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Synovial sarcoma (SS) is a malignant tumor comprising 5-10% of all soft tissue sarcomas. SS has distinct characteristics, such as a predilection for young adults and relatively slow growth compared to other soft tissue sarcomas. Some patients with SS experience long-standing pain at the tumor site before the development of a palpable mass. Herein, we report the case of a 39-year-old woman with SS in the upper arm who presented with pain for > 20 years. The tumor detected on magnetic resonance imaging at 17 years was an SS. To the best of our knowledge, no English-language reports on imaging study-based identification of SS, which was undiagnosed for > 20 years, are known in the literature. This report discusses the imaging features of this latent lesion and the volume-doubling time of this unusual tumor.

Objective: This study aims to explore the feasibility of employing convolutional neural networks for detecting and localizing implant cutouts on anteroposterior pelvic radiographs.

Materials and methods: The research involves the development of two Deep Learning models. Initially, a model was created for image-level classification of implant cutouts using 40191 pelvic radiographs obtained from a single institution. The radiographs were partitioned into training, validation, and hold-out test datasets in a 6/2/2 ratio. Performance metrics including the area under the receiver operator characteristics curve (AUROC), sensitivity, and specificity were calculated using the test dataset. Additionally, a second object detection model was trained to localize implant cutouts within the same dataset. Bounding box visualizations were generated on images predicted as cutout-positive by the classification model in the test dataset, serving as an adjunct for assessing algorithm validity.

Results: The classification model had an accuracy of 99.7%, sensitivity of 84.6%, specificity of 99.8%, AUROC of 0.998 (95% CI: 0.996, 0.999) and AUPRC of 0.774 (95% CI: 0.646, 0.880). From the pelvic radiographs predicted as cutout-positive, the object detection model could achieve 95.5% localization accuracy on true positive images, but falsely generated 14 results from the 15 false-positive predictions.

Conclusion: The classification model showed fair accuracy for detection of implant cutouts, while the object detection model effectively localized cutout. This serves as proof of concept of using a deep learning-based approach for classification and localization of implant cutouts from pelvic radiographs.

Objective: Osteoporosis and falls are both prevalent in the elderly, and CT brain (CTB) is frequently performed post head-strike. We aim to validate the relationship between frontal bone density (Hounsfield unit) from routine CTB and bone mineral density from dual-energy X-ray absorptiometry (DEXA) scan for opportunistic osteoporosis screening.

Materials and methods: Patients who had a non-contrast CTB followed by a DEXA scan in the subsequent year were included in this multi-center retrospective study. The relationship between frontal bone density on CT and femoral neck T-score on DEXA was examined using ANOVA, Pearson's correlation, and receiver operating curve (ROC) analysis. Sensitivity, specificity, negative and positive predictive values, and area under the curve (AUC) were calculated.

Results: Three hundred twenty-six patients (205 females and 121 males) were analyzed. ANOVA analysis showed that frontal bone density was lower in patients with DEXA-defined osteoporosis (p < 0.001), while Pearson's correlation analysis demonstrated a fair correlation with femoral neck T-score (r = 0.3, p < 0.001). On subgroup analysis, these were true in females but not in males. On ROC analysis, frontal bone density weakly predicted osteoporosis (AUC 0.6, 95% CI 0.5-0.7) with no optimal threshold identified. HU < 610 was highly specific (87.5%) but poorly sensitive (18.9%). HU > 1200 in females had a strong negative predictive value for osteoporosis (92.6%, 95% CI 87.1-98.1%).

Conclusion: Frontal bone density from routine CTB is significantly different between females with and without osteoporosis, but not between males. However, frontal bone density was a weak predictor for DEXA-defined osteoporosis. Further research is required to determine the role of CTB in opportunistic osteoporosis screening.

Cubital tunnel syndrome (CuTS) is the second most common peripheral neuropathy in the upper limb. It occurs due to ulnar nerve compression within the fibro-osseous cubital tunnel at the elbow joint. Although CuTS is typically diagnosed clinically and with electrodiagnostic studies, the importance of imaging in evaluating the condition is growing. Knowing the typical imaging findings of ulnar nerve entrapment is necessary for precise diagnosis and proper treatment. In this article, we focus on the clinical features, workup and complex imaging of the "anatomic" cubital tunnel and relevant pathological entities.

Chordoma is a malignant bone tumor originating from notochordal remnants, most commonly occurring at the sacrococcygeal junction. We present a case of a 70-year-old male with chronic pain in the lower lumbar spine. MRI performed elsewhere revealed a large tumor that involved S4, S5, and the coccyx with a presacral soft tissue component. The lesion was heterogeneously hyperintense on T2-weighted images with a thick hypointense rim anteriorly. On T1-weighted images, the lesion showed a native hyperintense signal centrally probably due to hemorrhage. Based on this MRI, the diagnosis of chordoma was suggested. A spontaneous marked reduction in size was observed on a 4-week interval MRI performed at our institution before biopsy. Due to spontaneous tumor shrinkage along with peripheral enhancement, a differential diagnosis of infection or bleeding in a retrorectal cyst was proposed. This case teaches us that chordomas may contain a large hemorrhagic component, which is hyperintense on T1-weighted images and shows peripheral rim enhancement. Spontaneous shrinkage of a tumor may occur due to the resolution of a hematoma within weeks. Biopsy is key to obtain the correct diagnosis. Understanding the typical and more rare features of chordomas is key for MSK radiologists as well as pathologists. Chordomas are typically slow-growing tumors, but radiologists should be aware that intratumoral hemorrhage can lead to rapid changes in tumor size, which may be mistaken for either regression or progression of tumor. This case highlights the importance of considering hemorrhagic events within chordomas in the differential diagnosis when observing size fluctuations on imaging.

