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Recent advances in musculoskeletal (MSK) radiology have markedly improved diagnostic accuracy through innovations in MRI, CT, and artificial intelligence (AI). This review summarizes 7 key domains shaping current MSK imaging: (1) CT-like contrast MRI techniques for bone visualization, (2) quantitative MRI approaches, (3) AI applications in image reconstruction and diagnostic support, (4) MR spectroscopy (MRS) for metabolic assessment, (5) whole-body MRI for systemic disease evaluation, (6) positron emission tomography (PET) for metabolic and inflammatory imaging, and (7) advanced CT techniques such as weight-bearing CT. Zero echo time and ultrashort echo time MRI sequences enable the visualization and quantitative assessment of short-T2 tissues such as cortical bone, tendons, and fibrocartilage. Deep learning-based image reconstruction improves SNR and shortens scan time, enhancing image quality and diagnostic confidence. In parallel, AI-driven diagnostic support systems, including convolutional neural networks for lesion detection and natural language processing for report generation, are transforming workflow efficiency and consistency. MRS offers metabolic insights into muscle disorders such as sarcopenia, and whole-body-MRI provides comprehensive, radiation-free evaluation of tumor burden and inflammatory joint or enthesis involvement, making it valuable in oncology and rheumatic diseases. PET complements MRI by identifying metabolically active or inflammatory lesions. CT-based innovations further contribute to evaluating joint biomechanics with high spatial resolution. Together, these technological developments are enabling earlier disease detection, more precise diagnosis, and improved treatment monitoring, representing a paradigm shift in MSK imaging and clinical practice.
Ide et al. (Wed,) studied this question.