STUDY DESIGN: Prospective study of the 3-D shape variability of spinal curve in Lenke type 1 adolescent idiopathic scoliosis (AIS). OBJECTIVES: To determine the statistical 3-D variability of Lenke type 1 curves and to evaluate clinical parameters that can be integrated to refine the Lenke et al original proposal, and to pave the road for a comprehensive 3-D subclassification of AIS. SUMMARY OF BACKGROUND DATA: Several classification systems based on the identification of key features from frontal and sagittal x-rays have been proposed in AIS, but these remain an oversimplification of the complex 3-D deformity because it is only based on 2-D imaging. Clinical 3-D parameter variability has been investigated in previous studies, but has never been considered in the context of the Lenke classification. METHODS: Radiographs of 68 AIS patients with Lenke type 1 curves were reconstructed in 3-dimension using a stereo-radiographic technique and were submitted to a computer algorithm to compute a set of 3-D parameters that can be used to characterize the 3-D curve. Cluster analysis was performed to determine the statistical distribution of 3-D parameters among Lenke 1 curve types. RESULTS: Statistical analysis shows specific 3-D deformation patterns within Lenke type 1 curves, mostly using the best-fit plane or BFP (SD+/-22.9, +/-49.8) and geometric torsion parameters. No significant variability was found using the plane of maximum curvature or PMC. CONCLUSIONS: Recent advances in computer vision facilitate the introduction of 3-D reconstruction in a standard clinical setting and can provide more information toward the spine behavior in 3-D space. A direct consequence of commonly used 3-D reconstruction would be to be able to evaluate 3-D indices and to devise a real 3-D classification system from the Lenke et al proposal.
STUDY DESIGN: Prospective study of the 3-D shape variability of spinal curve in Lenke type 1 adolescent idiopathic scoliosis (AIS). OBJECTIVES: To determine the statistical 3-D variability of Lenke type 1 curves and to evaluate clinical parameters that can be integrated to refine the Lenke et al original proposal, and to pave the road for a comprehensive 3-D subclassification of AIS. SUMMARY OF BACKGROUND DATA: Several classification systems based on the identification of key features from frontal and sagittal x-rays have been proposed in AIS, but these remain an oversimplification of the complex 3-D deformity because it is only based on 2-D imaging. Clinical 3-D parameter variability has been investigated in previous studies, but has never been considered in the context of the Lenke classification. METHODS: Radiographs of 68 AIS patients with Lenke type 1 curves were reconstructed in 3-dimension using a stereo-radiographic technique and were submitted to a computer algorithm to compute a set of 3-D parameters that can be used to characterize the 3-D curve. Cluster analysis was performed to determine the statistical distribution of 3-D parameters among Lenke 1 curve types. RESULTS: Statistical analysis shows specific 3-D deformation patterns within Lenke type 1 curves, mostly using the best-fit plane or BFP (SD+/-22.9, +/-49.8) and geometric torsion parameters. No significant variability was found using the plane of maximum curvature or PMC. CONCLUSIONS: Recent advances in computer vision facilitate the introduction of 3-D reconstruction in a standard clinical setting and can provide more information toward the spine behavior in 3-D space. A direct consequence of commonly used 3-D reconstruction would be to be able to evaluate 3-D indices and to devise a real 3-D classification system from the Lenke et al proposal.
Authors: Edgar García-Cano; Fernando Arámbula Cosío; Luc Duong; Christian Bellefleur; Marjolaine Roy-Beaudry; Julie Joncas; Stefan Parent; Hubert Labelle Journal: Med Biol Eng Comput Date: 2018-06-09 Impact factor: 2.602
Authors: Stefano Negrini; Sabrina Donzelli; Angelo Gabriele Aulisa; Dariusz Czaprowski; Sanja Schreiber; Jean Claude de Mauroy; Helmut Diers; Theodoros B Grivas; Patrick Knott; Tomasz Kotwicki; Andrea Lebel; Cindy Marti; Toru Maruyama; Joe O'Brien; Nigel Price; Eric Parent; Manuel Rigo; Michele Romano; Luke Stikeleather; James Wynne; Fabio Zaina Journal: Scoliosis Spinal Disord Date: 2018-01-10