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Our 10-year institutional experience demonstrates that WBMRI facilitates early detection of extrapulmonary MLS metastases before the onset of clinical symptoms and pulmonary metastases. WBMRI also depicts extrapulmonary metastases that are occult on CT scans. The current surveillance strategies are insufficient for screening for extrapulmonary MLS metastases.

There is an anecdotal need to increase radiology education in medical school. Surveys were distributed to three medical schools, with a respondency of 55 %. Over 91 % of students believed there should be more radiology teaching in medical school. Students prefer different methods of teaching, lectures, group learning, and web-based modules.

Artificial intelligence (AI) will transform every step in the imaging value chain, including interpretive and noninterpretive components. Radiologists should familiarize themselves with AI developments to become leaders in their clinical implementation. This article explores the impact of AI through the entire imaging cycle of musculoskeletal radiology, from the placement of the requisition to the generation of the report, with an added Canadian perspective. Noninterpretive tasks which may be assisted by AI include the ordering of appropriate imaging tests, automatic exam protocoling, optimized scheduling, shorter magnetic resonance imaging acquisition time, computed tomography imaging with reduced artifact and radiation dose, and new methods of generation and utilization of radiology reports. Applications of AI for image interpretation consist of the determination of bone age, body composition measurements, screening for osteoporosis, identification of fractures, evaluation of segmental spine pathology, detection and temporal monitoring of osseous metastases, diagnosis of primary bone and soft tissue tumors, and grading of osteoarthritis.

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