Skeletal Radiology最新文献

Objective: To evaluate the cost-effectiveness of opportunistic CT for sarcopenia screening compared with standard-of-care clinical screening methods, using a decision-analytic model based on quality-adjusted life years (QALYs) and healthcare costs.

Materials and methods: We developed a decision-analytic model simulating a hypothetical cohort of 70-year-old male patients at risk for sarcopenia over a 3-year time horizon from a US healthcare system perspective. The model compared two screening strategies: standard-of-care clinical evaluation per EWGSOP2 guidelines (physical exam + DXA evaluation of lean mass) and opportunistic CT as measures of muscle mass and quality. Model inputs-including screening sensitivities/specificities, costs, utility values, and probabilities of cardiovascular complications-were derived from published literature. Incremental cost-effectiveness ratio (ICER) and net monetary benefit (NMB) were calculated, and sensitivity analyses were performed to assess the robustness of findings across variable inputs.

Results: Opportunistic CT was the favored strategy, with lower costs ($845 vs. $1,295), comparable effectiveness (0.87 QALYs), and higher net monetary benefit ($86,037 vs. $85,588) relative to the standard-of-care strategy. The standard-of-care strategy's ICER was $47.7 million per QALY, exceeding our willingness-to-pay threshold of $100,000. Probabilistic sensitivity analysis across 100,000 simulations demonstrated that opportunistic CT was favored across all tested willingness-to-pay thresholds up to $200,000.

Conclusion: Opportunistic CT is a cost-effective strategy for sarcopenia screening, offering similar effectiveness at a lower cost compared to the standard-of-care approach. By leveraging existing imaging studies, opportunistic CT screening has the potential to enhance early detection and decrease the underdiagnosis of sarcopenia while also reducing the burden of additional DXA scans and clinical visits.

We describe the case of an 11-year-old boy with hemophilia B who presented with swelling and pain in the left index finger. The patient was referred to our hospital after first presenting to another hospital. The patient experienced slight difficulty making a fist because of limited flexion of the proximal interphalangeal joint. Radiography of the left index finger revealed an expansile remodeling osteolytic lesion with a well-defined sclerotic border and cortical thinning. The patient had prolonged activated partial thromboplastin times and decreased factor IX levels. We performed curettage of the tumor in the left proximal phalanx and artificial bone filling. A hemophilic pseudotumor was diagnosed. At 1 year postoperatively, the patient was able to mobilize the index finger without range of motion limitations. Radiography of the left index finger revealed no signs of recurrence. Hemophilic pseudotumor usually occurs in patients with severe hemophilia A; however, this is the first reported case of a hemophilic pseudotumor arising from the finger of a child with mild hemophilia B. When progressive expansile remodeling of bone in the hand of a patient with hemophilia is observed, the possibility of a hemophilic pseudotumor, regardless of the severity or type of hemophilia, should be considered.

Objective: To develop and validate a deep learning model for the detection of aberrant anterior tibial artery (AATA) on axial T2-weighted knee MRI, given the surgical relevance of unrecognized AATA and the lack of automated detection tools.

Materials and methods: This retrospective study included 70,260 MRI images from 2315 examinations (1441 without AATA and 874 with AATA) collected after institutional review board approval. Musculoskeletal radiologists performed image-level annotations. Data were split at the patient level into training, validation, and internal test sets; an independent dataset from another institution served as an external test set. A convolutional neural network was implemented in Python and PyTorch. Model performance was assessed at the patient level.

Results: At the slice level, the model achieved an F1-score of 0.838 on the internal test set. Patient-level classification using the validation-derived threshold (0.17) yielded F1-scores of 0.966 on the validation set, 0.979 on the internal test set, and 0.786 on the external test set. The area under the receiver operating characteristic curve for the external cohort was 0.97, indicating strong generalization despite a decrease in precision due to false positives.

Conclusion: To our knowledge, this is the first study to apply artificial intelligence for automated detection of AATA on knee MRI. The proposed deep learning model performs this task with high sensitivity. Despite reduced precision in the external cohort, it demonstrates strong potential for enhancing preoperative risk assessment and surgical planning. Broader multicenter validation is warranted before clinical deployment.

Objectives: To assess the added value of two additional dedicated MRI sequences in the evaluation of the acromioclavicular ligament complex in patients with traumatic acromioclavicular joint injury.

Materials and methods: In this single-center study, shoulder MRIs of post-traumatic patients with suspected acromioclavicular joint dislocation were retrospectively evaluated twice by four readers of varying levels of expertise: once with the standard protocol and once with two additional dedicated acromioclavicular ligament sequences (a proton density-weighted sequence parallel to the acromioclavicular joint and a coronal oblique PD-weighted sequence, with a slice thickness of 2 mm). The acromioclavicular and the coracoclavicular ligaments, along with their different bundles, were analyzed. Intrareader reliability and interreader agreement were assessed by intraclass correlations. Associated shoulder lesions were reported.

Results: A total of 85 shoulder MRIs from patients with acute trauma were retrospectively analyzed (mean age 38.4 ± 13.6 years, male = 73 [85.9%]). Acromioclavicular dislocations were reported in 75 patients (88.2%). The intrareader reliability was good to excellent, ranging from 0.81 to 0.90. Overall, the interreader agreements were excellent (intraclass correlations = 0.93 and 0.94 at both four and six sequences, respectively). The less experienced reader agreed with the more experienced one with and without dedicated acromioclavicular sequences (significant equivalence: t[12] = 2.946, p = 0.006).

