Development of an architecturally comprehensive database of forearm flexors and extensors from a single cadaveric specimen

Intramuscular aponeuroses and fiber bundle morphology of the five bellies of flexor digitorum superficialis: A three-dimensional modeling study

Restoring balanced function of the five bellies of flexor digitorum superficialis (FDS) following injury requires knowledge of the muscle architecture and the arrangement of the contractile and connective tissue elements. No three-dimensional (3D) studies of FDS architecture were found in the literature. The purpose was to (1) digitize/model in 3D the contractile/connective tissue elements of FDS, (2) quantify/compare architectural parameters of the bellies and (3) assess functional implications. The fiber bundles (FBs)/aponeuroses of the bellies of FDS were dissected and digitized (MicroScribe® Digitizer) in 10 embalmed specimens. Data were used to construct 3D models of FDS to determine/compare the morphology of each digital belly and quantify architectural parameters to assess functional implications. FDS consists of five morphologically and architecturally distinct bellies, a proximal belly, and four digital bellies. FBs of each belly have unique attachment sites to one or more of the three aponeuroses (proximal/distal/median). The proximal belly is connected through the median aponeurosis to the bellies of the second and fifth digits. The third belly exhibited the longest mean FB length (72.84 ± 16.26 mm) and the proximal belly the shortest (30.49 ± 6.45 mm). The third belly also had the greatest mean physiological cross-sectional area, followed by proximal/second/fourth/fifth. Each belly was found to have distinct excursion and force-generating capabilities based on their 3D morphology and architectural parameters. Results of this study provide the basis for the development of in vivo ultrasound protocols to study activation patterns of FDS during functional activities in normal and pathologic states.

Comparison of Optimization Strategies for Musculoskeletal Modeling of the Wrist for Therapy Planning in Case of Total Wrist Arthroplasty

The human wrist joint is an elegant mechanism. The wrist allows the positioning and orienting of the hand to the forearm. The computational modeling of the human hand, especially of the wrist joint, can reveal important information about biomechanical mechanisms and provide the basis for its dysfunction and pathologies. For instance, this could be used for therapy planning in total wrist arthroplasty (TWA). In this study, different optimization methods and sensitivity analyses of anatomical parameters for musculoskeletal modeling were presented. Optimization includes finding the best available value of an objective function, including a variety of different types of objective functions. In the simplest case, optimization consists of maximizing or minimizing a function by systematically choosing input values from within an allowed set and computing the value of the function. Optimization techniques are used in many facets, such as the model building of joints or joint systems such as the wrist. The purpose of this study is to show the variability and influence of the included information for modeling, investigating the biomechanical function and load situation of the joint in representative scenarios. These possibilities to take them into account by an optimization and seem essential for the application of computational modeling to joint pathologies.

The Myokinetic Control Interface: How Many Magnets Can be Implanted in an Amputated Forearm? Evidence From a Simulated Environment

We recently introduced the concept of a new human-machine interface (the myokinetic control interface) to control hand prostheses. The interface tracks muscle contractions via permanent magnets implanted in the muscles and magnetic field sensors hosted in the prosthetic socket. Previously we showed the feasibility of localizing several magnets in non-realistic workspaces. Here, aided by a 3D CAD model of the forearm, we computed the localization accuracy simulated for three different below-elbow amputation levels, following general guidelines identified in early work. To this aim we first identified the number of magnets that could fit and be tracked in a proximal (T1), middle (T2) and distal (T3) representative amputation, starting from 18, 20 and 23 eligible muscles, respectively. Then we ran a localization algorithm to estimate the poses of the magnets based on the sensor readings. A sensor selection strategy (from an initial grid of 840 sensors) was also implemented to optimize the computational cost of the localization process. Results showed that the localizer was able to accurately track up to 11 (T1), 13 (T2) and 19 (T3) magnetic markers (MMs) with an array of 154, 205 and 260 sensors, respectively. Localization errors lower than 7% the trajectory travelled by the magnets during muscle contraction were always achieved. This work not only answers the question: "how many magnets could be implanted in a forearm and successfully tracked with a the myokinetic control approach?", but also provides interesting insights for a wide range of bioengineering applications exploiting magnetic tracking.

Diffusion-Tensor Imaging Versus Digitization in Reconstructing the Masseter Architecture

Accurate characterization of the craniomaxillofacial (CMF) skeleton using finite element (FE) modeling requires representation of complex geometries, heterogeneous material distributions, and physiological loading. Musculature in CMF FE models are often modeled with simple link elements that do not account for fiber bundles (FBs) and their differential activation. Magnetic resonance (MR) diffusion-tensor imaging (DTI) enables reconstruction of the three-dimensional (3D) FB arrangement within a muscle. However, 3D quantitative validation of DTI-generated FBs is limited. This study compares 3D FB arrangement in terms of pennation angle (PA) and fiber bundle length (FBL) generated through DTI in a human masseter to manual digitization. CT, MR-proton density, and MR-DTI images were acquired from a single cadaveric specimen. Bone and masseter surfaces were reconstructed from CT and MR-proton density images, respectively. PA and FBL were estimated from FBs reconstructed from MR-DTI images using a streamline tracking (STT) algorithm (n = 193) and FBs identified through manual digitization (n = 181) and compared using the Mann–Whitney test. DTI-derived PAs did not differ from the digitized data (p = 0.411), suggesting that MR-DTI can be used to simulate FB orientation and the directionality of transmitted forces. Conversely, a significant difference was observed in FBL (p < 0.01) which may have resulted due to the tractography stopping criterion leading to early tract termination and greater length variability. Overall, this study demonstrated that DTI can yield muscle FB orientation data suitable to representative directionality of physiologic muscle loading in patient-specific CMF FE modeling.

Architecture of the Suprahyoid Muscles: A Volumetric Musculoaponeurotic Analysis

PURPOSE

Suprahyoid muscles play a critical role in swallowing. The arrangement of the fiber bundles and aponeuroses has not been investigated volumetrically, even though muscle architecture is an important determinant of function. Thus, the purpose was to digitize, model in three dimensions, and quantify the architectural parameters of the suprahyoid muscles to determine and compare their relative functional capabilities.

METHOD

Fiber bundles and aponeuroses from 11 formalin-embalmed specimens were serially dissected and digitized in situ. Data were reconstructed in three dimensions using Autodesk Maya. Architectural parameters were quantified, and data were compared using independent samples t-tests and analyses of variance.

RESULTS

Based on architecture and attachment sites, suprahyoid muscles were divided into 3 groups: anteromedial, superolateral, and superoposterior. Architectural parameters differed significantly (p < .05) across muscles and across the 3 groups, suggesting differential roles in hyoid movement during swallowing. When activated simultaneously, anteromedial and superoposterior muscle groups could work together to elevate the hyoid.

CONCLUSIONS

The results suggest that the suprahyoid muscles can have individualized roles in hyoid excursion during swallowing. Muscle balance may be important for identifying and treating hyolaryngeal dysfunction in patients with dysphagia.