### 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: AP30_{estimate}, AP90_{estimate}, IE30_{estimate}, IE90_{estimate}, VV0_{estimate}, VV30_{estimate.} 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 (η^{2}) and the corresponding p-value (*p estimate model. The η^{2} ranged from 0.568 (IE90_{estimate}) to 0.995 (IE30_{estimate}). 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 language | English |
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Pages (from-to) | 1-8 |

Number of pages | 8 |

Journal | Computer Methods in Biomechanics and Biomedical Engineering |

DOIs | |

Publication status | Accepted/In press - Apr 28 2016 |

### Fingerprint

### 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

*Computer Methods in Biomechanics and Biomedical Engineering*, 1-8. https://doi.org/10.1080/10255842.2016.1176152

**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.

Research output: Contribution to journal › Article

*Computer Methods in Biomechanics and Biomedical Engineering*, pp. 1-8. https://doi.org/10.1080/10255842.2016.1176152

}

TY - JOUR

T1 - Predictive mathematical modeling of knee static laxity after ACL reconstruction

T2 - in vivo analysis

AU - Signorelli, C.

AU - Bonanzinga, T.

AU - Grassi, A.

AU - Lopomo, N.

AU - Zaffagnini, S.

AU - Marcacci, M.

PY - 2016/4/28

Y1 - 2016/4/28

N2 - 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.

AB - 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.

KW - ACL reconstruction

KW - modeling

KW - Static laxity

KW - surgery outcome

KW - surgical variables

UR - http://www.scopus.com/inward/record.url?scp=84966649972&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84966649972&partnerID=8YFLogxK

U2 - 10.1080/10255842.2016.1176152

DO - 10.1080/10255842.2016.1176152

M3 - Article

SP - 1

EP - 8

JO - Computer Methods in Biomechanics and Biomedical Engineering

JF - Computer Methods in Biomechanics and Biomedical Engineering

SN - 1025-5842

ER -