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Accurate reconstructions of pelvic defects and discontinuities using statistical shape models.


ABSTRACT: Treatment of large acetabular defects and discontinuities remains challenging and relies on the accurate restoration of the native anatomy of the patient. This study introduces and validates a statistical shape model for the reconstruction of acetabular discontinuities with severe bone loss through a two-sided Markov Chain Monte Carlo reconstruction method. The performance of the reconstruction algorithm was evaluated using leave-one-out cross-validation in three defect types with varying severity as well as severe defects with discontinuities. The two-sided reconstruction method was compared to a one-sided methodology. Although, reconstruction errors increased with defect size and this increase was most pronounced for pelvic discontinuities, the two-sided reconstruction method was able to reconstruct the native anatomy with higher accuracy than the one-sided reconstruction method. These findings can improve the preoperative planning and custom implant design in patients with large pelvic defects, both with and without discontinuities.

SUBMITTER: Meynen A 

PROVIDER: S-EPMC7643466 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Accurate reconstructions of pelvic defects and discontinuities using statistical shape models.

Meynen Alexander A   Matthews Harold H   Nauwelaers Nele N   Claes Peter P   Mulier Michiel M   Scheys Lennart L  

Computer methods in biomechanics and biomedical engineering 20200703 13


Treatment of large acetabular defects and discontinuities remains challenging and relies on the accurate restoration of the native anatomy of the patient. This study introduces and validates a statistical shape model for the reconstruction of acetabular discontinuities with severe bone loss through a two-sided Markov Chain Monte Carlo reconstruction method. The performance of the reconstruction algorithm was evaluated using leave-one-out cross-validation in three defect types with varying severi  ...[more]

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