ERC BioMechTools

Biomechanical Diagnostic, Pre-Planning and Outcome Tools to improve Musculoskeletal Surgery

Within the BioMechTools programme we will develop diagnostic and evaluation tools to quantify the degenerative status of orthopaedic patients. Our focus lies on the lower extremities. This project will open new research fields related to biomechanical patient assessment and modelling of musculoskeletal pathologies.

Project Description

Project Description

The aetiology of many musculoskeletal diseases is related to biomechanical factors. However, the tools used by clinicians and researchers to assess the biomechanical condition of patients are often crude and subjective, leading to non-optimal patient analyses and care. For example, clinicians usually base their diagnosis on their own, subjective, interpretation of static imaging data like MRI-images and CT-scans. Yet, it is much more powerful to visualize the pathological tissue in a dynamic manner, i.e. a tear in a meniscus is easier to see when the meniscus is moving than when it is imaged statically.

The Orthopaedic Research Laboratory, in collaboration with the Department of Biomechanical Engineering (University of Twente), has been very successful in delivering imaging modalities and in generating patient specific musculoskeletal and finite element models. These types of models can be used to analyse the pathology in detail and to assess the biomechanical consequences of various surgical scenarios. See, for example, our research line ‘Musculoskeletal Biomechanics‘ and the ‘TLEMsafe‘ project.

With the BioMechTools project we aim to develop MRI and Ultrasound tools to quantify tissue strains under dynamic circumstances. Innovations related to imaging, sensor technology and biomechanical modelling will be utilized to generate versatile, accurate and objective methods to quantify the (pathological) musculoskeletal condition of the lower extremity of patients in a unique manner. These advanced diagnostic, pre-planning and outcome tools will provide clinicians and researchers with detailed biomechanical analysis about abnormal tissue deformations, pathological loading of the joints, abnormal stresses in the hard and soft tissues, and aberrant joint kinematics.

Our research will be done in collaboration with the BioMedical NMR group of the Technical University of Eindhoven and the Radiology department of the Academic Medical Centre Amsterdam for the dynamic MRI imaging and with the ‘Medical UltraSound Imaging Center‘ of the Radboudumc for the ultrasound techniques.

Our key objectives are:

  • develop and validate image based 3-D volumetric elastographic diagnostic methods that can quantify normal and pathological conditions of tissues under dynamic loading and which can be linked to biomechanical modelling tools
  • create an ultrasound-based system to assess internal joint kinematics which can be used as a diagnostic tool for clinicians and researchers and which is a validation tool for biomechanical modelling
  • generate and validate an ambulant functional (force and kinematic) diagnostic system which is easy to use and which can be used to provide input data for biomechanical models
  • create and validate a new modelling approach that integrates muscle-models with finite element models at a highly personalized level
  • generate biomechanical models which have personalized mechanical properties of the hard and soft tissues
  • demonstrate the applicability of the personalized diagnostic and pre-planning platform by application to healthy individuals and to patients

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Principle Investigator:
Nico Verdonschot, Prof. Dr. Ir.
André Sprengers, Ph.D.

Finite Element and Musculoskeletal Modelling

Hamid Naghibi-Beidokhti, Ph.D.
Marco Marra, Ph.D.

Quantification of Deformations using Dynamic MRI Techniques

TU/e partner:
TU/e partner:
AMC partner:
BioMedical NMR group
Radiology: Novel MRI techniques
Klaas Nicolay, Prof. Dr.
Gustav Strijkers, Dr. Ir.
A.J. Nederveen, Dr. Ir.
Valentina Mazzoli, Ph.D.

Quantification of Deformations using Ultrasound Techniques

MUSIC partner:
Medical UltraSound Imaging Center
Chris de Korte, Prof. Dr.
Kaj Gijsbertse, Ph.D.

The Ambulant Gait Analysis System and
the Ultrasound-based Kinematic Analysis System

Utwente partner:
Utwente partner:
Department of Biomechanical Engineering
Biomedical Signals And Systems
Bart Koopman, Prof. Dr. Ir.
Peter H. Veltink, Prof. Dr. Ir.
Kenan Niu, Ph.D.
Victor Sluiter, B.Eng.

ERC short-list

Awarded to:
Funded by:
Call details:
Prof. Dr. Ir. Nico Verdonschot
The European Research Council (ERC-Advanced Grant)
ERC-2012-ADG LS7
60 months (from May 2013)

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see PubMed


2019 April 16th

Marra, Marco;
Personalized Musculoskeletal Modeling of the Knee Joint.

2018 December 20th

Gijsbertse, Kaj;
Functional Ultrasound Imaging of the Lower Extremity

2018 November 19th

Naghibi Beidokhti, Hamid;
Personalized Finite Element Models of the Knee Joint: a Platform for Optimal Orthopedic Surgery Pre-Planning.

2018 February 15th

Niu, Kenan;
Ultrasound based Skeletal Motion Capture : the development and validation of a Non-Invasive Knee Joint Motion Tracking Method.

2017 December 6th

Mazzoli, Valentina;
Functional MRI of the Lower Extremities.

List of articles

Three-Dimensional Ultrasound Strain Imaging of Skeletal Muscles.

Gijsbertse K, Sprengers AM, Nillesen MM, Hansen HH, Lopata RG, Verdonschot N, de Korte CL.
Phys Med Biol. 2017 Jan 21;62(2):596-611
doi: 10.1088/1361-6560/aa5077
Epub 2016 Dec 29

A novel diffusion-tensor MRI approach for skeletal muscle fascicle length measurements.

Oudeman J, Mazzoli V, Marra MA, Nicolay K, Maas M, Verdonschot N, Sprengers AM, Nederveen AJ, Strijkers GJ, Froeling M.
Physiol Rep. 2016 Dec; 4(24). pii: e13012.
doi: 10.14814/phy2.13012
PMID: 28003562 Free PMC Article

Assessment of passive muscle elongation using Diffusion Tensor MRI: Correlation between fiber length and diffusion coefficients.

Mazzoli V, Oudeman J, Nicolay K, Maas M, Verdonschot N, Sprengers AM, Nederveen AJ, Froeling M, Strijkers GJ.
NMR Biomed. 2016 Dec; 29(12):1813-1824
doi: 10.1002/nbm.3661
PMID: 27862471

A comparison between dynamic implicit and explicit finite element simulations of the native knee joint.

Naghibi Beidokhti H, Janssen D, Khoshgoftar M, Sprengers A, Perdahcioglu ES, Van den Boogaard T, Verdonschot N.
Med Eng Phys. 2016 Oct; 38(10):1123-30
doi: 10.1016/j.medengphy.2016.06.001
PMID: 27349493

Water and fat separation in real-time MRI of joint movement with phase-sensitive bSSFP.

Mazzoli V, Nederveen AJ, Oudeman J, Sprengers A, Nicolay K, Strijkers GJ, Verdonschot N.
Magn Reson Med. 2016 Jul 15
doi: 10.1002/mrm.26341
PMID: 27417271

A subject-specific musculoskeletal modeling framework to predict in vivo mechanics of total knee arthroplasty.

Marra MA, Vanheule V, Fluit R, Koopman BH, Rasmussen J, Verdonschot N, Andersen MS.
J Biomech Eng. 2015 Feb 1;137(2):020904
doi: 10.1115/1.4029258
PMID: 25429519

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