Nocturnal Changes in Knee Cartilage Thickness in Young Healthy Adults

Magnetic resonance imaging (MRI) allows one to analyze cartilage physiology in vivo. Cartilage deforms during loading, but little is known about its recovery after deformation. Here we study `nocturnal' changes in knee cartilage thickness and whether postexercise deformation differs between morning and evening. Axial magnetic resonance (MR) images were acquired in the right knees of 17 healthy volunteers (age 23.5 +/- 3.0 years) after a normal day, and then after 30 deep knee bends. Coronal images were additionally acquired in 8 of these volunteers after a normal day and then after 2 min of static loading of the leg with 150% body weight. The volunteers then remained unloaded overnight and the same protocol was repeated in the morning. A significant increase (p < 0.01) in cartilage thickness was observed between evening (preexercise) and morning (preexercise): +2.4% in the patella, +8.4% in the medial tibia and +6.2% in the lateral tibia. Deformation in the morning (-6.8/-4.6/-5.1%) was generally greater than that in the evening (-5.4/-3.2/-3.7%), but this difference did not reach statistical significance. No significant difference in the nocturnal thickness increase (or postexercise deformation) was observed between men and women. We conclude that knee cartilage (thickness) recovers overnight by approximately 2-8%, independent of sex. Given the lack of `predeformation' after nocturnal periods of unloading, morning postexercise deformation of the cartilage may have a greater magnitude than evening postexercise deformation. Copyright (C) 2012 S. Karger AG, Base

Präzision MRT-basierter Gelenkflächen- und Knorpeldickenanalysen im Kniegelenk bei Verwendung einer schnellen Wasseranregungs-Sequenz und eines semiautomatischen Segmentierungs-Algorithmus

The aim of this study was to analyse the precision of three-dimensional joint surface and cartilage thickness measurements in the knee, using a fast, high-resolution water-excitation sequence and a semiautomated segmentation algorithm. The knee joint of 8 healthy volunteers, aged 22 to 29 years, were examined at a resolution of 1.5 mm x 0.31 mm x 0.31 mm, with four sagittal data sets being acquired after repositioning the joint. After semiautomated segmentation with a B-spline Snake algorithm and 3D reconstruction of the patellar, femoral and tibial cartilages, the joint surface areas (triangulation), cartilage volume, and mean and maximum thickness (Euclidean distance transformation) were analysed, independently of the orientation of the sections. The precision (CV%) for the surface areas was 2.1 to 6.6%. The mean cartilage thickness and cartilage volume showed coefficients of 1.9 to 3.5% (except for the femoral condyles), the value for the medial femoral condyle being 9.1%, and for the lateral condyle 6.5%. For maximum thickness, coefficients of between 2.6 and 5.9% were found. In the present study we investigate for the first time the precision of MRI-based joint surface area measurements in the knee, and of cartilage thickness analyses in the femur. Using a selective water-excitation sequence, the acquisition time can be reduced by more than 50%. The poorer precision in the femoral condyles can be attributed to partial Volume effects that occur at the edges of the joint surfaces with a sagittal image protocol. Since MRI is non-invasive, it is highly suitable for examination of healthy subjects (generation of individual finite element models, analysis of functional adaptation to mechanical stimulation, measurement of cartilage deformation in vivo) and as a diagnostic tool for follow-up, indication for therapy, and objective evaluation of new therapeutic agents in osteoarthritis

Stress distribution in the trochlear notch

n 16 cadaver humeroulnar joints, the distribution of subchondral mineralisation was assessed by CT osteoabsorptiometry and the position and size of the contact areas by polyether casting under loads of 10 N to 1280 N. Ulnas with separate olecranon and coronoid cartilaginous surfaces showed matching bicentric patterns of mineralisation. Under small loads there were separate contact areas on the olecranon and coronoid surfaces; these areas merged centrally as the load increased. They occupied as little as 9% of the total articular surface at 10 N and up to 73% at 1280 N. Ulnas with continuous cartilaginous surfaces also had density patterns with two maxima but those were less prominent, and in these specimens the separate contact areas merged at lower loads. The findings indicate a physiological incongruity of the articular surfaces which may serve to optimise the distribution of stress

In vivo measures of cartilage deformation: patterns in healthy and osteoarthritic female knees using 3T MR imaging

