• Shanu Gambhir, Tian Wang, Matthew H Pelletier, William R Walsh, and Jonathon R Ball.
• Royal North Shore Hospital, St Leonards, New South Wales, Australia.
• World Neurosurg. 2019 Jun 1; 126: e606-e611.

BackgroundConsideration of sagittal alignment is an integral part of spinal fusion surgery correlating with superior outcomes. Segmental lordosis is an important contributor to sagittal alignment. This study assessed surgical factors influencing segmental lordosis in a 360° fusion model, including cage dimensions, anterior longitudinal ligament resection, facetectomy, and posterior compression.MethodsSix L3-4 synthetic spinal motion segments were used in a repeated measures design. Each sample was sequentially instrumented with lateral cages of increasing height and angle. Lordosis was assessed from lateral radiographs of intact and each instrumented condition. The effect of anterior longitudinal ligament resection, posterior compression with pedicle screws, and bilateral facetectomy was additionally examined.ResultsA linear relationship between segmental lordosis and cage height was found. This effect was greater with the anterior longitudinal ligament divided. In cages of the same anterior height, increased intrinsic cage lordosis did not result in increased segmental lordosis; cages with no intrinsic lordosis resulted in the highest segmental lordosis. In examining this finding, it was shown that posterior cage height had a larger influence on segmental lordosis. Posterior compression with pedicle screws and bilateral facetectomy increased the segmental lordosis by a further 3.4° and 2.6°, respectively.ConclusionsCage height was a key factor, with posterior compression further increasing lordosis. The finding that 0° cages results in the most segmental lordosis was an unexpected finding and highlights the importance of appropriate sizing on resulting lordosis. These findings are relevant to cage selection but require further study prior to applying to clinical practice and may influence future cage design.Copyright © 2019 Elsevier Inc. All rights reserved.

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