Chronic Nonspinal Osteomyelitis in Adults: Consensus Recommendations on Percutaneous Bone Biopsies from the Society of Academic Bone Radiologists.

The diagnosis and management of chronic nonspinal osteomyelitis can be challenging, and guidelines regarding the appropriateness of performing percutaneous image-guided biopsies to acquire bone samples for microbiological analysis remain limited. An expert panel convened by the Society of Academic Bone Radiologists developed and endorsed consensus statements on the various indications for percutaneous image-guided biopsies to standardize care and eliminate inconsistencies across institutions. The issued statements pertain to several commonly encountered clinical presentations of chronic osteomyelitis and were supported by a literature review. For most patients, MRI can help guide management and effectively rule out osteomyelitis when performed soon after presentation. Additionally, in the appropriate clinical setting, open wounds such as sinus tracts and ulcers, as well as joint fluid aspirates, can be used for microbiological culture to determine the causative microorganism. If MRI findings are positive, surgery is not needed, and alternative sites for microbiological culture are not available, then percutaneous image-guided biopsies can be performed. The expert panel recommends that antibiotics be avoided or discontinued for an optimal period of 2 weeks prior to a biopsy whenever possible. Patients with extensive necrotic decubitus ulcers or other surgical emergencies should not undergo percutaneous image-guided biopsies but rather should be admitted for surgical debridement and intraoperative cultures. Multidisciplinary discussion and approach are crucial to ensure optimal diagnosis and care of patients diagnosed with chronic osteomyelitis.

Relationships between diagnostic imaging of first carpometacarpal osteoarthritis and pain, functional status, and disease progression: A systematic review.

OBJECTIVE: To systematically review the association of pain, function, and progression in first carpometacarpal (CMC) osteoarthritis (OA) with imaging biomarkers and radiography-based staging. DESIGN: Database searches in PubMed, Embase, and the Cochrane Library, along with citation searching were conducted in accordance with published guidance. Data on the association of imaging with pain, functional status, and disease progression were extracted and synthesized, along with key information on study methodology such as sample sizes, use of control subjects, study design, number of image raters, and blinding. Methodological quality was assessed using National Heart, Lung, and Blood Institute tools. RESULTS: After duplicate removal, a total of 1969 records were screened. Forty-six articles are included in this review, covering a total of 28,202 study participants, 7263 with first CMC OA. Osteophytes were found to be one of the strongest biomarkers for pain across imaging modalities. Radiographic findings alone showed conflicting relationships with pain. However, Kellgren-Lawrence staging showed consistent associations with pain in various studies. Radiographic, sonographic, and MRI findings and staging showed little association to tools evaluating functional status across imaging modalities. The same imaging methods showed limited ability to predict progression of first CMC OA. A major limitation was the heterogeneity in the study base, limiting synthesis of results. CONCLUSION: Imaging findings and radiography-based staging systems generally showed strong associations with pain, but not with functional status or disease progression. More research and improved imaging techniques are needed to help physicians better manage patients with first CMC OA.

Automated abdominal CT contrast phase detection using an interpretable and open-source artificial intelligence algorithm.

