TLEM 2.0 - a comprehensive musculoskeletal geometry dataset for subject-specific modeling of lower extremity

V Carbone; R Fluit; P Pellikaan; M M van der Krogt; D Janssen; M Damsgaard; L Vigneron; T Feilkas; H F J M Koopman; N Verdonschot

doi:10.1016/j.jbiomech.2014.12.034

TLEM 2.0 - a comprehensive musculoskeletal geometry dataset for subject-specific modeling of lower extremity

J Biomech. 2015 Mar 18;48(5):734-41. doi: 10.1016/j.jbiomech.2014.12.034. Epub 2015 Jan 8.

Authors

V Carbone¹, R Fluit², P Pellikaan², M M van der Krogt³, D Janssen⁴, M Damsgaard⁵, L Vigneron⁶, T Feilkas⁷, H F J M Koopman², N Verdonschot⁸

Affiliations

¹ Laboratory of Biomechanical Engineering, Faculty of Engineering Technology, MIRA Institute, University of Twente, Enschede, The Netherlands. Electronic address: v.carbone@utwente.nl.
² Laboratory of Biomechanical Engineering, Faculty of Engineering Technology, MIRA Institute, University of Twente, Enschede, The Netherlands.
³ Laboratory of Biomechanical Engineering, Faculty of Engineering Technology, MIRA Institute, University of Twente, Enschede, The Netherlands; Department of Rehabilitation Medicine, Research Institute MOVE, VU University Medical Center, Amsterdam, The Netherlands.
⁴ Orthopaedic Research Laboratory, Radboud University Medical Centre, Nijmegen, The Netherlands.
⁵ AnyBody Technology A/S, Aalborg, Denmark.
⁶ Materialise N.V., Leuven, Belgium.
⁷ Brainlab AG, Munich, Germany.
⁸ Laboratory of Biomechanical Engineering, Faculty of Engineering Technology, MIRA Institute, University of Twente, Enschede, The Netherlands; Orthopaedic Research Laboratory, Radboud University Medical Centre, Nijmegen, The Netherlands.

PMID: 25627871
DOI: 10.1016/j.jbiomech.2014.12.034

Abstract

When analyzing complex biomechanical problems such as predicting the effects of orthopedic surgery, subject-specific musculoskeletal models are essential to achieve reliable predictions. The aim of this paper is to present the Twente Lower Extremity Model 2.0, a new comprehensive dataset of the musculoskeletal geometry of the lower extremity, which is based on medical imaging data and dissection performed on the right lower extremity of a fresh male cadaver. Bone, muscle and subcutaneous fat (including skin) volumes were segmented from computed tomography and magnetic resonance images scans. Inertial parameters were estimated from the image-based segmented volumes. A complete cadaver dissection was performed, in which bony landmarks, attachments sites and lines-of-action of 55 muscle actuators and 12 ligaments, bony wrapping surfaces, and joint geometry were measured. The obtained musculoskeletal geometry dataset was finally implemented in the AnyBody Modeling System (AnyBody Technology A/S, Aalborg, Denmark), resulting in a model consisting of 12 segments, 11 joints and 21 degrees of freedom, and including 166 muscle-tendon elements for each leg. The new TLEM 2.0 dataset was purposely built to be easily combined with novel image-based scaling techniques, such as bone surface morphing, muscle volume registration and muscle-tendon path identification, in order to obtain subject-specific musculoskeletal models in a quick and accurate way. The complete dataset, including CT and MRI scans and segmented volume and surfaces, is made available at http://www.utwente.nl/ctw/bw/research/projects/TLEMsafe for the biomechanical community, in order to accelerate the development and adoption of subject-specific models on large scale. TLEM 2.0 is freely shared for non-commercial use only, under acceptance of the TLEMsafe Research License Agreement.

Keywords: Lower extremity; Medical Imaging; Musculoskeletal geometry; Subject-specific modeling.

MeSH terms

Aged, 80 and over
Datasets as Topic*
Humans
Joints / physiology
Ligaments / physiology
Lower Extremity / physiology*
Magnetic Resonance Imaging
Male
Models, Biological*
Muscle, Skeletal / physiology
Tendons / physiology
Tomography, X-Ray Computed