This is the developer site of the OpenKnee project. The development efforts are organized by [http://www.lerner.ccf.org/bme/erdemir/ Ahmet Erdemir] and [http://www.lerner.ccf.org/bme/cobi/ CoBi Core] of the Cleveland Clinic. This study branched from a current NIH funded study on multiscale modeling and simulation of the knee joint, [https://simtk.org/home/j2c J2C]. If you are a new member ([:InstructionsForProjectSite#Team:How do I become a member?]), please read the following documentation to familiarize yourself with operational details:

• InstructionsForProjectSite

• InstructionsForWiki

• InstructionsForSourceCodeRepository

For recent wiki activity, check RecentChanges.

TableOfContents

Goals

Roadmap

Releases relies on the following numbering scheme:

version.major.minor.revision

version

numbering based on goals of the roadmap

major

implementation of a new feaure

minor

improvement of a feature or a bug fix

revision

revision number of the subversion repository on which the release is based on

Version 1.0

• Imaging data; DICOM files
• Geometry; STEP or IGES files
• Mesh; text based input deck
• Literature based material properties
• Frictionless contact between tissue structures
• Loading and boundary conditions representative of passive flexion
• Output at desired time increments

Long Term

Release Notes

Specifications

Geometry

Source: https://simtk.org/websvn/wsvn/openknee/dat/geo/

Currently, the knee geometry relies on manual digitization generated from sagittal MR images. Volsuite was used for this purpose. This initial geometry set was generated by Craig Bennetts of CoBi Core at Cleveland Clinic. 3D spline curves were used to develop NURBS surfaces using the loft feature in the CAD package Rhinoceros. Due to poor visibility of the lateral collateral ligament in sagittal image sets, its geometry is an approximation. Geometries are provided in a coordinate system aligned with the first sagittal MR image:

• origin - top-left corner
• x-axis - pointing towards right (anterior to posterior)
• y-axis - pointing downwards (superior to inferior)
• z-axis - pointing inwards (medial to lateral)

Mesh

Source: https://simtk.org/websvn/wsvn/openknee/dat/msh/

Current discretization relies on a fully hexahedral mesh generated using TrueGrid software (XYZ Scientific). The mesh file is a text based file conforming mesh definition convention of Abaqus. Element sets were defined for:

• femur
• tibia
• femoral cartilage
• tibial cartilage
• medial meniscus
• lateral meniscus
• medial collateral ligament
• lateral collateral ligament
• anterior cruciate ligament
• posterior cruciate ligament

Interface nodes between bone and cartilage were merged to eliminate the need for tie constraint enforcement in the FE model. Surface sets, to facilitate modeling of interactions between tissues, include:

• -- ["aerdemir"] DateTime(2010-02-25T03:26:31Z) Scott, if surface sets are defined during meshing, it may be easier to model contact. Please fill in this list accordingly.

Other sets are:

• -- ["aerdemir"] DateTime(2010-02-25T03:26:31Z) Scott, do you think we should define other useful sets such as menisci boundaries for defining springs. Please fill in this list accordingly.

Material Properties

Bone

Rigid

Cartilage

Incompressible, isotropic Mooney-Rivlin: C1=4.1 MPa, C2=0.41 MPa, K=407 MPa [#Li07 Li (2007)] -- ["aerdemir"] DateTime(2010-02-25T03:26:31Z) Let's use properties of the articular cartilage of the knee.

Ligament

Incompressible, transversely isotropic Neo-Hookean: C1=1.44 MPa, C3=0.57 MPa, C4=48, C5=467.1 MPa, lambda=1.062, K=144 MPa [#Gardiner03 Gardiner (2003)]

Meniscus

Incompressible, isotropic Mooney-Rivlin: C1=2.0 MPa, C2=0.2 MPa, K=207 MPa - made to be approximately half as stiff as cartilage. -- ["aerdemir"] DateTime(2010-02-25T03:26:31Z) Let's erly on literature values.

Interactions

Ligaments are attached to bone via rigid interface definitions (interface nodes become part of rigid body).

Frictionless, sliding contact defined between tibial to femoral cartilage, cartilage to meniscus, ligament to bone, and ACL to PCL.

Loading & Boundary Conditions

Output

Solver

Non-linear system is solved using a standard BFGS quasi-Newton algorithm or full Newton method implemented by Steve Maas in FEBio. The linear system at each iteration is solved using Pardiso, a sparse matrix solver for shared memory architecture. http://www.pardiso-project.org/

Software

For finite element analysis [http://mrl.sci.utah.edu/software/febio FEBio], a freely accessible package, will be used. This software is a product of significant efforts by Jeff Weiss and his group from the [http://mrl.sci.utah.edu/ Musculoskeletal Research Laboratories] at the University of Utah. Current version used in this project is FEBio 1.2, which can be downloaded from their [http://mrl.sci.utah.edu/software/febio site].

Settings

Data

Data for model development efforts are courtesy of [http://www.lerner.ccf.org/bme/bogert/ van den Bogert Laboratory] at the Cleveland Clinic. The information was collected is part of doctoral work conducted by Bhushan Borotikar.

Specimen

Imaging

Source: https://simtk.org/websvn/wsvn/openknee/dat/mri/

The knee specimen was imaged at the Biomechanics laboratory of the Cleveland Clinic using a 1.0T (Tesla) extremity MRI scanner (Orthone, ONI Medical Systems Inc, Wilmington MA). The scanner has the capability to scan upper and lower extremities of up to 180mm diameter. A scanning protocol that gave a good contrast for articular cartilage and ligaments in the same scan were used [#Borotikar09 Borotikar (2009)]. The specifics of this protocol are detailed in following:

The knee was kept in full extension position. Imaging technique utilizes 3D spoiled gradient echo sequence with fat suppression, TR = 30, TE = 6.7, Flip Angle = 200, Field of View (FOV) = 150mm X 150mm, Slice Thickness = 1.5mm. Scans in three anatomical planes, axial, sagittal, and coronal, were conducted. Total scanning time was approximately 18 minutes. Selecting these specific sequence parameters produced images that highlighted articular cartilage such that it could be easily discriminated from surrounding bone and tissue. The protocols and the image set reflect partial data from the doctoral work of [#Borotikar09 Borotikar (2009)].

Mechanical Testing

Documentation

Developer's Guide

User's Guide

Simulations

Test Suite

Physiological

References

Anchor(Borotikar09) Borotikar, Bhushan, Subject specific computational models of the knee to predict anterior cruciate ligament injury, Doctoral Dissertation, Cleveland State University, December 2009.

Anchor(Gardiner03) Gardiner JC, Weiss JA. Subject-specific finite element analysis of the human medial collateral ligament during valgus knee loading. J. Orthop. Res. 2003 Nov;21(6):1098-1106.

Anchor(Li07) Li Z, Kim J, Davidson JS, Etheridge BS, Alonso JE, Eberhardt AW. Biomechanical response of the pubic symphysis in lateral pelvic impacts: a finite element study. J Biomech. 2007;40(12):2758-2766.