OBJECTIVES: To develop and validate an open-source artificial intelligence (AI) algorithm to accurately detect contrast phases in abdominal CT scans. MATERIALS AND METHODS: Retrospective study aimed to develop an AI algorithm trained on 739 abdominal CT exams from 2016 to 2021, from 200 unique patients, covering 1545 axial series. We performed segmentation of five key anatomic structures-aorta, portal vein, inferior vena cava, renal parenchyma, and renal pelvis-using TotalSegmentator, a deep learning-based tool for multi-organ segmentation, and a rule-based approach to extract the renal pelvis. Radiomics features were extracted from the anatomical structures for use in a gradient-boosting classifier to identify four contrast phases: non-contrast, arterial, venous, and delayed. Internal and external validation was performed using the F1 score and other classification metrics, on the external dataset "VinDr-Multiphase CT". RESULTS: The training dataset consisted of 172 patients (mean age, 70 years ± 8, 22% women), and the internal test set included 28 patients (mean age, 68 years ± 8, 14% women). In internal validation, the classifier achieved an accuracy of 92.3%, with an average F1 score of 90.7%. During external validation, the algorithm maintained an accuracy of 90.1%, with an average F1 score of 82.6%. Shapley feature attribution analysis indicated that renal and vascular radiodensity values were the most important for phase classification. CONCLUSION: An open-source and interpretable AI algorithm accurately detects contrast phases in abdominal CT scans, with high accuracy and F1 scores in internal and external validation, confirming its generalization capability. CLINICAL RELEVANCE STATEMENT: Contrast phase detection in abdominal CT scans is a critical step for downstream AI applications, deploying algorithms in the clinical setting, and for quantifying imaging biomarkers, ultimately allowing for better diagnostics and increased access to diagnostic imaging. KEY POINTS: Digital Imaging and Communications in Medicine labels are inaccurate for determining the abdominal CT scan phase. AI provides great help in accurately discriminating the contrast phase. Accurate contrast phase determination aids downstream AI applications and biomarker quantification.

Skeletal Muscle Area on CT: Determination of an Optimal Height Scaling Power and Testing for Mortality Risk Prediction.

BACKGROUND. Sarcopenia is commonly assessed on CT by use of the skeletal muscle index (SMI), which is calculated as the skeletal muscle area (SMA) at L3 divided by patient height squared (i.e., a height scaling power of 2). OBJECTIVE. The purpose of this study was to determine the optimal height scaling power for SMA measurements on CT and to test the influence of the derived optimal scaling power on the utility of SMI in predicting all-cause mortality. METHODS. This retrospective study included 16,575 patients (6985 men, 9590 women; mean age, 56.4 years) who underwent abdominal CT from December 2012 through October 2018. The SMA at L3 was determined using automated software. The sample was stratified into two groups: 5459 patients without major medical conditions (based on ICD-9 and ICD-10 codes) who were included in the analysis for determining the optimal height scaling power and 11,116 patients with major medical conditions who were included for the purpose of testing this power. The optimal scaling power was determined by allometric analysis (whereby regression coefficients were fitted to log-linear sex-specific models relating height to SMA) and by analysis of statistical independence of SMI from height across scaling powers. Cox proportional hazards models were used to test the influence of the derived optimal scaling power on the utility of SMI in predicting all-cause mortality. RESULTS. In allometric analysis, the regression coefficient of log(height) in patients 40 years old and younger was 1.02 in men and 1.08 in women, and in patients older than 40 years old, it was 1.07 in men and 1.10 in women (all p < .05 vs regression coefficient of 2). In analyses for statistical independence of SMI from height, the optimal height scaling power (i.e., those yielding correlations closest to 0) was, in patients 40 years old and younger, 0.97 in men and 1.08 in women, whereas in patients older than 40 years old, it was 1.03 in men and 1.09 in women. In the Cox model used for testing, SMI predicted all-cause mortality with a higher concordance index using of a height scaling power of 1 rather than 2 in men (0.675 vs 0.663, p < .001) and in women (0.664 vs 0.653, p < .001). CONCLUSION. The findings support a height scaling power of 1, rather than a conventional power of 2, for SMI computation. CLINICAL IMPACT. A revised height scaling power for SMI could impact the utility of CT-based sarcopenia diagnoses in risk assessment.

Myositis and Its Mimics: Guideline Updates, MRI Characteristics, and New Horizons.

