IDEAS - Support frontier research

Title: Evaluation of Osteoarthritis Progression in a Patient-Specific Manner using Magnetic Resonance Imaging and Computational Modeling - OAPROGRESS

Principal investigator: Associate Professor Rami Korhonen

Funded by: European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 281180

Project description:

Osteoarthritis (OA) is one of the most prevalent disorders of the musculoskeletal system. In Europe, over 100 million people have arthritis. During OA, articular cartilage degenerates and its structure and mechanical properties change. Abnormal loading of diarthrodial joints has typically been implicated harmful for cartilage, but monitoring or predicting the progression of OA has not been possible. Magnetic resonance imaging (MRI) is a potential tool for the imaging of joint tissues, estimation of cartilage structure and diagnostics of OA, whereas joint loading and estimation of stresses/strains within joint tissues necessitates computational modeling. However, none of the earlier models have been able to evaluate the effect of loading on the progression of OA. It would be a major breakthrough if one could develop a technique where, based on MRI and computational modeling, prediction and evaluation of OA progression of a patient under a certain loading condition would be possible.

The main aims of the project are divided in applied and basic studies; 1) to combine MRI with computational modeling for the estimation of stresses and possible failure points within human knee joints, and 2) to develop second generation adaptive models of articular cartilage for the prediction of altered tissue structure and composition during OA progression. For the model validation, cartilage structure, composition and biomechanical properties as well as cell responses in situ are characterized. At the end of the project these main aims will be merged 3) to estimate the effect of loading on cartilage degeneration (altered composition and structure) during the progression of OA in a patient-specific manner.

Currently there are limited tools to restrain the increase in amount of OA patients in Europe. Combining MRI information of joint geometries as well as structural inclusions of cartilage with the computational modeling, we develop a tool to evaluate the effect of different interventions on stress concentration areas in human joints. By combining this tool with an adaptive model that can estimate the effect of loading on cartilage composition and structure, we hope to be able to predict changes in cartilage properties during OA progression in a patient-specific manner several years ahead. This would help in decision making of clinical treatments and interventions (conservative or surgical) for the prevention or further progression of OA.

Video 1: Workflow of the project.

Some of the latest results (see PubMed for a full list):

Cell and tissue mechanics in osteoarthritis

Arokoski ME, Tiitu V, Jurvelin JS, Korhonen RK, Fick JM. (2015). Topographical investigation of changes in depth-wise proteoglycan distribution in rabbit femoral articular cartilage at 4 weeks after transection of the anterior cruciate ligament. Journal of Orthopaedic Research 33(9):1278-86. doi: 10.1002/jor.22906.

Figure 1: (a) A New Zealand White Rabbit femoral condyle representing the medial and lateral compartments and located on the left and right hand side of the image. (b-e) Safarin-O stained sections obtained from the femoral condyles in the (b) lateral and (d) medial compartments of the contralateral knee and in the (c) lateral and (e) medial compartments of the anterior cruciate ligament transected (ACLT) knees. Images show a significant decrease in the proteoglycan content in the ACLT knees, especially in the medial compartment. Scale bars = 1 mm.

Mäkelä JTA, Rezaeian ZS, Mikkonen S, Madden R, Han S-K, Jurvelin JS, Herzog W, Korhonen RK (2014). Site-Dependent Changes in Structure and Function of Lapine Articular Cartilage 4 Weeks After Anterior Cruciate Ligament Transection. Osteoarthritis and Cartilage 22:869-878.

Huttu MRJ, Puhakka J, Mäkelä JTA, Takakubo Y, Tiitu V, Saarakkala S, Konttinen YT, Kiviranta I, Korhonen RK (2014). Cell-tissue interactions in osteoarthritic human hip joint articular cartilage. Connective Tissue Research 55:282-291.

Figure 2: Reprensetative images for determination of proteoglycan content, collagen content and collagen orientation angle. Image obtained from Huttu et al. Connect Tissue Res, 2014; 55(4): 282-291. Click figure for original publication.

Fick JM, Huttu MRJ, Lammi MJ, Korhonen RK (2014). In vitro glycation of articular cartilage alters the biomechanical response of chondrocytes in a depth-dependent manner. Osteoarthritis and Cartilage 22(10):1410-8.

Korhonen RK, Julkunen P, Li LP, van Donkelaar CC (2013). Computational Models of Articular Cartilage. Computational and Mathematical Methods in Medicine 2013:254507.

Knee joint modeling

Venäläinen MS, Mononen ME, Salo J, Räsänen LP, Jurvelin JS, Töyräs J, Virén T, Korhonen RK. (2016). Quantitative Evaluation of the Mechanical Risks Caused by Focal Cartilage Defects in the Knee. Scientific Reports, 6:37538. doi: 10.1038/srep37538.

Halonen KS, Mononen ME, Jurvelin JS, Töyräs J, Salo J, Korhonen RK (2014). Deformation of articular cartilage during static loading of a knee joint - experimental and finite element analysis. Journal of Biomechanics 47:2467-2474.

Mononen ME, Jurvelin JS and Korhonen RK (2013). Effects of Radial Tears and Partial Meniscectomy of Lateral Meniscus on the Knee Joint Mechanics During the Stance Phase of the Gait Cycle - A 3D finite element study. Journal of Orthopaedic Research 31:1208-1217.

Figure 3: Effects of radial tears and partial meniscectomy on the stress distributions (left column), average tibial surface stresses (middle column) and stresses in the node at the end of radial tear (right column) within the knee joint during the gait cycle loading. Stress distributions represent the time during the loading response (20% of the stance).

Multiscale modeling

Räsänen LP, Mononen ME, Lammentausta E, Nieminen MT, Jurvelin JS, Korhonen RK. (2016). Three dimensional patient-specific collagen architecture modulates cartilage responses in the knee joint during gait. Computer Methods in Biomechanics and Biomedical Engineering., 19(11):1225-40. doi: 10.1080/10255842.2015.1124269.

Tanska P, Mononen ME, Korhonen RK (2015). A Multiscale Finite Element Model for Investigating Cartilage and Chondrocyte Mechanics in Human Knee Joint During Walking – The Effect of Medial Meniscectomy on Chondrocyte and Matrix Responses. Journal of Biomechanics, 48(8):1397-406. doi: 10.1016/j.jbiomech.2015.02.043.

Tanska P, Mononen ME, Korhonen RK (2014). Multiscale modeling of articular chondrocytes in a knee joint. In Proceedings of the 7th World Congress of Biomechanics, Boston, USA, 6-11 July. (invited presentation)

Figure 4: Schematic presentation of multiscale modelling approach. Magnetic resonance imaging is used for capturing patient-specific knee joint geometry and structure. Captured geometry can be meshed with e.g. finite-element method and knee joint movement (based either on translation-rotation or force-moment data) can be applied into the finite-element model. Then, cartilage mechanics can be studied on joint, tissue or cell scale.

Modeling of osteoarthritis progression

Mononen ME, Tanska P, Isaksson H, Korhonen RK (2016). A Novel Method to Simulate the Progression of Collagen Degeneration of Cartilage in the Knee: Data from the Osteoarthritis Initiative. Scientific Reports, 6:21415. doi: 10.1038/srep21415.

Figure 5: Simulation of osteoarthritis progression. The degeneration algorithm, based on accumulated tensile stresses in cartilage, prediced severe cartilage degeneration in overweight subject and no degeneration in normal weight subject. The result was consistent with 4-year follow up data obtained from the Osteoarthritis Initiative database. See the original research article for more details.
Video 2: Workflow for simulating the progression of subject specific knee osteoarthritis.
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