Prediction of magnetic resonance imaging-derived trunk muscle geometry with application to spine biomechanical modeling

BACKGROUND

Accurate geometry of the trunk musculature is essential for reliably estimating spinal loads in biomechanical models. Currently, many models employ straight muscle path assumptions that yield far less accurate tissue loads, particularly in extreme postures. Precise muscle moment-arms and physiological cross-sectional areas are important when incorporating curved muscle geometry in biomechanical models. The objective of this study was to develop a predictive model of moment arms and physiological cross-sectional areas of trunk musculature at multiple levels in the thoracic/lumbar spine as a function of anthropometric measures.

METHODS

Based on magnetic resonance imaging data from thirty subjects (10 male and 20 female) reported in a previous study, a polynomial regression analysis was conducted to estimate the muscle moment-arms and physiological cross-sectional areas of trunk muscles through thoracic/lumbar spine as a function of vertebral level, gender, age, height, and body mass.

FINDINGS

Gender, body mass, and height were the best predictors of muscle moment-arms and physiological cross-sectional areas. The predictability of muscle parameters tended to be higher for erector spinae than other muscles. Most muscles showed a curved muscle path along the thoracic/lumbar spine.

INTERPRETATION

The polynomial regression model of the muscle geometry in this study generally showed good predictability compared to previous reports. The predictive model in this study will be useful to develop personalized biomechanical models that incorporate curved trunk muscle geometries.

Influence of muscle length on the three-dimensional architecture and aponeurosis dimensions of rabbit calf muscles

The function of a muscle is highly dependent on its architecture, which is characterized by the length, pennation, and curvature of the fascicles, and the geometry of the aponeuroses. During in vivo function, muscles regularly undergo changes in length, thereby altering their architecture. During passive muscle lengthening, fascicle length (FL) generally increases and the angle of fascicle pennation (FP) and the fascicle curvature (FC) decrease, while the aponeuroses increase in length but decrease in width. Muscles are differently structured, making their change during muscle lengthening complex and multifaceted. To obtain comprehensive data on architectural changes in muscles during passive length, the present study determined the three-dimensional fascicle geometry of rabbit M. gastrocnemius medialis (GM), M. gastrocnemius lateralis (GL), and M. plantaris (PLA). For this purpose, the left and right legs of three rabbits were histologically fixed at targeted ankle joint angles of 95° (short muscle length [SML]) and 60° (long muscle length [LML]), respectively, and the fascicles were tracked by manual three-dimensional digitization. In a second set of experiments, the GM aponeurosis dimensions of ten legs from five rabbits were determined at varying muscle lengths via optical marker tracking. The GM consisted of a uni-pennated compartment, whereas the GL and PLA contained multiple compartments of differently pennated fascicles. In the LML compared to the SML, the GM, GL, and PLA had on average a 41%, 29%, and 41% increased fascicle length, and a 30%, 25%, and 33% decrease in fascicle pennation and a 32%, 11%, and 35% decrease in fascicle curvature, respectively. Architectural properties were also differentiated among the different compartments of the PLA and GL, allowing for a more detailed description of their fascicle structure and changes. It was shown that the compartments change differently with muscle length. It was also shown that for each degree of ankle joint angle reduction, the proximal GM aponeurosis length increased by 0.11%, the aponeurosis width decreased by 0.22%, and the area was decreased by 0.20%. The data provided improve our understanding of muscles and can be used to develop and validate muscle models.

Automated quantification of the anatomic accuracy of muscle paths and its application in an image-based subject-specific modeling workflow for adult spinal deformity

BACKGROUND

Musculoskeletal models (MSKM) can non-invasively evaluate the effect of altered muscle geometry and physiology on locomotor function. Nevertheless, this requires anatomically accurate muscle paths throughout functional ranges of motion. However, reference data to evaluate such muscle paths is rarely available, including in adult spinal deformity (ASD). Although this degenerative disorder alters muscle geometry and physiology, these parameters are not available to inform clinical decision-making as generic MSKM cannot account for these alterations, and reliable ASD-specific modeling workflows do not currently exist.

RESEARCH QUESTION

Can an efficient workflow be developed for evaluating and optimizing the anatomic accuracy of dynamic muscle paths in personalized MSKM and applied for reliable spinal motion simulations in ASD?

METHODS

A workflow was developed to automatically analyze anatomic muscle accuracy throughout predefined ranges of motion in terms of muscle-bone penetration, muscle action, moment arm magnitude, and discontinuities. Erector spinae, multifidus, and psoas muscles were semi-automatically segmented in magnetic resonance images of one healthy and two ASD subjects. Next, their muscle representation, insertion sites, and complexity were iteratively refined with the above workflow to generate subject-specific MSKM and compare them against state-of-the-art generic MSKM.

RESULTS

All muscles in the subject-specific MSKM were anatomically accurate, except for discontinuities in 3.81 % (psoas) and 0.37 % (multifidus) of moment arm curves across motions and subjects. In contrast, scaled generic MSKM were consistently associated with muscle-bone penetration, decreased moment arm magnitude, and opposite muscle actions.

SIGNIFICANCE

This novel workflow is the first to allow for an efficient evaluation of the anatomic accuracy of dynamic muscle paths. Its application in MSKM of ASD patients resulted in subject-specific muscle paths, with an anatomically correct muscle geometry, while preventing bone penetration during the representative range of motions. The workflow is promising to enable biomechanical analyses of ASD with an accuracy beyond that of scaled generic models.

Influence of muscle packing on the three-dimensional architecture of rabbit M. plantaris

In their physiological condition, muscles are surrounded by connective tissue, other muscles and bone. These tissues exert transverse forces that change the three-dimensional shape of the muscle compared to its isolated condition, in which all surrounding tissues are removed. A change in shape affects the architecture of a muscle and therefore its mechanical properties. The rabbit M. plantaris is a multi-pennate calf muscle consisting of two compartments. A smaller, bi-pennate inner muscle compartment is embedded in a larger, uni-pennate outer compartment (Böl et al., 2015). As part of the calf, the plantaris is tightly packed between other muscles. It is unclear how packing affects the shape and architecture of the plantaris. Therefore, we examined the isolated and packed plantaris of the contralateral legs of three rabbits to determine the influence of the surrounding muscles on its shape and architectural properties using photogrammetric reconstruction and manual digitization, respectively. In the packed condition, the plantaris showed a 27% increase in fascicle pennation and a 54% increase in fascicle curvature compared to the isolated condition. Fascicle length was not affected by muscle packing. The change in muscle architecture occurred mainly in the outer compartment of the plantaris. Furthermore, the isolated plantaris showed a more circular shape and a reduced width of its muscle belly. It can be concluded that the packed plantaris is flattened by the forces exerted by the surrounding muscles, causing a complex architectural change. The data provided improve our understanding of muscle packages in general and can be used to develop and validate realistic three-dimensional muscle models.