Myositis is defined as inflammation within skeletal muscle and is a subcategory of myopathy, which is more broadly defined as any disorder affecting skeletal muscle. Myositis may be encountered as a component of autoimmune and connective tissue diseases, where it is described as idiopathic inflammatory myopathy (IIM). Myositis can also be caused by infections as well as toxins and drugs, including newer classes of medications. MRI plays an important role in the diagnosis and evaluation of patients with suspected myositis, but many entities may have imaging features similar to those of myositis and can be considered myositis mimics. These include muscular dystrophies, denervation, deep venous thrombosis, diabetic myonecrosis, muscle injury, heterotopic ossification, and even neoplasms. In patients with suspected myositis, definitive diagnosis may require integrated analysis of imaging findings with clinical, laboratory, and pathology data. The objectives of this article are to review the fundamental features of myositis, including recent updates in terminology and consensus guidelines for IIMs; the most important MRI differential diagnostic considerations for myositis (i.e., myositis mimics); and new horizons, including the potential importance of artificial intelligence and multimodal integrated diagnostics in the evaluation of patients with muscle disorders.

MRI of Soft-Tissue Tumors: What to Include in the Report.

MRI serves as a critical step in the workup, local staging, and treatment planning of extremity soft-tissue masses. For the radiologist to meaningfully contribute to the management of soft-tissue masses, they need to provide a detailed list of descriptors of the lesion outlined in an organized report. While it is occasionally possible to use MRI to provide a diagnosis for patients with a mass, it is more often used to help with determining the differential diagnosis and planning of biopsies, surgery, radiation treatment, and chemotherapy (when provided). Each descriptor on the list outlined in this article is specifically aimed to assist in one or more facets of the overall approach to soft-tissue masses. This applies to all masses, but in particular sarcomas. Those descriptors are useful to help narrow the differential diagnosis and ensure concordance with a pathologic diagnosis and its accompanying grade assignment of soft-tissue sarcomas. These include a lesion's borders and shape, signal characteristics, and contrast enhancement pattern; the presence of peritumoral edema and peritumoral enhancement; and the presence of lymph nodes. The items most helpful in assisting surgical planning include a lesion's anatomic location, site of origin, size, location relative to a landmark, relationship to adjacent structures, and vascularity including feeding and draining vessels. The authors provide some background information on soft-tissue sarcomas, including their diagnosis and treatment, for the general radiologist and as a refresher for radiologists who are more experienced in tumor imaging. ©RSNA, 2024 See the invited commentary by Murphey in this issue.

Opportunistic Screening of Bone Fragility Using Computed Tomography.

Opportunistic screening uses existing imaging studies for additional diagnostic insights without imposing further burden on patients. We explore the potential of opportunistic computed tomography (CT) screening for osteoporosis, a condition affecting 500 million people globally and leading to significant health care costs and fragility fractures. Although dual-energy X-ray absorptiometry (DXA) remains the gold standard for diagnosing osteoporosis, > 50% of fractures occur in individuals not screened previously with DXA. With recent advancements in technology, CT has emerged as the most promising tool for opportunistic screening due to its wide use and the ability to provide quantitative measurements of bone attenuation, a surrogate of bone mineral density. This article discusses the technical considerations, calibration methods, and potential benefits of CT for osteoporosis screening. It also explores the role of automation, supervised and unsupervised, in streamlining the diagnostic process, improving accuracy, and potentially developing new biomarkers of bone health. The potential addition of radiomics and genomics is also highlighted, showcasing the synergy between genetic and imaging data for a more comprehensive understanding of osteoporosis pathophysiology and with it possible novel osteoporosis therapies. The future of opportunistic CT screening holds significant promise, with automation and advanced image processing ultimately enhancing patient care, reducing rates of osteoporotic fractures, and improving patient outcomes.

Biomarkers of Body Composition.

The importance and impact of imaging biomarkers has been increasing over the past few decades. We review the relevant clinical and imaging terminology needed to understand the clinical and research applications of body composition. Imaging biomarkers of bone, muscle, and fat tissues obtained with dual-energy X-ray absorptiometry, computed tomography, magnetic resonance imaging, and ultrasonography are described.

Clinical, functional, and opportunistic CT metrics of sarcopenia at the point of imaging care: analysis of all-cause mortality.

