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Towards a Deformable Multi-surface Approach to Ligamentous Spine Models for Predictive Simulation-Based Scoliosis Surgery Planning

Authors :
H. Sheldon St-Clair
Austin Tapp
Sebastian Y. Bawab
Michel A. Audette
Craig Goodmurphy
Michael Polanco
Jérôme Schmid
Source :
Lecture Notes in Computer Science ISBN: 9783030137359, CSI@MICCAI
Publication Year :
2019
Publisher :
Springer International Publishing, 2019.

Abstract

Scoliosis correction surgery is typically a highly invasive procedure that involves either an anterior or posterior release, which respectively entail the resection of ligaments and bone facets from the front or back of the spine, in order to make it sufficiently compliant to enable the correction of the deformity. In light of progress in other areas of surgery in minimally invasive therapies, orthopedic surgeons have begun envisioning computer simulation-assisted planning that could answer unprecedented what-if questions. This paper presents preliminary steps taken towards simulation-based surgery planning that will provide answers as to how much anterior or posterior release is truly necessary, provided we also establish the amplitude of surgical forces involved in corrective surgery. This question motivates us to pursue a medical image-based anatomical modeling pipeline that can support personalized finite elements simulation, based on models of the spine that not only feature vertebrae and inter-vertebral discs (IVDs), but also descriptive ligament models. This paper suggests a way of proceeding, based on the application of deformable multi-surface Simplex model applied to a CAD-based representation of the spine that makes explicit all spinal ligaments, along with vertebrae and IVDs. It presents a preliminary model-based segmentation study whereby Simplex meshes of CAD vertebrae are registered to the subject’s corresponding vertebrae in CT data, which then drives ligament and IVD model registration by aggregation of neighboring vertebral transformations. This framework also anticipates foreseen improvements in MR imaging that could achieve better contrasts in ligamentous tissues in the future.

Details

ISBN :
978-3-030-13735-9
ISBNs :
9783030137359
Database :
OpenAIRE
Journal :
Lecture Notes in Computer Science ISBN: 9783030137359, CSI@MICCAI
Accession number :
edsair.doi...........7cf11ec8bf1346e80efa3dcbadb3582b
Full Text :
https://doi.org/10.1007/978-3-030-13736-6_8