Consensus for experimental design in electromyography (CEDE) project: Checklist for reporting and critically appraising studies using EMG (CEDE-Check).

The diversity in electromyography (EMG) techniques and their reporting present significant challenges across multiple disciplines in research and clinical practice, where EMG is commonly used. To address these challenges and augment the reproducibility and interpretation of studies using EMG, the Consensus for Experimental Design in Electromyography (CEDE) project has developed a checklist (CEDE-Check) to assist researchers to thoroughly report their EMG methodologies. Development involved a multi-stage Delphi process with seventeen EMG experts from various disciplines. After two rounds, consensus was achieved. The final CEDE-Check consists of forty items that address four critical areas that demand precise reporting when EMG is employed: the task investigated, electrode placement, recording electrode characteristics, and acquisition and pre-processing of EMG signals. This checklist aims to guide researchers to accurately report and critically appraise EMG studies, thereby promoting a standardised critical evaluation, and greater scientific rigor in research that uses EMG signals. This approach not only aims to facilitate interpretation of study results and comparisons between studies, but it is also expected to contribute to advancing research quality and facilitate clinical and other practical applications of knowledge generated through the use of EMG.

Update on musculoskeletal applications of magnetic resonance-guided focused ultrasound.

Magnetic resonance-guided focused ultrasound (MRgFUS) is a noninvasive, incisionless, radiation-free technology used to ablate tissue deep within the body. This technique has gained increased popularity following FDA approval for treatment of pain related to bone metastases and limited approval for treatment of osteoid osteoma. MRgFUS delivers superior visualization of soft tissue targets in unlimited imaging planes and precision in targeting and delivery of thermal dose which is all provided during real-time monitoring using MR thermometry. This paper provides an overview of the common musculoskeletal applications of MRgFUS along with updates on clinical outcomes and discussion of future applications.

Team Approach: Extremity Soft Tissue Sarcoma.

¼ Synovial sarcoma is a soft tissue sarcoma that most commonly presents in the extremity in a periarticular location.¼ As the history and physical examination of patients with synovial sarcoma can overlap considerably with those of patients with non-oncologic orthopedic conditions, it is important that orthopedic surgeons maintain a high level of suspicion when caring for patients with extremity masses.¼ Soft tissue sarcomas are best treated using a team approach. Early recognition and referral to a multidisciplinary sarcoma team are crucial to ensure the best clinical outcome for the patient.

Botryomycosis: a rare mimic of sarcoma as an initial presentation of acquired immunodeficiency syndrome.

Botryomycosis is a rare granulomatous response to chronic bacterial infection most frequently associated with Staphylococcus aureus. This disease, which predominantly affects immunocompromised patients, may present with cutaneous, visceral, or soft tissue manifestations. Soft tissue involvement typically has an aggressive mass-like appearance on imaging which can be concerning for malignancy. In immunocompromised patients, botryomycosis can resemble fungal infection both clinically and histologically; therefore, definitive diagnosis requires tissue sampling along with histological and microbiological analysis. Presented here is a 25-year-old man with an enlarging intramuscular soft tissue mass of the right forearm as his first presentation of undiagnosed acquired immunodeficiency syndrome (AIDS). MR imaging showed a mildly T2 hyperintense and enhancing mass with infiltrative margins extending through tissue planes. Biopsy of the mass revealed Staphylococcus aureus-associated botryomycosis, which improved with nonsurgical treatment employing antibiotics. Unfortunately, the patient subsequently expired from other manifestations of his new AIDS diagnosis. This case describes the MR and PET-CT appearance of botryomycosis and also underscores that infection can mimic sarcoma, particularly in the setting of immunodeficiency.

Imaging of Overuse Injuries of the Hip.

Overuse injuries of the hip are common, and clinical diagnosis may be difficult because of overlapping and nonspecific clinical symptoms. Imaging can play an essential role in guiding diagnosis and management. Femoroacetabular joint structural abnormalities result in various conditions that can predispose patients to early development of osteoarthritis. Repetitive stress on the skeletally immature hip can result in apophyseal injuries. Notable nonosseous overuse hip pathologies include athletic pubalgia, trochanteric bursitis, and injuries involving the iliopsoas myotendinous unit. Timely diagnosis of overuse injuries of the hip can facilitate improved response to conservative measures and prevent irreversible damage.