PURPOSE: This study examines clinical, functional, and CT metrics of sarcopenia and all-cause mortality in older adults undergoing outpatient imaging. METHODS: The study included outpatients ≥ 65 years of age undergoing CT or PET/CT at a tertiary care institution. Assessments included screening questionnaires for sarcopenia (SARC-F) and frailty (FRAIL scale), and measurements of grip strength and usual gait speed (6 m course). Skeletal muscle area (SMA), index (SMI, area/height2) and density (SMD) were measured on CT at T12 and L3. A modified SMI was also examined (SMI-m, area/height). Mortality risk was studied with Cox proportional hazard analysis. RESULTS: The study included 416 patients; mean age 73.8 years [sd 6.2]; mean follow-up 2.9 years (sd 1.34). Abnormal grip, SARC-F, and FRAIL scale assessments were associated with higher mortality risk (HR [95%CI] = 2.0 [1.4-2.9], 1.6 [1.1-2.3], 2.0 [1.4-2.8]). Adjusting for age, higher L3-SMA, T12-SMA, T12-SMI and T12-SMI-m were associated with lower mortality risk (HR [95%CI] = 0.80 [0.65-0.90], 0.76 [0.64-0.90], 0.84 [0.70-1.00], and 0.80 [0.67-0.90], respectively). T12-SMD and L3-SMD were not predictive of mortality. After adjusting for abnormal grip strength and FRAIL scale assessments, T12-SMA and T12-SMI-m remained predictive of mortality risk (HR [95%CI] = 0.83 [0.70-1.00] and 0.80 [0.67-0.97], respectively). CONCLUSION: CT areal metrics were weaker predictors of all-cause mortality than clinical and functional metrics of sarcopenia in our older patient cohort; a CT density metric (SMD) was not predictive. Of areal CT metrics, SMI (area/height2) appeared to be less effective than non-normalized SMA or SMA normalized by height1.

MRI of patellar stabilizers: Anatomic visibility, inter-reader reliability, and intra-reader reproducibility of primary and secondary ligament anatomy.

OBJECTIVE: To compare MRI features of medial and lateral patellar stabilizers in patients with and without patellar instability. METHODS: Retrospective study of 196 patients (mean age, 33.1 ± 18.5 years; 119 women) after diagnosis of patellar instability (cohort-1, acute patellar dislocation; cohort-2, chronic patellar maltracking) or no patellar instability (cohort-3, acute ACL rupture; cohort-4, chronic medial meniscus tear). On MRI, four medial and four lateral stabilizers were evaluated for visibility and injury by three readers independently. Inter- and intra-reader agreement was determined. RESULTS: Medial and lateral patellofemoral ligaments (MPFL and LPFL) were mostly or fully visualized in all cases (100%). Of the secondary patellar stabilizers, the medial patellotibial ligament was mostly or fully visualized in 166 cases (84.7%). Other secondary stabilizers were mostly or fully visualized in only a minority of cases (range, 0.5-32.1%). Injury scores for all four medial stabilizers were higher in patients with acute patellar dislocation than the other 3 cohorts (p < .05). Visibility inter- and intra-reader agreement was good for medial stabilizers (κ 0.61-0.78) and moderate-to-good for lateral stabilizers (κ 0.40-0.72). Injury inter- and intra-reader agreement was moderate-to-excellent for medial stabilizers (κ 0.43-0.90) and poor-to-moderate for lateral stabilizers (κ 0-0.50). CONCLUSION: The MPFL and LPFL were well visualized on MRI while the secondary stabilizers were less frequently visualized. The secondary stabilizers were more frequently visualized medially than laterally, and patellotibial ligaments were more frequently visualized compared to the other secondary stabilizers. Injury to the medial stabilizers was more common with acute patellar dislocation than with chronic patellar maltracking or other knee injuries.

Noise2Recon: Enabling SNR-robust MRI reconstruction with semi-supervised and self-supervised learning.

