Neck pain with prevertebral soft tissue thickening

10.47102/annals-acadmedsg.2022112Annals of the Academy of Medicine, Singapore518520-52

Multiple Myeloma: Case of a “Moving” Sternal Wire

Multiple myeloma generally occurs in older adults, with the clonal proliferation of plasma cells and accumulation of monoclonal protein resulting in a broad range of clinical manifestations and complications, including hypercalcemia, renal dysfunction, anaemia, and bone destruction (termed CRAB features). A 64-year-old man with no history of malignancy presented with an enlarging precordial lump occurring three years post-sternotomy for uneventful coronary artery bypass grafting surgery. Initial investigations showed anaemia and impaired renal function. Multimodal imaging performed for further evaluation showcases the radio-pathological features which can be encountered in haematological malignancy. Subsequent percutaneous biopsy confirmed an underlying plasma cell neoplasm, and a diagnosis of multiple myeloma was achieved. The prompt resolution of the lesions upon the initiation of treatment highlights the importance of early diagnosis and treatment

The peroneus longus muscle and tendon: a review of its anatomy and pathology.

This article will review the anatomy and common pathologies affecting the peroneus longus muscle and tendon. The anatomy of the peroneus longus is complex and its long course can result in symptomatology referable to the lower leg, ankle, hindfoot, and plantar foot. Proximally, the peroneus longus muscle lies within the lateral compartment of the lower leg with its distal myotendinous junction arising just above the level of the ankle. The distal peroneus longus tendon has a long course and makes two sharp turns at the lateral ankle and hindfoot before inserting at the medial plantar foot. A spectrum of pathology can occur in these regions. At the lower leg, peroneus longus muscle injuries (e.g., denervation) along with retromalleolar tendon instability/subluxation will be discussed. More distally, along the lateral calcaneus and cuboid tunnel, peroneus longus tendinosis and tears, tenosynovitis, and painful os peroneum syndrome (POPS) will be covered. Pathology of the peroneus longus will be illustrated using clinical case examples along its entire length; these will help the radiologist understand and interpret common peroneus longus disorders

Measurement of haem and total iron in fish, shrimp and prawn using ICP-MS: implications for dietary iron intake calculations

Twenty-five species of fish, shrimp and prawn from local markets in Bangladesh were analysed for concentrations of total Fe, haem Fe and non-haem Fe by ICP-MS. Total Fe and non-haem Fe concentrations were measured in nitric acid-digested samples and haem Fe was extracted using acidified 80% acetone for 60 min. Total Fe concentrations ranged from 0.55–14.43 mg/100 g FW, and haem Fe% ranged from 18%–93% of total Fe. Repeat extractions with 80% acetone recovered additional haem Fe, suggesting that previous measurement by this technique may have underestimated haem Fe content. Calculation of Fe balance (summing Fe in acetone extracts and Fe in the residue after haem Fe extraction) was not significantly different from total Fe, indicating the two processes recovered the different forms of Fe with similar effectiveness

Eye Globe Abnormalities on MR and CT in Adults: An Anatomical Approach

10.3348/kjr.2016.17.5.664KOREAN JOURNAL OF RADIOLOGY175664-67

Application of Artificial Intelligence Methods on Osteoporosis Classification with Radiographs—A Systematic Review

Osteoporosis is a complex endocrine disease characterized by a decline in bone mass and microstructural integrity. It constitutes a major global health problem. Recent progress in the field of artificial intelligence (AI) has opened new avenues for the effective diagnosis of osteoporosis via radiographs. This review investigates the application of AI classification of osteoporosis in radiographs. A comprehensive exploration of electronic repositories (ClinicalTrials.gov, Web of Science, PubMed, MEDLINE) was carried out in adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 statement (PRISMA). A collection of 31 articles was extracted from these repositories and their significant outcomes were consolidated and outlined. This encompassed insights into anatomical regions, the specific machine learning methods employed, the effectiveness in predicting BMD, and categorizing osteoporosis. Through analyzing the respective studies, we evaluated the effectiveness and limitations of AI osteoporosis classification in radiographs. The pooled reported accuracy, sensitivity, and specificity of osteoporosis classification ranges from 66.1% to 97.9%, 67.4% to 100.0%, and 60.0% to 97.5% respectively. This review underscores the potential of AI osteoporosis classification and offers valuable insights for future research endeavors, which should focus on addressing the challenges in technical and clinical integration to facilitate practical implementation of this technology