Utilizing a Digital Swarm Intelligence Platform to Improve Consensus Among Radiologists and Exploring Its Applications.

Radiologists today play a central role in making diagnostic decisions and labeling images for training and benchmarking artificial intelligence (AI) algorithms. A key concern is low inter-reader reliability (IRR) seen between experts when interpreting challenging cases. While team-based decisions are known to outperform individual decisions, inter-personal biases often creep up in group interactions which limit nondominant participants from expressing true opinions. To overcome the dual problems of low consensus and interpersonal bias, we explored a solution modeled on bee swarms. Two separate cohorts, three board-certified radiologists, (cohort 1), and five radiology residents (cohort 2) collaborated on a digital swarm platform in real time and in a blinded fashion, grading meniscal lesions on knee MR exams. These consensus votes were benchmarked against clinical (arthroscopy) and radiological (senior-most radiologist) standards of reference using Cohen's kappa. The IRR of the consensus votes was then compared to the IRR of the majority and most confident votes of the two cohorts. IRR was also calculated for predictions from a meniscal lesion detecting AI algorithm. The attending cohort saw an improvement of 23% in IRR of swarm votes (k = 0.34) over majority vote (k = 0.11). Similar improvement of 23% in IRR (k = 0.25) in 3-resident swarm votes over majority vote (k = 0.02) was observed. The 5-resident swarm had an even higher improvement of 30% in IRR (k = 0.37) over majority vote (k = 0.07). The swarm consensus votes outperformed individual and majority vote decision in both the radiologists and resident cohorts. The attending and resident swarms also outperformed predictions from a state-of-the-art AI algorithm.

Consensus for experimental design in electromyography (CEDE) project: Single motor unit matrix.

The analysis of single motor unit (SMU) activity provides the foundation from which information about the neural strategies underlying the control of muscle force can be identified, due to the one-to-one association between the action potentials generated by an alpha motor neuron and those received by the innervated muscle fibers. Such a powerful assessment has been conventionally performed with invasive electrodes (i.e., intramuscular electromyography (EMG)), however, recent advances in signal processing techniques have enabled the identification of single motor unit (SMU) activity in high-density surface electromyography (HDsEMG) recordings. This matrix, developed by the Consensus for Experimental Design in Electromyography (CEDE) project, provides recommendations for the recording and analysis of SMU activity with both invasive (needle and fine-wire EMG) and non-invasive (HDsEMG) SMU identification methods, summarizing their advantages and disadvantages when used during different testing conditions. Recommendations for the analysis and reporting of discharge rate and peripheral (i.e., muscle fiber conduction velocity) SMU properties are also provided. The results of the Delphi process to reach consensus are contained in an appendix. This matrix is intended to help researchers to collect, report, and interpret SMU data in the context of both research and clinical applications.

An Accurate and Real-Time Method for Resolving Superimposed Action Potentials in MultiUnit Recordings.

OBJECTIVE: Spike sorting of muscular and neural recordings requires separating action potentials that overlap in time (superimposed action potentials (APs)). We propose a new algorithm for resolving superimposed action potentials, and we test it on intramuscular EMG (iEMG) and intracortical recordings. METHODS: Discrete-time shifts of the involved APs are first selected based on a heuristic extension of the peel-off algorithm. Then, the time shifts that provide the minimal residual Euclidean norm are identified (Discrete Brute force Correlation (DBC)). The optimal continuous-time shifts are then estimated (High-Resolution BC (HRBC)). In Fusion HRBC (FHRBC), two other cost functions are used. A parallel implementation of the DBC and HRBC algorithms was developed. The performance of the algorithms was assessed on 11,000 simulated iEMG and 14,000 neural recording superpositions, including two to eight APs, and eight experimental iEMG signals containing four to eleven active motor units. The performance of the proposed algorithms was compared with that of the Branch-and-Bound (BB) algorithm using the Rank-Product (RP) method in terms of accuracy and efficiency. RESULTS: The average accuracy of the DBC, HRBC and FHRBC methods on the entire simulated datasets was 92.16±17.70, 93.65±16.89, and 94.90±15.15 (%). The DBC algorithm outperformed the other algorithms based on the RP method. The average accuracy and running time of the DBC algorithm on 10.5 ms superimposed spikes of the experimental signals were 92.1±21.7 (%) and 2.3±15.3 (ms). CONCLUSION AND SIGNIFICANCE: The proposed algorithm is promising for real-time neural decoding, a central problem in neural and muscular decoding and interfacing.