Objective: The purpose of this study is to analyze changes in the utilization of MRA of the hip and shoulder at a large tertiary care academic medical center during a period of significant technological advancements over the last 20 years.

Materials and methods: This retrospective cross-sectional analysis identified MRA of the hip and shoulder performed at our institution over a 20-year period (2/2003-2/2023) in relation to the total number of MR hip and shoulder examinations during the same period. Patient characteristics and referring provider demographic information were extracted. Descriptive statistics and trend analysis were performed.

Results: The total number of MRIs of the hip and shoulder increased overall, with small dips in 2020 and 2022. MRA of the hip increased significantly over the first 10 years of the study period (p = 0.0005), while MRA of the shoulder did not change significantly (p = 0.33). The proportion of both MRA of the hip and shoulder declined over the last 10 years (hip, p = 0.0056; shoulder, p = 0.0017). Over the same period, there was significant increase in the proportion of examinations performed at 3 Tesla versus 1.5 (p < 0.0001).

Conclusion: Overall, there was a downward trend in MR shoulder and hip arthrogram utilization in the second half of this 20-year study period. However, utilization varied somewhat by referring specialties and credentials. These changes are likely reflective of both improvements in image quality and evolving practice recommendations. Awareness of such trends may be valuable in ensuring appropriate patient care, as well as for anticipating the needs of a musculoskeletal radiology practice.

Objective: Although SLAP-5 lesions are associated with recurrent dislocations, their causes and pathomechanisms have not been fully elucidated. This study aimed to investigate the association between SLAP-5 lesions and scapular morphology in traumatic anterior shoulder instability (ASI). We hypothesized that there may be a relationship between SLAP-5 lesions and scapular morphology in traumatic ASI patients.

Materials and methods: The study included 74 patients with isolated Bankart lesions and 69 with SLAP-5 lesions who underwent arthroscopic labral repair for ASI. Critical shoulder angle (CSA) was measured on the roentgenograms, while glenoid inclination (GI) and glenoid version (GV) were measured on magnetic resonance imaging (MRI) by two observers in two separate sessions blinded to each other. Both groups were compared in terms of CSA, GI, and GV.

Results: The mean ages of Bankart and SLAP-5 patients were 28.4±9.1 and 27.9±7.7 (P=0.89), respectively; their mean CSA values were 33.1°±2.6° and 28.2°±2.4°, respectively (P<0.001). The ROC analysis's cut-off value was 30.5°, with 75.0% sensitivity and 76.7% specificity (AUC = 0.830). SLAP-5 lesions were more common on the dominant side than isolated Bankart lesions (P=0.021), but no difference was found between the groups in terms of GI and GV (P=0.334, P=0.081, respectively).

Conclusions: In ASI, low CSA values appeared to be related to SLAP-5 lesions, and the cut-off value of CSA for SLAP lesion formation was 30.5° with 75.0% sensitivity and 76.7% specificity. Scapula morphology may be related to the SLAP-5 lesions, and CSA can be used as an additional parameter in provocative diagnostic tests and medical imaging techniques for the detection of SLAP lesions accompanying Bankart lesions.

Level of evidence: III retrospective case-control study.

Objective: To develop MRI-derived carpal kinematic metrics and investigating their stability.

Methods: The study used a 4D MRI method to track scaphoid, lunate, and capitate movements in the wrist. A panel of 120 metrics for radial-ulnar deviation and flexion-extension was created using polynomial models of scaphoid and lunate movements relative to the capitate. Intraclass correlation coefficients (ICCs) analyzed intra- and inter-subject stability in 49 subjects, 20 with and 29 without wrist injury history.

Results: Comparable degrees of stability were observed across the two different wrist movements. Among the total 120 derived metrics, distinct subsets demonstrated high stability within each type of movement. For asymptomatic subjects, 16 out of 17 metrics with high intra-subject stability also showed high inter-subject stability. The differential analysis of ICC values for each metric between asymptomatic and symptomatic cohorts revealed specific metrics (although relatively unstable) exhibiting greater variability in the symptomatic cohort, thereby highlighting the impact of wrist conditions on the variability of kinematic metrics.

Conclusion: The findings demonstrate the developing potential of dynamic MRI for assessing and characterizing complex carpal bone dynamics. Stability analyses of the derived kinematic metrics revealed encouraging differences between cohorts with and without wrist injury histories. Although these broad metric stability variations highlight the potential utility of this approach for analyzing carpal instability, further studies are necessary to better characterize these observations.