Table 1

Advantages and limitations of the various investigational methods

Data-collection methodExamplesAdvantagesLimitationsApplications in ACL research
In vivoObservational: questionnaires, video, interviewsDirect observation or description of injury mechanism
  • Cannot determine internal structure stresses/strains

Description of inciting event (contact or non-contact, type of sporting activity), gross position of knee, trunk, lower extremity during injury
  • Questionnaire/interview: subjective and dependent on athletes ability to recall event

  • Video: limited by quality of video, camera angles available and observer’s ability to describe event

Clinical: arthroscopic, imaging, physical exam
  • Identify lesions associated with injury, strain gauges on internal joint structures, analyse anatomical restraints—functional-dynamic imaging such as MRI or roentgen stereogrammetric analysis techniques offer enhanced ability to visualise internal structures during dynamic weight-bearing activities

  • Do not directly analyse injury mechanism

  • Strain gauges placed on ACL during arthroscopy provide information about ACL strains during external loads

  • Accuracy, precision, reliability of data acquisition continuous to improve

  • Postinjury pathology and associated biomechanical effects may not be reliable indicators of actual injury mechanisms

  • Bone bruise locations may provide evidence for injury mechanisms

  • Arthroscopic: not ethical for healthy subjects, may affect proprioception or cause joint impingement, expensive

  • Posterior tibial slope calculated from images may be associated with ACL injury

  • Imaging: possible radiation exposure, expensive

  • Lachman’s, pivot shift, knee arthrometer data provide evidence of biomechanical effects of ACL deficiency

  • Physical exam: often subjective and highly variable differences between subjects

  • Functional-dynamic images help identify osteokinematics and ACL changes that occur during weight-bearing tasks

Laboratory: motion analysis, electromyography
  • Mimic specific movements that occur during injury

  • Do not replicate actual injury; rather estimate total joint biomechanics during high-risk movements

  • Identify sex differences in landing/cutting mechanics that may be associated with ACL injury

  • Estimate both kinematics and net kinetics at joint during high-risk movements

  • Difficult to reproduce or even approximate the strains and stresses that occur in internal joint structures (ligaments, cartilage, bones)

  • Identify biomechanical/neuromuscular variables associated with ACL injury

  • Coupled biomechanical–epidemiological studies provide predictive tools about injury risk factors (allows for both correlation and prediction of musculoskeletal injury)

  • Unethical to try to produce injury in laboratory

In vitroRobotic, quasistatic, dynamic
  • Identify passive biomechanical characteristics of joint motions

  • Age of specimens (may differ significantly from the population of interest)

  • ACL strains and biomechanical parameters during different external loading parameters provide evidence of how ACL injuries may occur

  • Direct injury studies possible

  • Difficult to reproduce dynamic joint motions and neuromuscular contributions to motion during injury conditions

  • Cadaveric ACL injury may occur during anterior tibial shear, abduction, knee hyperextension and many combined loads

  • Quantify multiple degree of freedom kinematics of joints

  • Expensive and injury studies often require a large number of specimens to reproduce injury mechanisms

  • Biomechanical consequences of ACL deficiency

  • Measure ligament and joint articulation contact forces

  • Orientation of loading, rate of loading and age of specimen may have significant effects on musculoskeletal failure loads

In silicoPhenomenological, anatomical, rigid, finite element, quasistatic, dynamic, stochastic, inverse simulation, forward simulation
  • Estimate internal joint biomechanics

  • Due to complexity of joints, models are simplified

  • ACL injury simulations for various tasks

  • In vivo biomechanical data can be used as input for geometric models to analyse movements

  • Certain assumptions are necessary about material properties, boundary conditions and anatomy

  • Identification of possible strategies to lower ACL injury risk

  • Can be used to extend motion analysis data to relate ground reaction forces and kinematics to ligament, cartilage and bone forces

  • Models must be validated (ideally by in vivo and in vitro data) which can be difficult without adequate material property characteristics available for the population of interest

  • Extension of coupled biomechanical–epidemiological motion analysis data to relate ground reaction forces and external loading conditions to ACL strains

  • Can be used to simulate injury mechanisms

  • Not currently possible to validate high loading rate/injury simulations

  • Parametric/sensitivity studies possible

  • Relatively inexpensive if equipment is readily available

  • Accuracy, precision, reliability of data acquisition continuous to improve

  • ACL, anterior cruciate ligament.