Magnetic resonance imaging (MRI) is the modality of choice for evaluating traumatic, degenerative, and overuse injuries of the knee. Its superior soft tissue contrast and multiplanar capabilities enable comprehensive assessment of menisci, ligaments, cartilage, bone marrow, and periarticular structures. Recent advances in accelerated MRI, including parallel imaging, simultaneous multislice acquisition, and deep learning-based reconstruction, allow high-resolution diagnostic MRI scans to be completed in under 5 min. MRI provides critical information for early diagnosis, surgical planning, and postoperative assessment, improving patient outcomes and reducing unnecessary arthroscopies. This chapter summarizes imaging protocols, key diagnostic criteria for common injuries, and practical interpretation strategies, emphasizing pattern recognition, combined injury assessment, and diagnostic pitfalls. The integration of rapid MRI protocols and artificial intelligence can improve workflow efficiency and performance in musculoskeletal MRI.

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MRI of the Knee

  • J. Fritz,
  • L. White

摘要

Magnetic resonance imaging (MRI) is the modality of choice for evaluating traumatic, degenerative, and overuse injuries of the knee. Its superior soft tissue contrast and multiplanar capabilities enable comprehensive assessment of menisci, ligaments, cartilage, bone marrow, and periarticular structures. Recent advances in accelerated MRI, including parallel imaging, simultaneous multislice acquisition, and deep learning-based reconstruction, allow high-resolution diagnostic MRI scans to be completed in under 5 min. MRI provides critical information for early diagnosis, surgical planning, and postoperative assessment, improving patient outcomes and reducing unnecessary arthroscopies. This chapter summarizes imaging protocols, key diagnostic criteria for common injuries, and practical interpretation strategies, emphasizing pattern recognition, combined injury assessment, and diagnostic pitfalls. The integration of rapid MRI protocols and artificial intelligence can improve workflow efficiency and performance in musculoskeletal MRI.