Identification of potential compensatory muscle strategies in a breast cancer survivor population: A combined computational and experimental approach.

Background: Biomechanical models are often used to estimate the muscular demands of various activities. However, specific muscle dysfunctions typical of unique clinical populations are rarely considered. Due to iatrogenic tissue damage, pectoralis major capability is markedly reduced in breast cancer population survivors, which could influence arm internal and external rotation muscular strategies.

Methods: Accordingly, an optimization-based muscle force prediction model was systematically modified to emulate breast cancer population survivors through adjusting pectoralis capability and enforcing an empirical muscular co-activation relationship. Model permutations were evaluated through comparisons between predicted muscle forces and empirically measured muscle activations in survivors.

Findings: Similarities between empirical data and model outputs were influenced by muscle type, hand force, pectoralis major capability and co-activation constraints. Differences in magnitude were lower when the co-activation constraint was enforced (-18.4% [31.9]) than unenforced (-23.5% [27.6]) (p<0.0001).

Interpretation: This research demonstrates that muscle dysfunction in breast cancer population survivors can be reflected through including a capability constraint for pectoralis major. Further refinement of the co-activation constraint for survivors could improve its generalizability across this population and activities. Improving biomechanical models to more accurately represent clinical populations can provide novel information that can help in the development of optimal treatment programs for breast cancer population survivors.