ObjectiveTo explore and to compare the magnitude and spatial pattern of in vivo femorotibial cartilage deformation in healthy and in osteoarthritic (OA) knees.MethodsOne knee each in 30 women (age: 55 ± 6 years; BMI: 28 ± 2.4 kg/m(2); 11 healthy and 19 with radiographic femorotibial OA) was examined at 3Tesla using a coronal fat-suppressed gradient echo SPGR sequence. Regional and subregional femorotibial cartilage thickness was determined under unloaded and loaded conditions, with 50% body weight being applied to the knee in 20° knee flexion during imaging.ResultsCartilage became significantly (p &lt; 0.05) thinner during loading in the medial tibia (-2.7%), the weight-bearing medial femur (-4.1%) and in the lateral tibia (-1.8%), but not in the lateral femur (+0.1%). The magnitude of deformation in the medial tibia and femur tended to be greater in osteoarthritic knees than in healthy knees. The subregional pattern of cartilage deformation was similar for the different stages of radiographic OA.ConclusionOsteoarthritic cartilage tended to display greater deformation upon loading than healthy cartilage, suggesting that knee OA affects the mechanical properties of cartilage. The pattern of in vivo deformation indicated that cartilage loss in OA progression is mechanically driven

The Out-of-Equilibrium Time-Dependent Gutzwiller Approximation

We review the recently proposed extension of the Gutzwiller approximation, M. Schiro' and M. Fabrizio, Phys. Rev. Lett. 105, 076401 (2010), designed to describe the out-of-equilibrium time-evolution of a Gutzwiller-type variational wave function for correlated electrons. The method, which is strictly variational in the limit of infinite lattice-coordination, is quite general and flexible, and it is applicable to generic non-equilibrium conditions, even far beyond the linear response regime. As an application, we discuss the quench dynamics of a single-band Hubbard model at half-filling, where the method predicts a dynamical phase transition above a critical quench that resembles the sharp crossover observed by time-dependent dynamical mean field theory. We next show that one can actually define in some cases a multi-configurational wave function combination of a whole set of mutually orthogonal Gutzwiller wave functions. The Hamiltonian projected in that subspace can be exactly evaluated and is equivalent to a model of auxiliary spins coupled to non-interacting electrons, closely related to the slave-spin theories for correlated electron models. The Gutzwiller approximation turns out to be nothing but the mean-field approximation applied to that spin-fermion model, which displays, for any number of bands and integer fillings, a spontaneous $Z_2$ symmetry breaking that can be identified as the Mott insulator-to-metal transition.Comment: 25 pages. Proceedings of the Hvar 2011 Workshop on 'New materials for thermoelectric applications: theory and experiment

Transmission Electron Study of Heteroepitaxial Growth in the BiSrCaCuO System

Films of Bi$\rm _2$Sr$\rm _2$CaCu$\rm _2$O$\rm _8$ and Bi$\rm _2$Sr$\rm _2$CuO$\rm _6$ have been grown using Atomic-Layer-by-Layer Molecular Beam Epitaxy (ALL-MBE) on lattice-matched substrates. These materials have been combined with layers of closely-related metastable compounds like Bi$\rm _2$Sr$\rm _2$Ca$\rm _7$Cu$\rm _8$O$\rm _{20}$ (2278) and rare-earth-doped compounds like Bi$\rm _2$Sr$\rm _2$Dy$\rm _x$Ca$\rm _{1-x}$Cu$\rm _2$O$\rm _8$ (Dy:2212) to form heterostructures with unique superconducting properties, including superconductor/insulator multilayers and tunnel junctions. Transmission electron microscopy (TEM) has been used to study the morphology and microstructure of these heterostructures. These TEM studies shed light on the physical properties of the films, and give insight into the growth mode of highly anisotropic solids like Bi$\rm _2$Sr$\rm _2$CaCu$\rm _2$O$\rm _8$.Comment: 17 pages, submitted to J. Materials Research. Email to [email protected] if you want to receive copies of the figure

Derivation of an observer model adapted to irregular signals based on convolution channels.

Anthropomorphic model observers are mathe- matical algorithms which are applied to images with the ultimate goal of predicting human signal detection and classification accuracy across varieties of backgrounds, image acquisitions and display conditions. A limitation of current channelized model observers is their inability to handle irregularly-shaped signals, which are common in clinical images, without a high number of directional channels. Here, we derive a new linear model observer based on convolution channels which we refer to as the "Filtered Channel observer" (FCO), as an extension of the channelized Hotelling observer (CHO) and the nonprewhitening with an eye filter (NPWE) observer. In analogy to the CHO, this linear model observer can take the form of a single template with an external noise term. To compare with human observers, we tested signals with irregular and asymmetrical shapes spanning the size of lesions down to those of microcalfications in 4-AFC breast tomosynthesis detection tasks, with three different contrasts for each case. Whereas humans uniformly outperformed conventional CHOs, the FCO observer outperformed humans for every signal with only one exception. Additive internal noise in the models allowed us to degrade model performance and match human performance. We could not match all the human performances with a model with a single internal noise component for all signal shape, size and contrast conditions. This suggests that either the internal noise might vary across signals or that the model cannot entirely capture the human detection strategy. However, the FCO model offers an efficient way to apprehend human observer performance for a non-symmetric signal