PURPOSE: To develop a method for building MRI reconstruction neural networks robust to changes in signal-to-noise ratio (SNR) and trainable with a limited number of fully sampled scans. METHODS: We propose Noise2Recon, a consistency training method for SNR-robust accelerated MRI reconstruction that can use both fully sampled (labeled) and undersampled (unlabeled) scans. Noise2Recon uses unlabeled data by enforcing consistency between model reconstructions of undersampled scans and their noise-augmented counterparts. Noise2Recon was compared to compressed sensing and both supervised and self-supervised deep learning baselines. Experiments were conducted using retrospectively accelerated data from the mridata three-dimensional fast-spin-echo knee and two-dimensional fastMRI brain datasets. All methods were evaluated in label-limited settings and among out-of-distribution (OOD) shifts, including changes in SNR, acceleration factors, and datasets. An extensive ablation study was conducted to characterize the sensitivity of Noise2Recon to hyperparameter choices. RESULTS: In label-limited settings, Noise2Recon achieved better structural similarity, peak signal-to-noise ratio, and normalized-RMS error than all baselines and matched performance of supervised models, which were trained with 14 × $$ 14\times $$ more fully sampled scans. Noise2Recon outperformed all baselines, including state-of-the-art fine-tuning and augmentation techniques, among low-SNR scans and when generalizing to OOD acceleration factors. Augmentation extent and loss weighting hyperparameters had negligible impact on Noise2Recon compared to supervised methods, which may indicate increased training stability. CONCLUSION: Noise2Recon is a label-efficient reconstruction method that is robust to distribution shifts, such as changes in SNR, acceleration factors, and others, with limited or no fully sampled training data.

Generalizability of Deep Learning Segmentation Algorithms for Automated Assessment of Cartilage Morphology and MRI Relaxometry.

BACKGROUND: Deep learning (DL)-based automatic segmentation models can expedite manual segmentation yet require resource-intensive fine-tuning before deployment on new datasets. The generalizability of DL methods to new datasets without fine-tuning is not well characterized. PURPOSE: Evaluate the generalizability of DL-based models by deploying pretrained models on independent datasets varying by MR scanner, acquisition parameters, and subject population. STUDY TYPE: Retrospective based on prospectively acquired data. POPULATION: Overall test dataset: 59 subjects (26 females); Study 1: 5 healthy subjects (zero females), Study 2: 8 healthy subjects (eight females), Study 3: 10 subjects with osteoarthritis (eight females), Study 4: 36 subjects with various knee pathology (10 females). FIELD STRENGTH/SEQUENCE: A 3-T, quantitative double-echo steady state (qDESS). ASSESSMENT: Four annotators manually segmented knee cartilage. Each reader segmented one of four qDESS datasets in the test dataset. Two DL models, one trained on qDESS data and another on Osteoarthritis Initiative (OAI)-DESS data, were assessed. Manual and automatic segmentations were compared by quantifying variations in segmentation accuracy, volume, and T2 relaxation times for superficial and deep cartilage. STATISTICAL TESTS: Dice similarity coefficient (DSC) for segmentation accuracy. Lin's concordance correlation coefficient (CCC), Wilcoxon rank-sum tests, root-mean-squared error-coefficient-of-variation to quantify manual vs. automatic T2 and volume variations. Bland-Altman plots for manual vs. automatic T2 agreement. A P value < 0.05 was considered statistically significant. RESULTS: DSCs for the qDESS-trained model, 0.79-0.93, were higher than those for the OAI-DESS-trained model, 0.59-0.79. T2 and volume CCCs for the qDESS-trained model, 0.75-0.98 and 0.47-0.95, were higher than respective CCCs for the OAI-DESS-trained model, 0.35-0.90 and 0.13-0.84. Bland-Altman 95% limits of agreement for superficial and deep cartilage T2 were lower for the qDESS-trained model, ±2.4 msec and ±4.0 msec, than the OAI-DESS-trained model, ±4.4 msec and ±5.2 msec. DATA CONCLUSION: The qDESS-trained model may generalize well to independent qDESS datasets regardless of MR scanner, acquisition parameters, and subject population. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 1.

