Statistical shape modeling characterizes three-dimensional shape and alignment variability in the lumbar spine.

ABSTRACT

The mechanics of the lumbar spine are heavily dependent on the underlying anatomy. Anatomical measures are used to assess the progression of pathologies related to low back pain and to screen patients for surgical treatment options. To describe anatomical norms and pathological differences for the population, statistical shape modeling, which uses full three-dimensional representations of bone morphology and relative alignment, can capture intersubject variability and enable comparative evaluations of subject to population. Accordingly, the objective of this study was to develop a comprehensive set of three-dimensional statistical models to characterize anatomical variability in the lumbar spine, by specifically describing the shape of individual vertebrae, and shape and alignment of the entire lumbar spine (L1-S1), with a focus on the L4-L5 and L5-S1 functional spinal units (FSU). Using CT scans for a cohort of 52 patients, lumbar spine geometries were registered to a template to establish correspondence and a principal component analysis identified the primary modes of variation. Scaling was the most prevalent mode of variation for all models. Subsequent modes of the statistical shape models of the individual bones characterized shape variation within the processes. Subsequent modes of variation for the FSU and entire spine models described alignment changes associated with disc height and lordosis. Quantification of anatomical variation in the spine with statistical models can inform implant design and sizing, assist clinicians in diagnosing pathologies, screen patients for treatment options, and support pre-operative planning.