Meniscal pathologies are among the most common injuries of the femorotibial joint in both human and equine patients. Pathological forces and ensuing injuries of the cranial horn of the equine medial meniscus are considered analogous to those observed in the human posterior medial horn. Biomechanical properties of human menisci are site- and depth- specific. However, the influence of equine meniscus topography and composition on its biomechanical properties is yet unknown. A better understanding of equine meniscus composition and biomechanics could advance not only veterinary therapies for meniscus degeneration or injuries, but also further substantiate the horse as suitable translational animal model for (human) meniscus tissue engineering. Therefore, the aim of this study was to investigate the composition and structure of the equine knee meniscus in a site- and age-specific manner and their relationship with potential site-specific biomechanical properties. The meniscus architecture was investigated histologically. Biomechanical testing included evaluation of the shore hardness (SH), stiffness and energy loss of the menisci. The SH was found to be subjected to both age and site-specific changes, with an overall higher SH of the tibial meniscus surface and increase in SH with age. Stiffness and energy loss showed neither site nor age related significant differences. The macroscopic and histologic similarities between equine and human menisci described in this study, support continued research in this field.

Reduced knee weight-bearing from prescription or sedentary lifestyles are associated with cartilage degradation; effects on the meniscus are unclear. Rodents exposed to spaceflight or hind limb unloading (HLU) represent unique opportunities to evaluate this question. This study evaluated arthritic changes in the medial knee compartment that bears the highest loads across the knee after actual and simulated spaceflight, and recovery with subsequent full weight-bearing. Cartilage and meniscal degradation in mice were measured via microCT, histology, and proteomics and/or biochemically after: (1) ~ 35 days on the International Space Station (ISS); (2) 13-days aboard the Space Shuttle Atlantis; or (3) 30 days of HLU, followed by a 49-day weight-bearing readaptation with/without exercise. Cartilage degradation post-ISS and HLU occurred at similar spatial locations, the tibial-femoral cartilage-cartilage contact point, with meniscal volume decline. Cartilage and meniscal glycosaminoglycan content were decreased in unloaded mice, with elevated catabolic enzymes (e.g., matrix metalloproteinases), and elevated oxidative stress and catabolic molecular pathway responses in menisci. After the 13-day Shuttle flight, meniscal degradation was observed. During readaptation, recovery of cartilage volume and thickness occurred with exercise. Reduced weight-bearing from either spaceflight or HLU induced an arthritic phenotype in cartilage and menisci, and exercise promoted recovery.

The outcome of a tibial plateau fracture (TPF) depends on the fracture reduction achieved and the extent of soft-tissue lesions, including lesions in the ligaments, cartilage, and menisci. Sub-optimal treatment can result in poor knee function and osteoarthritis. Preoperative planning is primarily based on conventional X-ray and computed tomography (CT), which are unsuitable for diagnosing soft-tissue lesions. Magnetic resonance imaging (MRI) is not routinely performed. To date, no literature exists that clearly states the indications for preoperative MRI. This systematic review aimed to determine the frequency of soft-tissue lesions in TPFs, the association between fracture type and soft-tissue lesions, and the types of cases for which MRI is indicated.

To review existing biomechanical and clinical evidence regarding postoperative weight-bearing and range of motion restrictions for patients following meniscal repair surgery.

Meniscal root tears cause menisci and their insertions to inadequately distribute loads and potentially leave underlying articular cartilage unprotected. Untreated meniscal root tears are becoming increasingly recognized to induce joint degradation; however, little information is known about anterior meniscal root tears and how they affect joint tissue.

Focal cartilage lesions can proceed to severe osteoarthritis or remain unaltered even for years. A method to identify high risk defects would be of utmost importance to guide clinical decision making and to identify the patients that are at the highest risk for the onset and progression of osteoarthritis. Based on cone beam computed tomography arthrography, we present a novel computational model for evaluating changes in local mechanical responses around cartilage defects. Our model, based on data obtained from a human knee in vivo, demonstrated that the most substantial alterations around the defect, as compared to the intact tissue, were observed in minimum principal (compressive) strains and shear strains. Both strain values experienced up to 3-fold increase, exceeding levels previously associated with chondrocyte apoptosis and failure of collagen crosslinks. Furthermore, defects at the central regions of medial tibial cartilage with direct cartilage-cartilage contact were the most vulnerable to loading. Also locations under the meniscus experienced substantially increased minimum principal strains. We suggest that during knee joint loading particularly minimum principal and shear strains are increased above tissue failure limits around cartilage defects which might lead to osteoarthritis. However, this increase in strains is highly location-specific on the joint surface.

