The Effects of Surgical Parameters on Meniscal Mechanics Following Anterior Cruciate Ligament Reconstruction: An Exploratory In-Silico Study

The meniscus plays a vital role in knee biomechanics, contributing to shock absorption, joint stability, proprioception, and lubrication. Anterior cruciate ligament reconstruction (ACLR) aims to restore knee stability after anterior cruciate ligament (ACL) injury; however, 30–60% of patients experience concurrent or subsequent meniscal damage. Despite this, the influence of ACLR surgical parameters on meniscal biomechanics remains largely unexplored. This study investigates how four key ACLR surgical parameters—graft type, graft size, tunnel location, and pre-tensioning—affect meniscal contact forces and stress using a coupled neuromusculoskeletal-finite element (NMSKFE) modelling approach during simulated walking. NMSK-FE simulations were conducted in six participants to assess changes in meniscal-tibial contact forces and stress distributions under various ACLR configurations. While most surgical conditions restored meniscal mechanics to near-intact levels (normalized root mean square error (nRMSE) < 10%), substantial deviations were observed in certain cases, particularly in anteroposterior and mediolateral contact forces and maximum principal stress (nRMSE > 10%). Notably, posterior graft placement with zero pre-tensioning increased medial meniscus stress, potentially elevating the risk of degeneration or injury. These findings highlight the individualized nature of ACLR outcomes, influenced not only by surgical parameters but also by patient-specific factors such as knee morphology and gait patterns. This study underscores the need for pre-surgical assessments that integrate patient-specific biomechanics to optimize ACLR strategies, enhance meniscal preservation, and improve long-term knee health. By incorporating meniscal mechanics and dynamic gait analysis, this research advances personalized ACLR approaches, addressing a critical gap in the field. • Subject-specific joint geometry and control modulate post-ACLR meniscal mechanics. • ACLR parameter efficacy varied, underscoring the need for personalized protocols. • NMSK-FE modelling enables predictive, individualized ACLR surgical planning. • Posterior graft placement and low pre-tension elevated meniscal stress profiles.

Authors

Institutions

Publication Details

Journal
IRBM
Published
2026-01-07
DOI
https://doi.org/10.1016/j.irbm.2026.100929
Primary Topic
Knee injuries and reconstruction techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Effects of Surgical Parameters on Meniscal Mechanics Following Anterior Cruciate Ligament Reconstruction: An Exploratory In-Silico Study

Ayda Karimi Dastgerdi, Alireza Y Bavil, R. Korhonen, Christopher P. Carty et al.
IRBM
Knee injuries and reconstruction techniques
article

The Effects of Surgical Parameters on Meniscal Mechanics Following Anterior Cruciate Ligament Reconstruction: An Exploratory In-Silico Study

Ayda Karimi Dastgerdi, Alireza Y Bavil, R. Korhonen, Christopher P. Carty, David J. Saxby, Wayne Hall, Ivan Astori, Amir Esrafilian
article en

Abstract

The meniscus plays a vital role in knee biomechanics, contributing to shock absorption, joint stability, proprioception, and lubrication. Anterior cruciate ligament reconstruction (ACLR) aims to restore knee stability after anterior cruciate ligament (ACL) injury; however, 30–60% of patients experience concurrent or subsequent meniscal damage. Despite this, the influence of ACLR surgical parameters on meniscal biomechanics remains largely unexplored. This study investigates how four key ACLR surgical parameters—graft type, graft size, tunnel location, and pre-tensioning—affect meniscal contact forces and stress using a coupled neuromusculoskeletal-finite element (NMSKFE) modelling approach during simulated walking. NMSK-FE simulations were conducted in six participants to assess changes in meniscal-tibial contact forces and stress distributions under various ACLR configurations. While most surgical conditions restored meniscal mechanics to near-intact levels (normalized root mean square error (nRMSE) < 10%), substantial deviations were observed in certain cases, particularly in anteroposterior and mediolateral contact forces and maximum principal stress (nRMSE > 10%). Notably, posterior graft placement with zero pre-tensioning increased medial meniscus stress, potentially elevating the risk of degeneration or injury. These findings highlight the individualized nature of ACLR outcomes, influenced not only by surgical parameters but also by patient-specific factors such as knee morphology and gait patterns. This study underscores the need for pre-surgical assessments that integrate patient-specific biomechanics to optimize ACLR strategies, enhance meniscal preservation, and improve long-term knee health. By incorporating meniscal mechanics and dynamic gait analysis, this research advances personalized ACLR approaches, addressing a critical gap in the field. • Subject-specific joint geometry and control modulate post-ACLR meniscal mechanics. • ACLR parameter efficacy varied, underscoring the need for personalized protocols. • NMSK-FE modelling enables predictive, individualized ACLR surgical planning. • Posterior graft placement and low pre-tension elevated meniscal stress profiles.

IRBMVol. 47(2)
Griffith University (AU), University of Eastern Finland (FI), Children’s Health Queensland Hospital and Health Service (AU)
Good health and well-being
Openalex Percentile: Top 97%
Knee injuries and reconstruction techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.