Showing papers by "Jukka S. Jurvelin published in 2020"

Biomechanical Changes of Repair Tissue after Autologous Chondrocyte Implantation at Long-Term Follow-Up.

Abstract: Objective. This study aims to describe biomechanical maturation process of repair tissue after cartilage repair with autologous chondrocyte implantation (ACI) at long-term follow-up. Design. After ACI, 40 patients underwent altogether 60 arthroscopic biomechanical measurements of the repair tissue at various time points during an up to 11-year follow-up period. Of these patients, 30 patients had full-thickness cartilage lesions and 10 had an osteochondritis dissecans (OCD) defect. The mean lesion area was 6.5 cm2 (SD 3.2). A relative indentation stiffness value for each individually measured lesion was calculated as a ratio of repair tissue and surrounding cartilage indentation value to enable interindividual comparison. Results. Repair tissue stiffness improved during approximately 5 years after surgery. Most of the increase in stiffness occurred during the first 2 years. The curvilinear correlation between relative stiffness values and the follow-up time was 0.31 (95% CI 0.07-0.52), P = 0.017. The interindividual variation of the stiffness was high. Lesion properties or demographic factors showed no significant correlation to biomechanical outcome. The overall postoperative average relative stiffness was 0.75 (SD 0.47). Conclusions. Our clinical study describes a biomechanical maturation process of cartilage repair that may continue even longer than expected. A substantial increase in tissue stiffness proceeds for the first two years postoperatively. Minor progression proceeds for even longer. In some repairs, the biomechanical result was equal to native cartilage, suggesting hyaline-type repair. The variation in biomechanical results suggests substantial inconsistency in the structural outcome following ACI.

Clinical Contrast-Enhanced Computed Tomography With Semi-Automatic Segmentation Provides Feasible Input for Computational Models of the Knee Joint.

Abstract: Computational models can provide information on joint function and risk of tissue failure related to progression of osteoarthritis. Currently, the joint geometries utilized in modelling are primarily obtained via manual segmentation, which is time-consuming and hence impractical for direct clinical application. The aim of this study was to evaluate the applicability of a previously developed semiautomatic method for segmenting tibial and femoral cartilage to serve as input geometry for finite element (FE) models. Knee joints from seven volunteers were first imaged using a clinical CT with contrast enhancement and then segmented with semiautomatic and manual methods. In both segmentations, knee joint models with fibril-reinforced poroviscoelastic properties were generated and the mechanical responses of articular cartilage were computed during conditions of physiologically relevant loading. The mean differences in the absolute values of maximum principal stress, maximum principal strain, and fibril strain between the models generated from semiautomatic and manual segmentations were 0.05). This semiautomatic method speeded up the segmentation process by over 90% and there were only negligible differences in the results provided by the models utilizing either manual or semiautomatic segmentations. Thus, the presented CT imaging based segmentation method represents a novel tool for application in FE modelling in the clinic when a physician needs to evaluate knee joint function.

A novel semi-automatic hip morphology assessment tool is more accurate than manual radiographic evaluations

Abstract: Radiological and pathological characteristics of hip osteoarthritis (OA) is joint-space loss due to degradation of articular cartilage. However, patients with early-stage OA do not yet show any rad...