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      ArborSim: Articulated, branching, OpenSim routing for constructing models of multi-jointed appendages with complex muscle-tendon architecture

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          Abstract

          Computational models of musculoskeletal systems are essential tools for understanding how muscles, tendons, bones, and actuation signals generate motion. In particular, the OpenSim family of models has facilitated a wide range of studies on diverse human motions, clinical studies of gait, and even non-human locomotion. However, biological structures with many joints, such as fingers, necks, tails, and spines, have been a longstanding challenge to the OpenSim modeling community, especially because these structures comprise numerous bones and are frequently actuated by extrinsic muscles that span multiple joints—often more than three—and act through a complex network of branching tendons. Existing model building software, typically optimized for limb structures, makes it difficult to build OpenSim models that accurately reflect these intricacies. Here, we introduce ArborSim, customized software that efficiently creates musculoskeletal models of highly jointed structures and can build branched muscle-tendon architectures. We used ArborSim to construct toy models of articulated structures to determine which morphological features make a structure most sensitive to branching. By comparing the joint kinematics of models constructed with branched and parallel muscle-tendon units, we found that among various parameters—the number of tendon branches, the number of joints between branches, and the ratio of muscle fiber length to muscle tendon unit length—the number of tendon branches and the number of joints between branches are most sensitive to branching modeling method. Notably, the differences between these models showed no predictable pattern with increased complexity. As the proportion of muscle increased, the kinematic differences between branched and parallel models units also increased. Our findings suggest that stress and strain interactions between distal tendon branches and proximal tendon and muscle greatly affect the overall kinematics of a musculoskeletal system. By incorporating complex muscle-tendon branching into OpenSim models using ArborSim, we can gain deeper insight into the interactions between the axial and appendicular skeleton, model the evolution and function of diverse animal tails, and understand the mechanics of more complex motions and tasks.

          Author summary

          OpenSim models of musculoskeletal systems are valuable tools for understanding the mechanisms underlying biological movement. However, highly jointed structures, like necks and tails, have been difficult to model, likely due to the presence of numerous bones, and their complex network of branched muscle-tendon units that span many joints. We introduce ArborSim, a modeling tool that facilitates construction of branched muscle-tendon units. Our comparisons of equivalent branched and unbranched models suggest that the modeling approach greatly affects the model predictions, which thereby indicates the importance of accurately modeling branching in multi-jointed structures. With ArborSim, we provide a unified framework that not only streamlines the creation of the complex musculoskeletal models of these structures but also paves the way for more in-depth investigations into the biomechanical behavior of branched muscle-tendon networks. This encourages more detailed study of the material properties and mechanics of complex muscle-tendon branching networks and highly jointed structures.

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          Most cited references64

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          User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability.

          Active contour segmentation and its robust implementation using level set methods are well-established theoretical approaches that have been studied thoroughly in the image analysis literature. Despite the existence of these powerful segmentation methods, the needs of clinical research continue to be fulfilled, to a large extent, using slice-by-slice manual tracing. To bridge the gap between methodological advances and clinical routine, we developed an open source application called ITK-SNAP, which is intended to make level set segmentation easily accessible to a wide range of users, including those with little or no mathematical expertise. This paper describes the methods and software engineering philosophy behind this new tool and provides the results of validation experiments performed in the context of an ongoing child autism neuroimaging study. The validation establishes SNAP intrarater and interrater reliability and overlap error statistics for the caudate nucleus and finds that SNAP is a highly reliable and efficient alternative to manual tracing. Analogous results for lateral ventricle segmentation are provided.
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            3D Slicer as an image computing platform for the Quantitative Imaging Network.

            Quantitative analysis has tremendous but mostly unrealized potential in healthcare to support objective and accurate interpretation of the clinical imaging. In 2008, the National Cancer Institute began building the Quantitative Imaging Network (QIN) initiative with the goal of advancing quantitative imaging in the context of personalized therapy and evaluation of treatment response. Computerized analysis is an important component contributing to reproducibility and efficiency of the quantitative imaging techniques. The success of quantitative imaging is contingent on robust analysis methods and software tools to bring these methods from bench to bedside. 3D Slicer is a free open-source software application for medical image computing. As a clinical research tool, 3D Slicer is similar to a radiology workstation that supports versatile visualizations but also provides advanced functionality such as automated segmentation and registration for a variety of application domains. Unlike a typical radiology workstation, 3D Slicer is free and is not tied to specific hardware. As a programming platform, 3D Slicer facilitates translation and evaluation of the new quantitative methods by allowing the biomedical researcher to focus on the implementation of the algorithm and providing abstractions for the common tasks of data communication, visualization and user interface development. Compared to other tools that provide aspects of this functionality, 3D Slicer is fully open source and can be readily extended and redistributed. In addition, 3D Slicer is designed to facilitate the development of new functionality in the form of 3D Slicer extensions. In this paper, we present an overview of 3D Slicer as a platform for prototyping, development and evaluation of image analysis tools for clinical research applications. To illustrate the utility of the platform in the scope of QIN, we discuss several use cases of 3D Slicer by the existing QIN teams, and we elaborate on the future directions that can further facilitate development and validation of imaging biomarkers using 3D Slicer. Copyright © 2012 Elsevier Inc. All rights reserved.
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              OpenSim: open-source software to create and analyze dynamic simulations of movement.

