >90%, odds ratios of >3.6, and AUC values of >0.90 for diagnosing PSI. The presence of all 3 findings together yielded a PSI probability of >99%, per logistic regression analysis. CONCLUSIONS:Our study shows the clinical utility of advanced MARS-MRI for diagnosing PSI when using the ICM 2018 criteria as the reference standard. Although the reliability and diagnostic accuracy were high, these conclusions are based on our specific advanced MARS-MRI protocol interpreted by experienced musculoskeletal radiologists. Investigations with larger sample sizes are needed to confirm these results. LEVEL OF EVIDENCE/METHODS:Diagnostic Level III. See Instructions for Authors for a complete description of levels of evidence.

BACKGROUND/UNASSIGNED:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first identified in December 2019 in Wuhan, China. Although coronavirus disease-19 (COVID-19) affects every population group, the sports community and athletes require special consideration of the effects on cardiovascular, musculoskeletal, neurologic, and respiratory systems. A comprehensive understanding of imaging indications, findings, and features of COVID-19 supports appropriate imaging utilization and effective patient management and treatment. PURPOSE/UNASSIGNED:To review the spectrum of sports imaging in COVID-19 infection, organ system manifestations, vaccine effects, and complications in recreational and competitive athletes. STUDY DESIGN/UNASSIGNED:Narrative review. LEVEL OF EVIDENCE/UNASSIGNED:Levels 4 and 5. METHODS/UNASSIGNED:Based on a PubMed database search, studies describing the imaging findings of COVID-19 infection, organ system manifestations, vaccine effects, and complications in recreational and competitive athletes were included. RESULTS/UNASSIGNED:On March 11, 2020, World Health Organization officially declared COVID-19 a global pandemic. As of May 9, 2022, more than 515 million confirmed cases of COVID-19 were reported globally. While the multisystem effects of COVID-19 are incompletely understood, the role of imaging in diagnosing, monitoring, and prognosticating active disease, long-term effects, and complications is evolving. In the respiratory system, imaging plays an important role in diagnosing, characterizing, and monitoring pulmonary COVID-19 infections, barotrauma, and COVID-19-associated chronic pulmonary opacities and fibrotic-like lung changes. Ultrasonography, computed tomography, and magnetic resonance imaging aid in the timely diagnosis of ischemic, embolic, and thrombotic peripheral and central cardiovascular events, including deep venous thrombosis, pulmonary embolism, myocarditis, and stroke. COVID-19-associated musculoskeletal and peripheral nervous system manifestations include rhabdomyolysis and myonecrosis, plexus and peripheral neuropathies, Guillain-Barré syndrome, and shoulder injury related to vaccine administration. CONCLUSIONS/UNASSIGNED:In athletes, COVID-19 infections and associated effects on cardiovascular, musculoskeletal, neurologic, and respiratory systems require special consideration. With the increasing understanding of the multisystem effects of COVID-19, the role of imaging in diagnosing, monitoring, and prognosticating active disease, long-term effects, and complications is evolving. A comprehensive understanding of imaging indications, COVID-19 imaging features, and organ system effects aids in appropriate imaging utilization and effective patient management and treatments.

OBJECTIVE:Deep learning has the potential to automatically triage orthopedic emergencies, such as joint dislocations. However, due to the rarity of these injuries, collecting large numbers of images to train algorithms may be infeasible for many centers. We evaluated if the Internet could be used as a source of images to train convolutional neural networks (CNNs) for joint dislocations that would generalize well to real-world clinical cases. METHODS:We collected datasets from online radiology repositories of 100 radiographs each (50 dislocated, 50 located) for four joints: native shoulder, elbow, hip, and total hip arthroplasty (THA). We trained a variety of CNN binary classifiers using both on-the-fly and static data augmentation to identify the various joint dislocations. The best-performing classifier for each joint was evaluated on an external test set of 100 corresponding radiographs (50 dislocations) from three hospitals. CNN performance was evaluated using area under the ROC curve (AUROC). To determine areas emphasized by the CNN for decision-making, class activation map (CAM) heatmaps were generated for test images. RESULTS:The best-performing CNNs for elbow, hip, shoulder, and THA dislocation achieved high AUROCs on both internal and external test sets (internal/external AUC): elbow (1.0/0.998), hip (0.993/0.880), shoulder (1.0/0.993), THA (1.0/0.950). Heatmaps demonstrated appropriate emphasis of joints for both located and dislocated joints. CONCLUSION/CONCLUSIONS:With modest numbers of images, radiographs from the Internet can be used to train clinically-generalizable CNNs for joint dislocations. Given the rarity of joint dislocations at many centers, online repositories may be a viable source for CNN-training data.

