ArticleScientific reports2022
New method to apply the lumbar lordosis of standing radiographs to supine CT-based virtual 3D lumbar spine models.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 7 citations in OpenAlex.
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- Tibia-Fibula Relative Motion During Gait Cycle by 2D-3D Registration.Journal of orthopaedic research : official publication of the Orthopaedic Research Society · 2025Article
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- Identification of a lumped-parameter model of the intervertebral joint from experimental data.Frontiers in bioengineering and biotechnology · 2024Article
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Authors and funding
7 authors at 2 institutions in 1 country.
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Abstract
Standing radiographs play an important role in the characterization of spinal sagittal alignment, as they depict the spine under physiologic loading conditions. However, there is no commonly available method to apply the lumbar lordosis of standing radiographs to supine CT-based virtual 3D models of the lumbar spine. We aimed to develop a method for the sagittal rigid-body registration of vertebrae to standing radiographs, using the exact geometry reconstructed from CT-data. In a cohort of 50 patients with monosegmental spinal degeneration, segmentation and registration of the lumbar vertebrae and sacrum were performed by two independent investigators. Intersegmental angles and lumbar lordosis were measured both in CT scans and radiographs. Vertebrae were registered using the X-ray module of Materialise Mimics software. Postregistrational midsagittal sections were constructed of the sagittal midplane sections of the registered 3D lumbar spine geometries. Mean Hausdorff distance was measured between corresponding registered vertebral geometries. The registration process minimized the difference between the X-rays' and postregistrational midsagittal sections' lordoses. Intra- and inter-rater reliability was excellent based on angle and mean Hausdorff distance measurements. We propose an accessible, accurate, and reproducible method for creating patient-specific 3D geometries of the lumbar spine that accurately represent spinal sagittal alignment in the standing position.
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