Ultrasound-guided bursal injections.

The native bursa is a structure lined by synovium located adjacent to a joint which may serve to decrease friction between the tendons and overlying bone or skin. This extra-articular structure can become inflamed resulting in bursitis. Steroid injections have proven to be an effective method of treating bursal pathology in various anatomic locations. Performing these procedures requires a thorough understanding of relevant anatomy, proper technique, and expected outcomes. Ultrasound is a useful tool for pre procedure diagnostic evaluation and optimizing needle position during these procedures while avoiding adjacent structures. The purpose of this article is to review core principles of ultrasound-guided musculoskeletal procedures involving bursae throughout the upper and lower extremities.

Ultrasound-guided interventions of the upper extremity joints.

Ultrasound guidance is valuable for performing precise joint interventions. Joint interventions may be requested for therapeutic and diagnostic pain injections, joint aspiration in the setting of suspected infection, or contrast injection for arthrography. In practice, interventions of the shoulder girdle, elbow, and hand/wrist joints may be performed without any imaging guidance. However, imaging guidance results in more accurate interventions and better patient outcomes than those performed by palpation alone. When compared to other modalities used for imaging guidance, ultrasound has many potential advantages. Radiologists should be prepared to perform ultrasound-guided upper extremity joint interventions utilizing recommended techniques to optimize clinical practice and patient outcomes. KEY POINTS: 1. Ultrasound-guided injections of the glenohumeral, acromioclavicular, sternoclavicular, elbow, and hand/wrist joints have higher accuracy than injections performed without imaging guidance. 2. Ultrasound-guided aspirations of upper extremity joints have advantages to fluoroscopic-guided aspirations because of the potential to identify effusions, soft tissue abscess, or bursitis. 3. Ultrasound-guided contrast injection prior to MR arthrography is as accurate as fluoroscopic-guided injection for upper extremity joints.

Ultrasound-guided joint interventions of the lower extremity.

The purpose of this article is to better understand the role ultrasound plays in lower extremity joint interventions. Ultrasound is an important and reliable tool diagnostically and therapeutically. Real-time feedback, lack of ionizing radiation, and dynamic maneuverability make ultrasound an important tool in the proceduralist's armament. This article will touch upon the important anatomic considerations, clinical indications, and technical step-by-step details for lower extremity ultrasound interventions. Specifically, we will look at interventions involving the hip, knee, ankle, and foot. In addition, this article will discuss the roles corticosteroid and platelet-rich plasma may play in certain interventions.

Consensus for experimental design in electromyography (CEDE) project: High-density surface electromyography matrix.

High-density surface electromyography (HDsEMG) can be used to measure the spatial distribution of electrical muscle activity over the skin. As this distribution is associated with the generation and propagation of muscle fiber action potentials, HDsEMG is processed to extract information on regional muscle activation, muscle fiber characteristics and behaviour of individual motor units. This matrix, developed by the Consensus for Experimental Design in Electromyography (CEDE) project, summarizes recommendations on the use of HDsEMG in experimental studies. For each application, recommendations are included regarding electrode montage, electrode type and configuration, electrode location and orientation, data analysis, and interpretation. Cautions and reporting standards are also included. The steps of the Delphi process to reach consensus are contained in an appendix. This matrix is intended to help researchers when collecting, reporting, and interpreting HDsEMG data. It is hoped that this document will be used to generate new empirical evidence to improve how HDsEMG is used in research and in clinical applications.

Musculoskeletal Applications of Magnetic Resonance-Guided Focused Ultrasound.

