Magnetic resonance imaging (MRI) of the knee: Identification of difficult-to-diagnose meniscal lesions

被引:35
|
作者
Lecouvet, F. [1 ]
Van Haver, T. [1 ]
Acid, S. [1 ]
Perlepe, V. [1 ]
Kirchgesner, T. [1 ]
Vande Berg, B. [1 ]
Triqueneaux, P. [1 ]
Denis, M-L [1 ]
Thienpont, E. [1 ]
Malghem, J. [1 ]
机构
[1] UCL, Clin Univ St Luc, IREC, Dept Radiol & Med Imaging, Ave Hippocrate 10-2942, B-1200 Brussels, Belgium
关键词
Knee; Meniscus; Arthroscopy; Magnetic resonance imaging (MRI); BUCKET-HANDLE TEARS; CRUCIATE LIGAMENT INJURY; POSTERIOR HORN; MEDIAL MENISCUS; MENISCOCAPSULAR SEPARATION; LATERAL MENISCUS; SIGN; PATTERNS; CLASSIFICATION; ACCURACY;
D O I
10.1016/j.diii.2017.12.005
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
This article characterizes common meniscal pathologies, reviews magnetic resonance imaging (MRI) diagnostic criteria for meniscal tears, and identifies difficult-to-detect tears and fragments and the best MRI sequences and practices for recognizing these lesions. These difficult-to-diagnose meniscal lesions that radiologists should consider include tears, meniscocapsular separation lesions, and displaced meniscal fragments. Meniscus tears are either vertical, which are generally associated with traumatic injury, horizontal, which are associated with degenerative injury, or combinations of both. MRI has a high sensitivity for tears but not for fragments; MRI performance is also better for medial than lateral meniscal lesions. Fragment detection can be improved by recognizing signs secondary to migration, especially signs of epiphyseal irritation and mechanical impingement. Radial and peripheral tears, as well as those close to the posterior horn insertion, have been traditionally difficult to detect, but improvements in arthroscopic knowledge, identification of common lesion patterns, and selection of the proper MRI sequence and plane for each lesion type mean that, when properly used, MRI is an invaluable tool in detecting all types of meniscal tears. (C) 2017 Editions francaises de radiologie. Published by Elsevier Masson SAS. All rights reserved.
引用
收藏
页码:55 / 64
页数:10
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