New method to apply the lumbar lordosis of standing radiographs to supine CT-based virtual 3D lumbar spine models

Author:

Hajnal Benjamin,Eltes Peter Endre,Bereczki Ferenc,Turbucz Mate,Fayad Jennifer,Pokorni Agoston Jakab,Lazary Aron

Abstract

AbstractStanding 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.

Funder

Hungarian Scientific Research Fund

Doctoral Student Scholarship Program of the Co-operative Doctoral Program of the Ministry of Innovation and Technology, Hungary

European Commission

New National Excellence Program of the Ministry for Innovation and Technology from the source of the National Research, Development and Innovation Fund

Semmelweis University

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

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