Magnetic resonance-guided focused ultrasound (MRgFUS) is a novel noninvasive therapy that uses focused sound energy to thermally ablate focal pathology within the body. In the United States, MRgFUS is approved by the Food and Drug Administration for the treatment of uterine fibroids, palliation of painful bone metastases, and thalamotomy for the treatment of essential tremor. However, it has also demonstrated utility for the treatment of a wide range of additional musculoskeletal (MSK) conditions that currently are treated as off-label indications. Advantages of the technology include the lack of ionizing radiation, the completely noninvasive technique, and the precise targeting that offer unprecedented control of the delivery of the thermal dose, as well as real-time monitoring capability with MR thermometry. In this review, we describe the most common MSK applications of MRgFUS: palliation of bone metastases, treatment of osteoid osteomas, desmoid tumors, facet arthropathy, and other developing indications.

Consensus for experimental design in electromyography (CEDE) project: Terminology matrix.

Consensus on the definition of common terms in electromyography (EMG) research promotes consistency in the EMG literature and facilitates the integration of research across the field. This paper presents a matrix developed within the Consensus for Experimental Design in Electromyography (CEDE) project, providing definitions for terms used in the EMG literature. The definitions for physiological and technical terms that are common in EMG research are included in two tables, with key information on each definition provided in a comment section. A brief outline of some basic principles for recording and analyzing EMG is included in an appendix, to provide researchers new to EMG with background and context for understanding the definitions of physiological and technical terms. This terminology matrix can be used as a reference to aid researchers new to EMG in reviewing the EMG literature.

Genomic Profiling of Low-grade Intramedullary Cartilage Tumors Can Distinguish Enchondroma From Chondrosarcoma.

Low-grade intramedullary cartilage tumors include enchondroma and grade 1 chondrosarcoma. Classification based on radiopathologic correlation guides treatment, typically observation for asymptomatic enchondroma and surgery for chondrosarcoma. However, some tumors elude classification because radiographic and morphologic findings are equivocal. To date, no ancillary tests are available to aid the diagnosis of such indeterminate or suspicious tumors. We investigated the genomic landscape of low-grade cartilage tumors to determine the profile. We studied 10 each enchondroma, grade 1 chondrosarcoma, and suspicious cartilage neoplasms, respectively, by capture-based next-generation sequencing targeting 479 cancer genes and copy number. In enchondroma, IDH1 or IDH2 hotspot activating mutations and/or COL2A1 alterations were identified in 70% and 60% of cases, respectively; copy number changes were rare (20%). Suspicious cartilage neoplasms had frequent hotspot mutations in IDH1 or IDH2 and alterations in COL2A1 (90% and 70%, respectively); copy number changes were rare (20%). Overall, 80% of suspicious cartilage neoplasms were genomically indistinguishable from enchondroma. In contrast, 20% of chondrosarcoma had IDH1 or IDH2 alterations, 100% demonstrated alteration of COL2A1, and 70% had genomes with numerous copy number gains and losses. In total, 80% of chondrosarcomas demonstrated additional pathogenic mutations, deep deletions, or focal amplifications in cancer genes, predominantly CDKN2A. These results demonstrate distinct genomic profiles of enchondroma and grade 1 chondrosarcoma. Further, sequencing may aid in the correct classification of diagnostically challenging tumors. Additional pathogenic alterations (such as in CDKN2A) or numerous copy number gains or losses would support a diagnosis of chondrosarcoma although the absence of such findings does not exclude the diagnosis.

Rigorous performance assessment of the algorithms for resolving motor unit action potential superpositions.

It is necessary to decompose the intra-muscular EMG signal to extract motor unit action potential (MUAP) waveforms and firing times. Some algorithms were proposed in the literature to resolve superimposed MUAPs, including Peel-Off (PO), branch and bound (BB), genetic algorithm (GA), and particle swarm optimization (PSO). This study aimed to compare these algorithms in terms of overall accuracy and running time. Two sets of two-to-five MUAP templates (set1: a wide range of energies, and set2: a high degree of similarity) were used. Such templates were time-shifted, and white Gaussian noise was added. A total of 1000 superpositions were simulated for each template and were resolved using PO (also, POI: interpolated PO), BB, GA, and PSO algorithms. The generalized estimating equation was used to identify which method significantly outperformed, while the overall rank product was used for overall ranking. The rankings were PSO, BB, GA, PO, and POI in the first, and BB, PSO, GA, PO, POI in the second set. The overall ranking was BB, PSO, GA, PO, and POI in the entire dataset. Although the BB algorithm is generally fast, there are cases where the BB algorithm is too slow and it is thus not suitable for real-time applications.