Interdisciplinary consensus statements on imaging of DRUJ instability and TFCC injuries.

OBJECTIVES: 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: 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: • 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.

Ageism in Society and Its Health Impact.

Ageism is an increasingly recognized form of cognitive bias involving stereotypes, prejudice, and discrimination directed toward people on the basis of their age. Age-based bias influences how medicine is practiced and can result in profoundly negative but avoidable health outcomes. Awareness and education regarding ageism and its manifestations can improve the ability to identify and mitigate ageism. As this Viewpoint describes, radiologists are well situated to be part of the solution in addressing ageism.

Muscle Steatosis and Fibrosis in Older Adults, From the AJR Special Series on Imaging of Fibrosis.

The purpose of this article is to review steatosis and fibrosis of skeletal muscle, focusing on older adults. Although CT, MRI, and ultrasound are commonly used to image skeletal muscle and provide diagnoses for a variety of medical conditions, quantitative assessment of muscle steatosis and fibrosis is uncommon. This review provides radiologists with a broad perspective on muscle steatosis and fibrosis in older adults by considering their public health impact, biologic mechanisms, and evaluation using CT, MRI, and ultrasound. Promising directions in clinical research that employ artificial intelligence algorithms and the imaging assessment of biologic age are also reviewed. The presented imaging methods hold promise for improving the evaluation of common conditions affecting older adults including sarcopenia, frailty, and cachexia.

Knee MRI: Meniscus Roots, Ramps, Repairs, and Repercussions.

Menisci play an essential role in maintaining normal pain-free function of the knee. While there are decades of MRI literature on the tears involving the meniscus body and horns, there is now a surge in knowledge regarding injuries at the meniscus roots and periphery. The authors briefly highlight new insights into meniscus anatomy and then summarize recent developments in the understanding of meniscus injuries that matter, emphasizing meniscus injuries at the root and peripheral (eg, ramp) regions that may be missed easily at MRI and arthroscopy. Root and ramp tears are important to diagnose because they may be amenable to repair. However, if these tears are left untreated, ongoing pain and accelerated cartilage degeneration may ensue. The posterior roots of the medial and lateral menisci are most commonly affected by injury, and each of these injuries is associated with distinctive clinical profiles, MRI findings, and tear patterns. Specific diagnostic pitfalls can make the roots challenging to evaluate, including MRI artifacts and anatomic variations. As with root tears, MRI interpretation and orthopedic treatment have important differences for injuries at the medial versus lateral meniscus (LM) periphery (located at or near the meniscocapsular junction). Medially, ramp lesions typically occur in the setting of an anterior cruciate ligament rupture and are generally classified into five patterns. Laterally, the meniscocapsular junction may be injured in association with tibial plateau fractures, but disruption of the popliteomeniscal fascicles may also result in a hypermobile LM. Updated knowledge of the meniscus root and ramp tears is crucial in optimizing diagnostic imaging before repair and understanding the clinical repercussions. ©RSNA, 2023 Online supplemental material is available for this article. Quiz questions for this article are available in the Online Learning Center.

Patellar Tracking: An Old Problem with New Insights.

