A novel non-invasive method for measuring knee joint laxity in four dof: In vitro proof-of-concept and validation.

Knee joint laxity or instability is a common problem that may have detrimental consequences for patients. Unfortunately, assessment of knee joint laxity is limited by current methodologies resulting in suboptimal diagnostics and treatment. This paper presents a novel method for accurately measuring non-invasive knee joint laxity in four degrees-of-freedom (DOF). An arthrometer, combining a parallel manipulator and a six-axis force/moment sensor, was developed to be used in combination with a low-dose biplanar x-ray system and 3D image data to reconstruct tibiofemoral position and orientation of laxity measurements. As proof-of-concept, four cadaveric knees were tested in the device. Each cadaveric knee was mounted in the device at approximately 30° of flexion and twelve monoplanar anteroposterior, mediolateral and internal/external load cases were applied. Additionally, four biplanar load cases were applied, consisting of different combinations of anteroposterior and internal/external loads. The arthrometer was limited to four DOF to address the specific measurements. For validation purposes, the pose reconstructions of tibia and femur were compared with pose reconstructions of bone pin marker frames mounted on each bone. The measurements from the arthrometer in terms of translation and rotations displayed comparable values to what have previously been presented in the literature. Furthermore, the measurements revealed coupled motions in multiple planes, demonstrating the importance of multi DOF laxity measurements. The validation displayed an average mean difference for translations of 0.08 mm and an average limit of agreement between -1.64 mm and 1.80 mm. The average mean difference for rotations was 0.10° and the limit of agreement was between -0.85° and 1.05°. The presented method eliminates several limitations present in current methods and may prove a valuable tool for assessing knee joint laxity.

Multi-scale computational models of the airways to unravel the pathophysiological mechanisms in asthma and chronic obstructive pulmonary disease (AirPROM).

THE RESPIRATORY SYSTEM COMPRISES SEVERAL SCALES OF BIOLOGICAL COMPLEXITY: the genes, cells and tissues that work in concert to generate resultant function. Malfunctions of the structure or function of components at any spatial scale can result in diseases, to the detriment of gas exchange, right heart function and patient quality of life. Vast amounts of data emerge from studies across each of the biological scales; however, the question remains: how can we integrate and interpret these data in a meaningful way? Respiratory disease presents a huge health and economic burden, with the diseases asthma and chronic obstructive pulmonary disease (COPD) affecting over 500 million people worldwide. Current therapies are inadequate owing to our incomplete understanding of the disease pathophysiology and our lack of recognition of the enormous disease heterogeneity: we need to characterize this heterogeneity on a patient-specific basis to advance healthcare. In an effort to achieve this goal, the AirPROM consortium (Airway disease Predicting Outcomes through patient-specific computational Modelling) brings together a multi-disciplinary team and a wealth of clinical data. Together we are developing an integrated multi-scale model of the airways in order to unravel the complex pathophysiological mechanisms occurring in the diseases asthma and COPD.