Biomechanical Morphing for Personalized Fitting of Scoliotic Torso Skeleton Models.

biomechanical models geometry fitting low-dose x-rays modeling of the torso scoliosis

Journal

Frontiers in bioengineering and biotechnology
ISSN: 2296-4185
Titre abrégé: Front Bioeng Biotechnol
Pays: Switzerland
ID NLM: 101632513

Informations de publication

Date de publication:
2022
Historique:
received: 16 05 2022
accepted: 23 06 2022
entrez: 5 8 2022
pubmed: 6 8 2022
medline: 6 8 2022
Statut: epublish

Résumé

The use of patient-specific biomechanical models offers many opportunities in the treatment of adolescent idiopathic scoliosis, such as the design of personalized braces. The first step in the development of these patient-specific models is to fit the geometry of the torso skeleton to the patient's anatomy. However, existing methods rely on high-quality imaging data. The exposure to radiation of these methods limits their applicability for regular monitoring of patients. We present a method to fit personalized models of the torso skeleton that takes as input biplanar low-dose radiographs. The method morphs a template to fit annotated points on visible portions of the spine, and it relies on a default biomechanical model of the torso for regularization and robust fitting of hardly visible parts of the torso skeleton, such as the rib cage. The proposed method provides an accurate and robust solution to obtain personalized models of the torso skeleton, which can be adopted as part of regular management of scoliosis patients. We have evaluated the method on ten young patients who participated in our study. We have analyzed and compared clinical metrics on the spine and the full torso skeleton, and we have found that the accuracy of the method is at least comparable to other methods that require more demanding imaging methods, while it offers superior robustness to artifacts such as interpenetration of ribs. Normal-dose X-rays were available for one of the patients, and for the other nine we acquired low-dose X-rays, allowing us to validate that the accuracy of the method persisted under less invasive imaging modalities.

Identifiants

pubmed: 35928945
doi: 10.3389/fbioe.2022.945461
pii: 945461
pmc: PMC9343806
doi:

Types de publication

Journal Article

Langues

eng

Pagination

945461

Informations de copyright

Copyright © 2022 Koutras, Shayestehpour, Pérez, Wong, Rasmussen, Tournier, Nesme and Otaduy.

Déclaration de conflit d'intérêts

Authors MT and MN were employed by the company AnatoScope SA. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Christos Koutras (C)

Department of Computer Science, Universidad Rey Juan Carlos, Madrid, Spain.

Hamed Shayestehpour (H)

Department of Materials and Production, Aalborg University, Aalborg, Denmark.

Jesús Pérez (J)

Department of Computer Science, Universidad Rey Juan Carlos, Madrid, Spain.

Christian Wong (C)

Orthopedics Department, University Hospital of Hvidovre, Hvidovre, Denmark.

John Rasmussen (J)

Department of Materials and Production, Aalborg University, Aalborg, Denmark.

Maxime Tournier (M)

AnatoScope SA, Montbonnot-Saint-Martin, France.

Matthieu Nesme (M)

AnatoScope SA, Montbonnot-Saint-Martin, France.

Miguel A Otaduy (MA)

Department of Computer Science, Universidad Rey Juan Carlos, Madrid, Spain.

Classifications MeSH