Detecting Musculoskeletal Parameters by Magnetic Resonance Imaging for Biomechanical Models

Musculoskeletal biomechanical models are used to study mechanics of
musculoskeletal disorders and simulate surgical treatments [1]. To date,
biomechanical models are based on human cadaveric measurements. Bone surfaces
and muscle characteristics (e.g. muscle fiber length, muscle mass, pennation
angle) were obtained from these cadavers and from this anthropometrical data
biomechanical models were programmed. To personalize these musculoskeletal
biomechanical models scaling was introduced. For generic purpose this scaling
worked rather well. However for individual purpose these scaled models were
insufficient, for example to predict muscle activations [2]. This inaccuracy in
subject specific modelling is a major disadvantage to use these biomechanical
models in a clinical setting. Besides, these generic models are only tested on
healthy subjects; patients with musculoskeletal disorders are known to show
even larger deviations. Imaging techniques are expected to play an important
role for capturing individual musculoskeletal parameters for biomechanical
models [1].
Murphy et al (1986) [3] showed one of the first applications of MRI on skeletal
muscles. Their MRI scanner conducted low contrast pictures; nevertheless they
were able to distinguish different muscles. Modern MRI-scanners, 3 tesla or
higher, are able to produce pictures of the muscles with high contrast.
Moreover, nowadays MRI- protocols can detect musculoskeletal parameters, for
example muscle volume and fiber trajectories [4]. Froeling et al 2012 [5]
showed the visualisation of muscle fiber trajectories within a muscle by using
an advanced technique of MRI, Diffusion Tensor Imaging (DTI). This implies a
possibility for using this technique to determine Physiological Cross Sectional
Area (PCSA). The maximal force of a muscle is proportional to the PCSA.
Therefore, PCSA is an important determinant within biomechanical models.
Another possibility of in-vivo MRI is to determine insertion points of muscles
to the bones [6]. These insertion points have a large inter-individual
variation [7], for biomechanical models this is an important parameter to take
into account. Individual musculoskeletal parameters (e.g. PCSA and insertion
points of muscles) are necessary to obtain to make biomechanical models
subject-specific.

The main aim of this study is to estimate internal joint loading and muscle
activations during activities of daily living. Therefore, biomechanical models
are used that can predict these internal parameters non-invasively. However, to
make these biomechanical models accurate, subject specific data will be
necessary. For this reason musculoskeletal properties will be obtained by
magnetic resonance imaging (MRI).

Cross-sectional study, including a subset for reproducability.

The involved tests are minimally invasive. During the motion capture analysis
in the human movement laboratory, subjects will perform Daily activity tasks
(level walking, walking the stairs, sitting and rising from a chair). As safety
measure for walking the stairs we included handrails. Test subjects will be
guided by the investigator. Their is a possible risk for muscle soreness on the
day performing the maximal strength test, or the day(s) after.
Next a MRI scan will be performed. This requires lying down very still from a
subject for about two hours. The Radiology department will assist in preparing
the subject and explaining the protocol. All metal objects are removed from the
subject. The potential risks involved could be previously not mentioned
claustrophobia. If this ought to be an acute problem to the subject, then
subjects as well as the MRI-performing radiology-assistant are allowed to
withdraw from testing at all times. Otherwise we conclude there are no other
risks involved.