
While conventional structural magnetic resonance imaging (MRI) can detect cruciate ligament anatomy and injuries, it has inherent limitations. Recently, novel MRI technologies such as quantitative MRI and artificial intelligence (AI) have emerged to mitigate these shortcomings, providing critical quantitative insights beyond gross morphological imaging and poised to expand current knowledge in assessing cruciate ligament injuries and to facilitate clinical decision making. Quantitative MRI serves as a noninvasive histological and quantification tool, which significantly improves the evaluation of degeneration and repair processes. AI plays a crucial role in automating radiological estimations and enabling data-driven predictions of future events. Despite the transformative impact of advanced MRI techniques on the analytical and diagnostic algorithms related to cruciate ligament disorders, future efforts are warranted to address challenges such as economic burdens and ethical considerations.
Orthopedic surgery, pcl, magnetic resonance imaging, knee, deep learning, Knee, artificial intelligence, RD701-811, acl injury
Orthopedic surgery, pcl, magnetic resonance imaging, knee, deep learning, Knee, artificial intelligence, RD701-811, acl injury
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