Abstract
Unilateral cervical facet joint dislocation (UCFJD) is the most frequently missed cervical spine injury on plain radiographs. If left untreated, UCFJD can progress to bilateral cervical facet joint dislocation. Given the complexity of cervical facet joint dislocations, radiologists rely on metaphorical signs to identify them on radiographs. The "Bow-tie" and "laminar space" signs represent UCFJD on plain radiographs. The "reversed hamburger", "naked facet" and "headphones" signs represent cervical facet joint dislocations on axial cross-sectional imaging. Illustrating these signs in an engaging manner facilitates pattern-based recognition, which can benefit trainees and radiologists. Moreover, pattern-based recognition can be applied to machine learning.