Analysis of muscle forces acting on the patellofemoral joint

1
Analysis of muscle forces acting on the
patellofemoral joint

• Rob Spiller, Markin-Flanagan Student
• Supervisor Dr. Janet Ronsky
• May 12, 2004.

2
Outline

• Motivation
• Specific Aims
• PCSA
• Calculation of PCSA
• Methods
• Results
• Discussion
• Conclusions
• Acknowledgements Questions

3
Motivation

• Patellofemoral pain syndrome (PFPS)
• umbrella term
• 3 major factors (Thomee et al., 1999)
• Malalignment
• Muscular imbalance
• Overactivity
• Lack of consensus regarding the cause and
  treatment of PFPS

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Motivation

• Examine joint contact characteristics
  non-invasively in subjects with PFPS
• before and after an 8 week muscle training regime
  
• using MRI
• project by Ms. Kim McLaughlin, MSc student
• Determine subject specific physiological
  cross-sectional area (PCSA) to quantify role of
  muscles in PF contact mechanics

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Specific Aims

• Literature study on calculating PCSA from MR
  images
• Evaluate the measurement variability
  (inter-person, intra-person, sensitivity) in MRI
  PCSA calculations
• Determine the optimal method to measure subject
  specific PCSA from MRI images

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PCSA

• PCSA the cross-section of the muscle that is
  perpendicular to all the fibres of the muscle
• Better representation of muscles than ACSA

PCSA V / l cos(?) where, V volume of
muscle l fibre length ? angle of
pennation (Narici, 1999)
PCSA in Pennate Muscle
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Calculation of PCSA

• PCSA can be determined in-vivo by
• ultrasonography (US)
• computerized tomography (CT)
• magnetic resolution imaging (MRI)
• Determining variables
• V volume of muscle
• l fibre length ?
• ? angle of pennation ?

From published values (e.g. Wickiewicz et al.
1983)
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Calculation of PCSA

• Imaging series
• GE MRI unit (3.0 Tesla)
• thirty-five 3 mm slices
• centre of the patella to bottom of tuberositas
  plate
• User identified the x-sectional area on each
  image
• MR image analysis software volume of
  muscles

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Methods

• Inter-person variability
• medial gastrocnemius (MG), lateral gastrocnemius
  (LG)
• three subjects from identical images
• Intra-person repeatability
• one subject determined volume of MG
• repeated for four trials
• Sensitivity of the PCSA calculation
• - V from inter-person variability
• - l , ? from published literature (Wickiewicz et
  al. 1983, Friederich et al.1990, Narici et al.
  1992)

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Results

• Table 1 - Inter-Person Variability in Finding
  Muscle Volume from MRI

Table 2 - Intra-Person Variability in Finding
Muscle Volume from MRI
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Discussion

• Inter-person variability
• Expect higher volume higher standard deviation
• Variability of LG is higher from poor muscle
  differentiation on MR images
• Intra-person variability
• One person increases the repeatability
• Ideally would have an automated algorithm

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Results

• Table 3 - Sensitivity of PCSA Calculation to
  Individual Variables

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Discussion

• Sensitivity analysis
• PCSA calculation is least sensitive to the
  pennation angle
• most sensitive to fiber length, but most
  consistent in published literature
• this is significant to determining PCSA from MRI

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Conclusions

• Operator interpretation of unclear muscle
  boundaries is a significant cause of variability
• Repeatability is increased by having one observer
  identify the muscles on the MR images
• PCSA calculation is more sensitive to muscle
  volume and fibre length than the pennation angle

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Future Directions

• MRI imaging sequence for muscle boundaries
• Subject specific EMG-force relationship
• Force partitioning technique to incorporate
  subject specific PCSA values
• Predict force sharing amongst the vasti muscles

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Acknowledgements

• Markin-Flanagan Undergraduate Student Research
  Program
• NSERC
• Calgary Health Region
• Dr. Janet Ronsky
• Dr. Karen Gordon
• Ms. Kim McLaughlin