Biomechanics

Osteoporosis diagnostics

Osteoporosis is defined as low bone mass, and results in a markedly increased risk of skeletal fractures. Development of new drugs to reduce bone loss or increase bone mass is promising. However, it requires that the individuals at risk can be accurately identified. Our research aims at improving osteoporosis diagnosis and fracture risk assessment, by combining current radiological images with statistical modeling and computational simulations.
 

Figure: Schematic of the research idea to predict fracture risk. From left to right, a 2D radiological image (DXA) is acquired in a clinical setting. The 2D image is then converted to a full 3D description of the hip using a shape template and statistical modeling. 3D computer models are built and used to calculate the bone strength and determine the individual’s risk of fracture.

Hip pathologies in children

Osteoarthritis (OA) is one of the most common musculoskeletal disorders in adults, but several pathologies that increase the risk of OA appear already during growth. However, there are no well-defined thresholds to identify patients with deformities in their hip during growth. Our research aims to develop a method to detect hip abnormalities during growth. We believe that by combining information on the hip anatomy in 3D with computational modeling of the load on the cartilage and the overall mechanical competence of the bones, we can improve identification of hip developmental diseases and better identify those at long-term risk for OA. The model works as an atlas of normal hip anatomy in 3D as a function of age and sex and results in 3D subject-specific models of pelvis, femur, and the articular cartilage from one 2D X-ray image.
 

Figure: Schematic of the method to obtain 3D anatomy and load distribution of the hip joint from 2D X-ray images of children. The 2D X-ray image of a child's hip is reconstructed as a 3D model in a computer. This allows for further computer-based modeling of load distribution of the joint during movement.

Computer models of the hip bone can be used to accurately describe the mechanical behavior of the bone subjected to all kinds of loading scenarios. These models can be created based on clinical images and then be used to, for example, calculate the force required to fracture a hip. To ensure that the models are as accurate as possible their behaviors need to be carefully compared with experimental measurements.
Our research aims to confirm the most suitable way to describe the mechanical behavior of the hip bone computationally. To do this we perform experiments where we load bones until they break and measure how they deform on the surface using cameras. We continue to develop computer models that describe the experimental results.

Figure: Experimental setup used to record how bone deforms under load, and a computer model of the hip bone replicating the mechanical tests.

Bone is a composite material with a well-defined structure. Due to its unique structure, bone can deform and absorb energy and thereby protect the tissue from breaking. The most potent mechanisms are found at the microscale, where the microstructure efficiently prevents cracks from growing. These protective mechanisms are impaired with age and diseases, such as osteoporosis, which makes the bone tissue more likely to fracture. Our research aims to understand how the fracture resistance of bone is affected by age or disease and to identify what features are key for maintaining good loadbearing ability. To do this, we use computational fracture models to understand how microstructure affects crack growth. We have developed a framework for simulating crack propagation in bone tissue, using computer-based damage models to study local damage mechanisms.

Figure: (A) Schematic illustration of the microstructure in compact bone. (B) Experimental setup. A metal bar is pressed down on the center of a bone sample forming a bridge across two metal pillars. A camera records the bone deformation and crack propagation. (C-D) The cracks in the bone are studied as an effect of porosity in computer models.

The aim of our research is to understand the biomechanical behavior of tendons and how these mechanical properties change over time based on the loading the tissue is exposed to. We use both experimental methods and computer simulations. We have developed a 3D tendon computer model which enables us to investigate different tendon properties, e.g. tendon geometry, heterogeneous structure and time dependent mechanical behavior, through computer simulations. The computer model is validated with high-resolution imaging and mechanical data obtained from our experimental investigations of the tendon tissue. We do these studies both in small animal models and on human tissue and patient images.
 

Figure: Experimental data from small animal studies on healthy and ruptured rat Achilles tendon are used for identifying tendon properties and validating our computer models of the healing process. Normal tendons are compared to those who have been injected with botox to reduce the loading. Mechanical, structural and compositional properties are measured and implemented into the computational models. 

Our aim is to unravel the relationship between mechanical stimuli and tendon structure. To do this, we study how each structural length scale of the tissue is affected, as well as the load transfer between them. We also study how the tendon adapts to mechanical stimuli. We use small animal models, primarily the rat. Rat tendons are exposed to varies degree of loading and unloading, and high-resolution synchrotron-based techniques are combined with conventional methods (microscopy and mechanical testing), to study how the tissue changes.

Figure: Experiments are performed to study the tendon response to load on several length scales. (A) Schematic representation of the Achilles tendon hierarchical structure, from the whole organ down to the molecule. (B) Three levels of in vivo loading are studied, where normal tendons are compared to tendons that are unloaded by botox injection, or by botox in combination with a metallic boot. (C) At the tissue scale, tendon structure is determined by imaging with 3D phase contrast tomography. (D) At the material scale, collagen is studied using small angle X-ray scattering.

Our research aims at understanding how the mechanical properties of cartilage change as osteoarthritis progresses, using computer simulation models and experiments. This is combined with research about understanding how cartilage change in response to altered mechanical loading, such as overloading caused by overweight or joint injury. Computer models with patient-specific motion data are used to estimate the progression of osteoarthritis in the knee joint, and to compare those predictions to clinical data over time. Additionally, our research investigates novel techniques for characterizing samples of cartilage and meniscus to discover signs of osteoarthritis development. We work with 3D imaging from X-ray and Neutron facilities (such as MAX-IV and ESS in Lund) to image tissue samples from cartilage and meniscus. This allows us to measure cellular features, fiber structure or motion of water under mechanical compression, as well as how these features change with osteoarthritis. 

Figure: Studies of cartilage degeneration during disease progression. We use motion analysis data in combination with musculoskeletal models to determine the loading of the knee. This data is implemented in computer models. The load then predicts how the tissue changes over time. The computer predictions of tissue degeneration are compared to patient follow-up data.