Pleomorphic Sarcoma in a Patient with Osteopetrosis.

Osteopetrosis comprises a rare, heterogeneous group of heritable conditions that are characterized by a defect in bone resorption by osteoclasts. We report the case of a 53-year-old woman with previously undiagnosed osteopetrosis who presented with a pathologic proximal humeral fracture secondary to pleomorphic sarcoma, which is previously undescribed in the English literature. Management of the primary lesion necessitated ablative surgery, but the malignancy nonetheless was associated with rapidly progressive metastatic disease.

Consensus for experimental design in electromyography (CEDE) project: Amplitude normalization matrix.

The general purpose of normalization of EMG amplitude is to enable comparisons between participants, muscles, measurement sessions or electrode positions. Normalization is necessary to reduce the impact of differences in physiological and anatomical characteristics of muscles and surrounding tissues. Normalization of the EMG amplitude provides information about the magnitude of muscle activation relative to a reference value. It is essential to select an appropriate method for normalization with specific reference to how the EMG signal will be interpreted, and to consider how the normalized EMG amplitude may change when interpreting it under specific conditions. This matrix, developed by the Consensus for Experimental Design in Electromyography (CEDE) project, presents six approaches to EMG normalization: (1) Maximal voluntary contraction (MVC) in same task/context as the task of interest, (2) Standardized isometric MVC (which is not necessarily matched to the contraction type in the task of interest), (3) Standardized submaximal task (isometric/dynamic) that can be task-specific, (4) Peak/mean EMG amplitude in task, (5) Non-normalized, and (6) Maximal M-wave. General considerations for normalization, features that should be reported, definitions, and "pros and cons" of each normalization approach are presented first. This information is followed by recommendations for specific experimental contexts, along with an explanation of the factors that determine the suitability of a method, and frequently asked questions. This matrix is intended to help researchers when selecting, reporting and interpreting EMG amplitude data.

Automatic Hip Fracture Identification and Functional Subclassification with Deep Learning.

PURPOSE: To investigate the feasibility of automatic identification and classification of hip fractures using deep learning, which may improve outcomes by reducing diagnostic errors and decreasing time to operation. MATERIALS AND METHODS: Hip and pelvic radiographs from 1118 studies were reviewed, and 3026 hips were labeled via bounding boxes and classified as normal, displaced femoral neck fracture, nondisplaced femoral neck fracture, intertrochanteric fracture, previous open reduction and internal fixation, or previous arthroplasty. A deep learning-based object detection model was trained to automate the placement of the bounding boxes. A Densely Connected Convolutional Neural Network (or DenseNet) was trained on a subset of the bounding box images, and its performance was evaluated on a held-out test set and by comparison on a 100-image subset with two groups of human observers: fellowship-trained radiologists and orthopedists; senior residents in emergency medicine, radiology, and orthopedics. RESULTS: The binary accuracy for detecting a fracture of this model was 93.7% (95% confidence interval [CI]: 90.8%, 96.5%), with a sensitivity of 93.2% (95% CI: 88.9%, 97.1%) and a specificity of 94.2% (95% CI: 89.7%, 98.4%). Multiclass classification accuracy was 90.8% (95% CI: 87.5%, 94.2%). When compared with the accuracy of human observers, the accuracy of the model achieved an expert-level classification, at the very least, under all conditions. Additionally, when the model was used as an aid, human performance improved, with aided resident performance approximating unaided fellowship-trained expert performance in the multiclass classification. CONCLUSION: A deep learning model identified and classified hip fractures with expert-level performance, at the very least, and when used as an aid, improved human performance, with aided resident performance approximating that of unaided fellowship-trained attending physicians.Supplemental material is available for this article.© RSNA, 2020.