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. 1986 Sep-Oct;14(5):361-70.
doi: 10.1177/036354658601400503.

Magnetic resonance imaging as a tool for evaluation of traumatic knee injuries. Anatomical and pathoanatomical correlations

Magnetic resonance imaging as a tool for evaluation of traumatic knee injuries. Anatomical and pathoanatomical correlations

B R Mandelbaum et al. Am J Sports Med. 1986 Sep-Oct.

Abstract

Traumatic injury to the knee remains a diagnostic and therapeutic challenge. Magnetic resonance imaging (MRI) has been applied to musculoskeletal pathoanatomy and has been shown to be an effective tool for definition and characterization of knee pathology. A systematic approach is taken to establish anatomical and pathoanatomical correlations, as well as the role of MRI in the management of knee injuries. Imaging was performed at the UCLA Medical Center using a permanent magnet system and a combination of solenoidal surface coils and thin-section, high-resolution scanning techniques. Images depict structural anatomical and spatial details of the knee that correlate well with corresponding cadaveric cryosections. To determine pathoanatomical correlations and the efficacy of MRI, 105 patients with preoperative diagnoses of meniscal tears, anterior and posterior cruciate ligament tears, tibial plateau fracture, and patella and quadriceps injuries were imaged. Results indicated that for the medial meniscus MRI demonstrated a 95.7% sensitivity, 81.8% specificity, 90% accuracy, 88.2% positive predictive value (PPV), and 93.1% negative predictive value (NPV). Imaging of the lateral meniscus demonstrated a 75% sensitivity, 95% specificity, 91% accuracy, 80% PPV, and 94% NPV. MRI of the ACL revealed 100% sensitivity, specificity, accuracy, positive and negative predictive values. MRI is a noninvasive tool which uses no ionizing radiation and can accurately define and characterize anatomy and pathoanatomy. This study indicates that MRI in conjunction with clinical evaluation can contribute to treatment decision-making processes and assist in preoperative planning. An algorithm demonstrating the potential clinical use of MRI is presented.

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