Purpose: To evaluate the sensitivity, specificity and accuracy of various magnetic resonance imaging (MRI) features in differentiating vertebral compression fractures caused by malignancy, osteoporosis, and infections.
Methods: 35 men and 45 women aged 40 to 78 (mean, 59) years underwent MRI to assess the underlying pathology of already diagnosed vertebral compression fractures (n=152). The interval from presentation to imaging ranged from 7 to 95 (mean, 62) days. MRI features of each vertebral compression fracture were assessed. The sensitivity, specificity, and accuracy for each of the MRI features were calculated. Association between each MRI feature and various underlying pathologies (malignancy, osteoporosis, and infections) of vertebral compression fractures was evaluated.
Results: Regarding these 80 patients, the MRI diagnosis was correct in 78 and inconclusive in 2 with malignancy. MRI features suggestive of malignant fractures were a convex posterior border of the vertebral body, pedicle involvement, posterior neural element involvement, an epidural mass, a paraspinal mass, and other spinal metastases. MRI features suggestive of osteoporotic fractures were retropulsion, low signal intensity band, spared normal marrow signal intensity, and the fluid sign. MRI features suggestive of infective fractures were contiguous vertebral involvement, end plate disruption, disc involvement, and paraspinal and epidural abscesses.
Conclusion: Combination of several MRI features can provide clues to differentiate between malignant, osteoporotic, and infective vertebral compression fractures.
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http://dx.doi.org/10.1177/230949901101900203 | DOI Listing |
BMC Med Imaging
January 2025
Department of Ultrasound Medicine, First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China.
Background: Langerhans cell histiocytosis (LCH) is a rare disease, most prevalent in children. Ultrasound is a noninvasive, cheap, and widely available technique. However, systematic elucidation of sonographic features of LCH and treatment related follow-up are relatively few, resulting in overall underestimation of the clinical value of ultrasound in diagnosing and monitoring LCH.
View Article and Find Full Text PDFInt Ophthalmol
January 2025
Department of Ophtalmology, Dokuz Eylul University School of Medicine, Izmir, Turkey.
Purpose: This retrospective study aimed to characterize the clinical features, histopathological findings, and treatment outcomes of patients diagnosed with orbital inflammatory disease (OID) co-managed by the rheumatology and ophthalmology departments in a tertiary hospital.
Methods: Medical records of 14 patients with OID were analyzed. Data on demographics, clinical presentation, laboratory investigations, radiological imaging, histopathological results, treatment regimens, and disease outcomes were collected and reviewed.
Insights Imaging
January 2025
Department of Radiology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China.
Objective: To assess the utility of clinical and MRI features in distinguishing ovarian clear cell carcinoma (CCC) from adnexal masses with ovarian-adnexal reporting and data system (O-RADS) MRI scores of 4-5.
Methods: This retrospective study included 850 patients with indeterminate adnexal masses on ultrasound. Two radiologists evaluated all preoperative MRIs using the O-RADS MRI risk stratification system.
AJNR Am J Neuroradiol
January 2025
Department of Neurology, Cliniques Universitaires Saint-Luc, Université catholique de Louvain, Brussels, Belgium.
Purpose: Posterior fossa ring-enhancing lesions (PFREL) in the adult immunocompetent hosts pose a diagnostic challenge. We aimed to evaluate the spectrum of PFREL etiologies and propose a diagnostic algorithm.
Methods: This study involved a retrospective analysis of PFREL cases from our institution (January 2023 to April 2024) and a systematic literature review conducted using Embase and PubMed databases following the PRISMA 2020 guidelines.
Magn Reson Imaging
January 2025
GE Healthcare, Guangzhou 510623, China.
Background: Accurate preoperative prediction of vascular invasion in breast cancer is crucial for surgical planning and patient management. MRI radiomics has shown promise in enhancing diagnostic precision. This study aims to evaluate the effectiveness of integrating MRI radiomic features with clinical data using a deep learning approach to predict vascular invasion in breast cancer patients.
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