              Dynamic simulations of movement allow one to study neuromuscular coordination, analyze athletic performance, and estimate internal loading of the musculoskeletal system. Simulations can also be used to identify the sources of pathological movement and establish a scientific basis for treatment planning. We have developed a freely available, open-source software system (OpenSim) that lets users develop models of musculoskeletal structures and create dynamic simulations of a wide variety of movements. We are using this system to simulate the dynamics of individuals with pathological gait and to explore the biomechanical effects of treatments. OpenSim provides a platform on which the biomechanics community can build a library of simulations that can be exchanged, tested, analyzed, and improved through a multi-institutional collaboration. Developing software that enables a concerted effort from many investigators poses technical and sociological challenges. Meeting those challenges will accelerate the discovery of principles that govern movement control and improve treatments for individuals with movement pathologies.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: MethodologyRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: SoftwareRole: Writing – review & editing
                Role: ResourcesRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: Project administrationRole: ResourcesRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS Comput Biol
                PLoS Comput Biol
                plos
                PLOS Computational Biology
                Public Library of Science (San Francisco, CA USA )
                1553-734X
                1553-7358
                July 2024
                5 July 2024
                : 20
                : 7
                : e1012243
                Affiliations
                [1 ] Robotics, University of Michigan, Ann Arbor, Michigan, United States of America
                [2 ] Computer Science, University of Michigan, Ann Arbor, Michigan, United States of America
                [3 ] Mechanical Engineering, University of Michigan, Ann Arbor, Michigan, United States of America
                [4 ] Ecology and Evolutionary Biology, Museum of Zoology, University of Michigan, Ann Arbor, Michigan, United States of America
                University of Colorado Boulder, UNITED STATES OF AMERICA
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0003-0867-4512
                Article
                PCOMPBIOL-D-24-00087
                10.1371/journal.pcbi.1012243
                11253963
                38968305
                c353372c-2f9b-42a9-b0d3-8994719a5915
                © 2024 Fu et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 15 January 2024
                : 10 June 2024
                Page count
                Figures: 9, Tables: 1, Pages: 25
                Funding
                The author(s) received no specific funding for this work.
                Categories
                Software
                Biology and Life Sciences
                Anatomy
                Biological Tissue
                Connective Tissue
                Tendons
                Medicine and Health Sciences
                Anatomy
                Biological Tissue
                Connective Tissue
                Tendons
                Biology and Life Sciences
                Anatomy
                Musculoskeletal System
                Skeleton
                Skeletal Joints
                Medicine and Health Sciences
                Anatomy
                Musculoskeletal System
                Skeleton
                Skeletal Joints
                Biology and Life Sciences
                Biomechanics
                Musculoskeletal Mechanics
                Biology and Life Sciences
                Physiology
                Muscle Physiology
                Musculoskeletal Mechanics
                Biology and Life Sciences
                Cell Biology
                Cellular Types
                Animal Cells
                Muscle Fibers
                Biology and Life Sciences
                Anatomy
                Musculoskeletal System
                Muscles
                Muscle Fibers
                Medicine and Health Sciences
                Anatomy
                Musculoskeletal System
                Muscles
                Muscle Fibers
                Biology and Life Sciences
                Anatomy
                Biological Tissue
                Connective Tissue
                Ligaments
                Medicine and Health Sciences
                Anatomy
                Biological Tissue
                Connective Tissue
                Ligaments
                Physical Sciences
                Physics
                Classical Mechanics
                Kinematics
                Biology and Life Sciences
                Anatomy
                Musculoskeletal System
                Medicine and Health Sciences
                Anatomy
                Musculoskeletal System
                Research and Analysis Methods
                Simulation and Modeling
                Custom metadata
                vor-update-to-uncorrected-proof
                2024-07-17
                The source code of ArborSim is freely and anonymously accessible on GitHub, under the permissive Apache License 2.0, at https://github.com/EMBiRLab/ArborSim. The GitHub repository is called “ArborSim.”

                Quantitative & Systems biology
                Quantitative & Systems biology

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