Conclusion: In this retrospective cohort, adding dedicated acromioclavicular joint sequences did not show evidence of improvement in the detection and the characterization of potential acromioclavicular ligament lesions, regardless of the reader's level of experience.

Objectives: The purpose of this study was to evaluate the effectiveness of collagen-sensitive dual-energy computed tomography (DECT) as a quantitative imaging tool for the assessment and monitoring of load-induced tendinopathy in the Achilles and patellar tendons, comparing it to magnetic resonance imaging (MRI).

Methods: In a prospective study, 15 consecutive patients clinically diagnosed with Achilles or patellar tendinopathy underwent bilateral DECT and MRI at baseline and 6 months. Quantitative measurements included collagen density assessed via DECT and signal intensity via MRI. Clinical symptoms were evaluated using numerical pain ratings and VISA-A/P scores. The diagnostic accuracy of both imaging modalities was assessed using ROC analysis, and correlations between DECT and MRI findings were investigated.

Results: DECT revealed significantly lower collagen densities on corresponding maps in affected tendons (n = 18, 23.7 ± 20.2) compared to unaffected tendons (n = 12, 60.2 ± 29.6 HU, p < 0.001), whereas MRI demonstrated increased signal intensities in pathological regions. ROC analysis indicated comparable diagnostic performance for DECT (AUC = 0.84) and MRI (AUC = 0.80). A strong inverse correlation (r = -0.83) was observed between DECT-measured collagen densities and MRI signal intensities. Clinical improvements at follow-up were reflected by normalization trends in both imaging modalities, though not statistically significant.

Conclusions: Collagen-sensitive DECT provides a reliable quantitative approach for detecting and assessing tendon pathologies in load-induced tendinopathy, demonstrating diagnostic capabilities comparable to MRI while offering the possibility for collagen density quantification.

Soft tissue-RADS scoring system for musculoskeletal (MSK) tumor and tumor-like lesions is recently published. The system includes diagnostic MRI flowcharts and algorithms for lipomatous masses, cyst-like or high-water content masses, and indeterminate-solid appearing masses with consistent and standardized management recommendations. MSK radiology and cancer imaging training commonly provides the essential skills needed to render appropriate prospective diagnosis for many non-neoplastic tumor-like lesions and various commonly encountered sarcomas. Such trained readers may benefit from additional advanced algorithms to accurately identify and categorize different benign tumors and sarcomas and correctly input them in the soft tissue-RADS scoring system. These algorithms are built from a comprehensive literature search to establish an evidence-based composite and are supported by the expert opinions of the multidisciplinary ACR-soft tissue-RADS team. In this article we provide (1) a literature review of multimodality imaging, immunopathology, and clinical findings of soft tissue tumors and tumor-like lesions, presented in 7 tables (condensed from the 12 tables published in the WHO classification of soft tissue tumors) with respective table summaries; (2) a suggested modality-based lexicon; and (3) advanced diagnostic algorithms for trained readers based on published evidence and expert opinion that feed into the soft tissue-RADS scoring system (categories 1-6). The purpose of this work is to provide comprehensive guidance on soft tissue-RADS scoring to help streamline care for soft tissue tumors and tumor-like lesions and optimize patient outcomes.

The immature sacroiliac joint (SIJ) has developmental imaging appearances that frequently simulate sacroiliitis in children and adolescents evaluated for juvenile spondyloarthritis, and false-positive interpretation increases when adult MRI and structural criteria are applied. This review integrates developmental anatomy with MRI and CT findings and discusses CT-like MRI and MRI-based synthetic CT as structural adjuncts for cortical assessment in the immature SIJ. We emphasize the most relevant false-positive pathways in daily practice, including peri-physeal fluid-sensitive marrow hyperintensity, developmental cortical contour variants, transitional intersegmental fusion interfaces, well-corticated intra-articular developmental ossification centers, physiologic enhancement patterns, and intra-articular gas (vacuum phenomenon). The review also outlines modality-specific strengths and limitations and provides practical guidance on how to integrate fluid-sensitive and structural information across modalities. The figure set is organized as a teaching atlas focused on pattern recognition, multimodality correlation, and explicit interpretive safeguards to help radiologists distinguish physiologic maturation from true inflammatory disease in skeletally immature patients.

Although most imaging assessments are made qualitatively, quantitative measurements in orthopedic imaging are becoming more important in detecting subtle findings and assessing degrees of abnormality, which can help direct surgical management. In the knee, patellofemoral maltracking is a common cause of anterior pain, particularly in younger patients. Failure to recognize this pathophysiology may result in accelerated chondral loss and osteoarthritis (OA), and the imaging findings may be subtle. As a result, clinicians and radiologists have developed numerous measurements to detect and quantify patellofemoral alignment. Additional entities, such as femorotibial subluxation or angular abnormalities, may only be detected by using standardized measurements and can help detect ligamentous insufficiency or developmental malalignment, which can lead to instability and OA in the medial and lateral femorotibial compartments. Finally, the proper positioning and hardware selection for knee arthroplasty are critical to preventing early hardware failure and postsurgical pain. This review, which focuses on the knee, is the second in a three-part series discussing the appropriate imaging modalities on which to obtain specific lower extremity measurements as well as proper measurement techniques, grouped by pathology. Furthermore, the normal value or range of values according to current literature is reported, along with the significance of abnormal measurements.