An MRI-based leg model used to simulate biomechanical phenomena during cuff algometry: a finite element study

Area of Science:

• Biomedical Engineering
• Pain Research
• Biomechanics

Background:

• Cuff pressure stimulation is used to evaluate deep-tissue pain sensitivity by activating nociceptors.
• Understanding how mechanical stress transfers from the cuff to deeper tissues is crucial for accurate pain assessment.

Purpose of the Study:

• To investigate the biomechanical stress and strain transfer from cuff pressure to deep tissues, including muscle and bone-surrounding layers.
• To determine the efficacy of cuff algometry in stimulating nociceptors in deep tissues, particularly those near bones.

Main Methods:

• Developed 3D finite element models of the lower leg, incorporating bone and three deep tissue layers, based on MRI data.
• Applied cuff pressure at varying intensities (mild to painful) and mapped skin indentation using MRI.
• Analyzed the transfer of biomechanical stresses and strains to different tissue depths under the cuff.

Main Results:

• Mean stress under the cuff near the tibia and fibula was significantly higher (4.6-16.4 times) than on the muscle surface at pain threshold and intense stimulation.
• Mean strains around the tibia and fibula were a substantial percentage (32.9-42.3%) of the mean strain on the muscle surface.
• Stress and strain transfer varied with stimulation intensity and anatomical location (tibia vs. fibula).

Conclusions:

• Cuff algometry demonstrates significant stress and strain transfer to deep tissues, including those near bones.
• Assuming nociceptor activation is strain-dependent, cuff algometry may be less effective at challenging nociceptors in tissues surrounding bones compared to superficial muscles.
• Further research is needed to optimize cuff algometry for deep-tissue pain assessment.