Computer-assisted intra-operative verification of surgical outcome for the treatment of syndesmotic injuries through contralateral side comparison.


Journal

International journal of computer assisted radiology and surgery
ISSN: 1861-6429
Titre abrégé: Int J Comput Assist Radiol Surg
Pays: Germany
ID NLM: 101499225

Informations de publication

Date de publication:
Dec 2019
Historique:
received: 16 02 2019
accepted: 26 07 2019
pubmed: 9 8 2019
medline: 26 2 2020
entrez: 9 8 2019
Statut: ppublish

Résumé

Fracture reduction and fixation of syndesmotic injuries is a common procedure in trauma surgery. An intra-operative evaluation of the surgical outcome is challenging due to high inter-individual anatomical variation. A comparison to the contralateral uninjured ankle would be highly beneficial but would also incur additional radiation and time consumption. In this work, we pioneer automatic contralateral side comparison while avoiding an additional 3D scan. We reconstruct an accurate 3D surface of the uninjured ankle joint from three low-dose 2D fluoroscopic projections. Through CNN complemented 3D shape model segmentation, we create a reference model of the injured ankle while addressing the issues of metal artifacts and initialization. Following 2D-3D multiple bone reconstruction, a final reference contour can be created and matched to the uninjured ankle for contralateral side comparison without any user interaction. The accuracy and robustness of individual workflow steps were assessed using 81 C-arm datasets, with 2D and 3D images available for injured and uninjured ankles. Furthermore, the entire workflow was tested on eleven clinical cases. These experiments showed an overall average Hausdorff distance of [Formula: see text] mm measured at clinical evaluation level. Reference contours of the contralateral side reconstructed from three projection images can assist surgeons in optimizing reduction results, reducing the duration of radiation exposure and potentially improving postoperative outcomes in the long term.

Identifiants

pubmed: 31392672
doi: 10.1007/s11548-019-02043-8
pii: 10.1007/s11548-019-02043-8
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2211-2220

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Auteurs

Sarina Thomas (S)

Division of Medical Image Computing (E230), German Cancer Research Center, Heidelberg, Germany. s.thomas@dkfz-heidelberg.de.
Medical faculty, University of Heidelberg, Heidelberg, Germany. s.thomas@dkfz-heidelberg.de.

Fabian Isensee (F)

Division of Medical Image Computing (E230), German Cancer Research Center, Heidelberg, Germany.

Simon Kohl (S)

Division of Medical Image Computing (E230), German Cancer Research Center, Heidelberg, Germany.

Maxim Privalov (M)

MINTOS Research group, BG Trauma Center, Ludwigshafen, Germany.

Nils Beisemann (N)

MINTOS Research group, BG Trauma Center, Ludwigshafen, Germany.

Benedict Swartman (B)

MINTOS Research group, BG Trauma Center, Ludwigshafen, Germany.

Holger Keil (H)

MINTOS Research group, BG Trauma Center, Ludwigshafen, Germany.

Sven Y Vetter (SY)

MINTOS Research group, BG Trauma Center, Ludwigshafen, Germany.

Jochen Franke (J)

MINTOS Research group, BG Trauma Center, Ludwigshafen, Germany.

Paul A Grützner (PA)

MINTOS Research group, BG Trauma Center, Ludwigshafen, Germany.

Lena Maier-Hein (L)

Division of Computer-Assisted Medical Interventions (E130), German Cancer Research Center, Heidelberg, Germany.

Marco Nolden (M)

Division of Medical Image Computing (E230), German Cancer Research Center, Heidelberg, Germany.

Klaus Maier-Hein (K)

Division of Medical Image Computing (E230), German Cancer Research Center, Heidelberg, Germany.

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Classifications MeSH