Predictive mathematical modeling of knee static laxity after ACL reconstruction

in vivo analysis

C. Signorelli, T. Bonanzinga, A. Grassi, N. Lopomo, S. Zaffagnini, M. Marcacci

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Previous studies did not take into consideration such large variety of surgery variables which describe the performed anterior cruciate ligament (ACL) reconstruction and the interaction among them in the definition of postoperative outcome. Seventeen patients who underwent navigated Single Bundle plus Lateral Plasty ACL reconstruction were enrolled in the study. Static laxity was evaluated as the value of anterior/posterior displacement at 30° and at 90° of flexion, internal/external rotation at 30° and 90° of knee flexion, varus/valgus test at 0° and 30° of flexion. The evaluated surgical variables were analyzed through a multivariate analysis defining the following models: AP30estimate, AP90estimate, IE30estimate, IE90estimate, VV0estimate, VV30estimate. Surgical variables has been defined as the angles between the tibial tunnel and the three planes, the lengths of the tunnel and the relationship between native footprints and tunnels. An analogous characterization was performed for the femoral side. Performance and significance of the defined models have been quantified by the correlation ratio (η2) and the corresponding p-value (*p estimate model. The η2 ranged from 0.568 (IE90estimate) to 0.995 (IE30estimate). The orientation of the tibial tunnel resulted to be the most important surgical variable for the performed laxity estimation. Mathematical models for postoperative knee laxity is a useful tool to evaluate the effects of different surgical variables on the postoperative outcome.

Original languageEnglish
Pages (from-to)1-8
Number of pages8
JournalComputer Methods in Biomechanics and Biomedical Engineering
DOIs
Publication statusAccepted/In press - Apr 28 2016

Fingerprint

Ligaments
Tunnels
Surgery
Mathematical models

Keywords

  • ACL reconstruction
  • modeling
  • Static laxity
  • surgery outcome
  • surgical variables

ASJC Scopus subject areas

  • Bioengineering
  • Biomedical Engineering
  • Computer Science Applications
  • Human-Computer Interaction

Cite this

Predictive mathematical modeling of knee static laxity after ACL reconstruction : in vivo analysis. / Signorelli, C.; Bonanzinga, T.; Grassi, A.; Lopomo, N.; Zaffagnini, S.; Marcacci, M.

In: Computer Methods in Biomechanics and Biomedical Engineering, 28.04.2016, p. 1-8.

Research output: Contribution to journalArticle

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