Abstract

BackgroundThe Spine Trauma Study Group (STSG) has proposed a novel thoracolumbar injury classification system and score (TLICS) in an attempt to define traumatic spinal injuries and direct appropriate management schemes objectively. The TLICS assigns specific point values based on three variables to generate a final severity score that guides potential treatment options. Within this algorithm, significant emphasis has been placed on posterior ligamentous complex (PLC) integrity. The purpose of this study was to determine the interrater reliability of indicators surgeons use when assessing PLC disruption on imaging studies, including computed tomography (CT) and magnetic resonance imaging (MRI). MethodsOrthopedic surgeons and neurosurgeons retrospectively reviewed a series of thoracolumbar injury case studies. Thirteen case studies, including images, were distributed to STSG members for individual, independent evaluation of the following three criteria: (1) diastasis of the facet joints on CT; (2) posterior edema-like signal in the region of PLC components on sagittal T2-weighted fat saturation (FAT SAT) MRI; and (3) disrupted PLC components on sagittal T1-weighted MRI. Interrater agreement on the presence or absence of each of the three criteria in each of the 13 cases was assessed. ResultsAbsolute interrater percent agreement on diastasis of the facet joints on CT and posterior edema-like signal in the region of PLC components on sagittal T2-weighted FAT SAT MRI was similar (agreement 70.5%). Interrater agreement on disrupted PLC components on sagittal T1-weighted MRI was 48.9%. Facet joint diastasis on CT was the most reliable indicator of PLC disruption as assessed by both Cohen’s kappa (κ = 0.395) and intraclass correlation coefficient (ICC 0.430). ConclusionsThe interrater reliability of assessing diastasis of the facet joints on CT had fair to moderate agreement. The reliability of assessing the posterior edema-like signal in the region of PLC components was lower but also fair, whereas the reliability of identifying disrupted PLC components was poor.

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