OBJECTIVE:Periprosthetic dislocations of total hip arthroplasty (THA) are time-sensitive injuries, as the longer diagnosis and treatment are delayed, the more difficult they are to reduce. Automated triage of radiographs with dislocations could help reduce these delays. We trained convolutional neural networks (CNNs) for the detection of THA dislocations, and evaluated their generalizability by evaluating them on external datasets. METHODS:We used 357 THA radiographs from a single hospital (185 with dislocation [51.8%]) to develop and internally test a variety of CNNs to identify THA dislocation. We performed external testing of these CNNs on two datasets to evaluate generalizability. CNN performance was evaluated using area under the receiving operating characteristic curve (AUROC). Class activation mapping (CAM) was used to create heatmaps of test images for visualization of regions emphasized by the CNNs. RESULTS:Multiple CNNs achieved AUCs of 1 for both internal and external test sets, indicating good generalizability. Heatmaps showed that CNNs consistently emphasized the THA for both dislocated and located THAs. CONCLUSION/CONCLUSIONS:CNNs can be trained to recognize THA dislocation with high diagnostic performance, which supports their potential use for triage in the emergency department. Importantly, our CNNs generalized well to external data from two sources, further supporting their potential clinical utility.

Total hip arthroplasty and hip preservation surgeries have substantially increased over the past few decades. Musculoskeletal imaging and interventions are cornerstones of comprehensive postoperative care and surveillance in patients undergoing established and more recently introduced hip surgeries. Hence the radiologist's role continues to evolve and expand. A strong understanding of hip joint anatomy and biomechanics, surgical procedures, expected normal postoperative imaging appearances, and postoperative complications ensures accurate imaging interpretation, intervention, and optimal patient care. This article presents surgical principles and procedural details pertinent to postoperative imaging evaluation strategies after common hip surgeries, such as radiography, ultrasonography, computed tomography, and magnetic resonance imaging. We review and illustrate the expected postoperative imaging appearances and complications following chondrolabral repair, acetabuloplasty, osteochondroplasty, periacetabular osteotomy, realigning and derotational femoral osteotomies, and hip arthroplasty.

OBJECTIVES/OBJECTIVE:To test whether a 4-fold accelerated 3D T2-weighted (T2) CAIPIRINHA SPACE TSE sequence with isotropic voxel size is equivalent to conventional 2DT2 TSE for the evaluation of intrinsic and perilesional soft tissue tumors (STT) characteristics. METHODS:For 108 patients with histologically-proven STTs, MRI, including 3DT2 (CAIPIRINHA SPACE TSE) and 2DT2 (TSE) sequences, was performed. Two radiologists evaluated each sequence for quality (diagnostic, non-diagnostic), tumor characteristics (heterogeneity, signal intensity, margin), and the presence or absence of cortical involvement, marrow edema, and perilesional edema (PLE); tumor size and PLE extent were measured. Signal-to-noise (SNR) and contrast-to-noise (CNR) ratios and acquisition times for 2DT2 in two planes and 3DT2 sequences were reported. Descriptive statistics and inter-method agreement were reported. RESULTS:Image quality was diagnostic for all sequences (100% [108/108]). No difference was observed between 3DT2 and 2DT2 tumor characteristics (p < 0.05). There was no difference in mean tumor size (3DT2: 2.9 ± 2.5 cm, 2DT2: 2.8 ± 2.6 cm, p = 0.4) or PLE extent (3DT2:0.5 ± 1.2 cm, 2DT2:0.5 ± 1.0 cm, p = 0.9) between the sequences. There was no difference in the SNR of tumors, marrow, and fat between the sequences, whereas the SNR of muscle was higher (p < 0.05) on 3DT2 than 2DT2. CNR measures on 3DT2 were similar to 2DT2 (p > 0.1). The average acquisition time was shorter for 3DT2 compared with 2DT2 (343 ± 127 s vs 475 ± 162 s, respectively). CONCLUSION/CONCLUSIONS:Isotropic 3DT2 MRI offers higher spatial resolution, faster acquisition times, and equivalent assessments of STT characteristics compared to conventional 2DT2 MRI in two planes. 3DT2 is interchangeable with a 2DT2 sequence in tumor protocols. KEY POINTS/CONCLUSIONS:• Isotropic 3DT2 CAIPIRINHA SPACE TSE offers higher spatial resolution than 2DT2 TSE and is equivalent to 2DT2 TSE for assessments of soft tissue tumor intrinsic and perilesional characteristics. • Multiplanar reformats of 3DT2 CAIPIRINHA SPACE TSE can substitute for 2DT2 TSE acquired in multiple planes, thereby reducing the acquisition time of MRI tumor protocols. • 3DT2 CAIPIRINHA SPACE TSE and 2DT2 TSE had similar CNR of tissues.

A standardized guideline and scoring system should be used for the MR imaging diagnosis of peripheral neuropathy. The MR imaging-based Neuropathy Score Reporting and Data System (NS-RADS) is a newly devised classification system (in press in AJR) that can be used to communicate both type and severity of peripheral neuropathy in the light of clinical history and examination findings. The spectrum of neuropathic conditions and peripheral nerve disorders covered in this system includes nerve injury, entrapment, neoplasm, diffuse neuropathy, and post-interventional states. This classification system also describes the temporal MR imaging appearances of regional muscle denervation changes. This review article is based on the multicenter validation study pre-published in American journal of Roentgenology and discusses technical considerations of optimal MR imaging for peripheral nerve evaluation and discusses the NS-RADS classification and its severity scales with illustration of conditions that fall under each classification. The readers can gain knowledge of the NS-RADS classification system and learn to apply it in their practices for improved inter-disciplinary communications and timely patient management.