Patellofemoral pain and instability are common indications for imaging that are encountered in everyday practice. The authors comprehensively review key aspects of patellofemoral instability pertinent to radiologists that can be seen before the onset of osteoarthritis, highlighting the anatomy, clinical evaluation, diagnostic imaging, and treatment. Regarding the anatomy, the medial patellofemoral ligament (MPFL) is the primary static soft-tissue restraint to lateral patellar displacement and is commonly reconstructed surgically in patients with MPFL dysfunction and patellar instability. Osteoarticular abnormalities that predispose individuals to patellar instability include patellar malalignment, trochlear dysplasia, and tibial tubercle lateralization. Clinically, patients with patellar instability may be divided into two broad groups with imaging findings that sometimes overlap: patients with a history of overt patellar instability after a traumatic event (eg, dislocation, subluxation) and patients without such a history. In terms of imaging, radiography is generally the initial examination of choice, and MRI is the most common cross-sectional examination performed preoperatively. For all imaging techniques, there has been a proliferation of published radiologic measurement methods. The authors summarize the most common validated measurements for patellar malalignment, trochlear dysplasia, and tibial tubercle lateralization. Given that static imaging is inherently limited in the evaluation of patellar motion, dynamic imaging with US, CT, or MRI may be requested by some surgeons. The primary treatment strategy for patellofemoral pain is conservative. Surgical treatment options include MPFL reconstruction with or without osseous corrections such as trochleoplasty and tibial tubercle osteotomy. Postoperative complications evaluated at imaging include patellar fracture, graft failure, graft malposition, and medial patellar subluxation. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.

Pre-operative imaging for surgical decision-making and the frequency of wrist arthrodesis and carpectomy procedures: a scoping review.

OBJECTIVES: Our objectives were to (1) analyze the imaging modalities utilized pre-operatively that influence surgical decision-making for wrist arthrodesis and carpectomy procedures and (2) determine the type and frequency of these procedures for the treatment of wrist arthritis. MATERIALS AND METHODS: This review was performed according to the guidelines of PRISMA Extension for Scoping Reviews. Using PubMed, Embase, and Scopus, peer-reviewed literature from 2011 to 2022 was searched for use of imaging in pre-operative decision-making for wrist arthrodesis and carpectomy surgical procedures. Data were compiled to determine the type(s) of imaging modalities used pre-operatively and types of surgical techniques reported in the literature. RESULTS: Of 307 articles identified, 35 articles satisfied eligibility criteria, with a total of 1377 patients (68% men; age mean, 50.9 years [range, 10-81]) and 1428 wrist surgical interventions. Radiography was reported for pre-operative planning in all articles for all patients. Pre-operative cross-sectional imaging was reported in 2 articles (5.7%), but no articles reported detailed data on how CT or MRI influenced pre-operative wrist arthrodesis and carpectomy procedure decision-making. A dozen different types of surgical techniques were reported. The four most common procedures were four-corner arthrodesis with scaphoid excision (846, 59%), proximal row carpectomy (239, 17%), total wrist arthrodesis (130, 9%), and scaphocapitate arthrodesis (53, 4%). CONCLUSION: Radiography is always used in pre-operative decision-making, but the literature lacks data on the influence of CT and MRI for selecting among a dozen different types of wrist arthrodesis and carpectomy procedures.

Charges for Shoppable Musculoskeletal Imaging Examinations: CMS Transparency Compliance and Variability Among 250 U.S. Hospitals.

As of January 2021, among other transparency requirements, the Centers for Medicare & Medicaid Services require that hospitals publish consumer-friendly displays of charges for shoppable health care services, including four musculoskeletal imaging examinations. Of 250 selected U.S. hospitals, all published charges for these four examinations, although 21% did not provide charges within consumer-friendly displays. Bed count was larger for compliant hospitals than for noncompliant hospitals (500 vs 384 beds). All four examinations had widely variable charges (representing a 73.8-fold difference).

Sarcopenia in rheumatic disorders: what the radiologist and rheumatologist should know.

Sarcopenia is defined as the loss of muscle mass, strength, and function. Increasing evidence shows that sarcopenia is common in patients with rheumatic disorders. Although sarcopenia can be diagnosed using bioelectrical impedance analysis or DXA, increasingly it is diagnosed using CT, MRI, and ultrasound. In rheumatic patients, CT and MRI allow "opportunistic" measurement of body composition, including surrogate markers of sarcopenia, from studies obtained during routine patient care. Recognition of sarcopenia is important in rheumatic patients because sarcopenia can be associated with disease progression and poor outcomes. This article reviews how opportunistic evaluation of sarcopenia in rheumatic patients can be accomplished and potentially contribute to improved patient care.