Non-contact anterior cruciate ligament (ACL) rupture is mostly caused by a pivot shift mechanism including valgus collapse and internal tibial rotation. In female athletes, the incidence of ACL rupture has been reported to be significantly higher than in their male counterparts. However, to date, there have been limited reports and controversy regarding sex differences underlying injury mechanisms of ACL and severity of injury. In this study, we hypothesized that 1) in patients with non-contact ACL rupture, the incidence and severity of pivot shift injury, which are determined by injury pattern on MRI, would be significantly higher in females, and 2) anatomical factors associated with pivot shift injury would be significantly associated with female sex. A total of 148 primary ACL ruptures (145 patients) caused by non-contact injury mechanisms were included in this study. Among them, 41 knees (41 patients) were female and 107 knees (104 patients) were male. The status of the osseous lesions, lateral and medial tibial slope, depth of the medial tibial plateau, collateral ligaments, and menisci were assessed by MRI and compared between sexes. The severity of osseous lesions at the lateral tibial plateau, lateral femoral condyle, medial tibial plateau, and medial femoral condyle were comparable between sexes. There were no significant differences between sexes in the location of tibial contusions (p = 0.21), femoral contusions (p = 0.23), or meniscus tears (p = 0.189). Lateral tibial slope was found to be significantly larger in females (8.95° vs. 6.82°; p<0.0001; odds ratio = 1.464), and medial tibial depth was significantly shallower in females (1.80mm vs. 2.41mm; p<0.0001; odds ratio = 0.145). In conclusion, females showed greater lateral tibial slope and shallower medial tibial depth compared to males, however it did not affect the sex differences in injury pattern.

The aim of the present study is to build a software implementation of a previous study and to diagnose discoid lateral menisci on knee joint radiograph images. A total of 160 images from normal individuals and patients who were diagnosed with discoid lateral menisci were included. Our software implementation includes two parts: preprocessing and measurement. In the first phase, the whole radiograph image was analyzed to obtain basic information about the patient. Machine learning was used to segment the knee joint from the original radiograph image. Image enhancement and denoising tools were used to strengthen the image and remove noise. In the second phase, edge detection was used to quantify important features in the image. A specific algorithm was designed to build a model of the knee joint and measure the parameters. Of the test images, 99.65% were segmented correctly. Furthermore, 97.5% of the tested images were segmented correctly and their parameters were measured successfully. There was no significant difference between manual and automatic measurements in the discoid (P=0.28) and control groups (P=0.15). The mean and standard deviations of the ratio of lateral joint space distance to the height of the lateral tibial spine were compared with the results of manual measurement. The software performed well on raw radiographs, showing a satisfying success rate and robustness. Thus, it is possible to diagnose discoid lateral menisci on radiographs with the help of radiograph-image-analyzing software (BM3D, etc.) and artificial intelligence-related tools (YOLOv3). The results of this study can help build a joint database that contains data from patients and thus can play a role in the diagnosis of discoid lateral menisci and other knee joint diseases in the future.

Sesamoids bones are small intra-tendinous (or ligamentous) ossifications found near joints and are often variable between individuals. Related bones, lunulae, are found within the menisci of certain joints. Several studies have described sesamoids and lunulae in lizards and their close relatives (Squamata) as potentially useful characters in phylogenetic analysis, but their status in the extant outgroup to Squamata, tuatara (Sphenodon), remains unclear. Sphenodon is the only living rhynchocephalian, but museum specimens are valuable and difficult to replace. Here, we use non-destructive X-ray microtomography to investigate the distribution of sesamoids and lunulae in 19 Sphenodon specimens and trace the evolution of these bones in Lepidosauria (Rhynchocephalia + Squamata). We find adult Sphenodon to possess a sesamoid and lunula complement different from any known squamate, but also some variation within Sphenodon specimens. The penultimate phalangeal sesamoids and tibial lunula appear to mineralize prior to skeletal maturity, followed by mineralization of a sesamoid between metatarsal I and the astragalocalcaneum (MTI-AC), the palmar sesamoids, and tibiofemoral lunulae around attainment of skeletal maturity. The tibial patella, ulnar, and plantar sesamoids mineralize late in maturity or variably. Ancestral state reconstruction indicates that the ulnar patella and tibiofemoral lunulae are synapomophies of Squamata, and the palmar sesamoid, tibial patella, tibial lunula, and MTI-AC may be synapomorphies of Lepidosauria. J. Morphol. 278:62-72, 2017. ©© 2016 Wiley Periodicals,Inc.

Convolutional neural networks (CNNs) are the state-of-the-art for automated assessment of knee osteoarthritis (KOA) from medical image data. However, these methods lack interpretability, mainly focus on image texture, and cannot completely grasp the analyzed anatomies' shapes. In this study we assess the informative value of quantitative features derived from segmentations in order to assess their potential as an alternative or extension to CNN-based approaches regarding multiple aspects of KOA. Six anatomical structures around the knee (femoral and tibial bones, femoral and tibial cartilages, and both menisci) are segmented in 46,996 MRI scans. Based on these segmentations, quantitative features are computed, i.e., measurements such as cartilage volume, meniscal extrusion and tibial coverage, as well as geometric features based on a statistical shape encoding of the anatomies. The feature quality is assessed by investigating their association to the Kellgren-Lawrence grade (KLG), joint space narrowing (JSN), incident KOA, and total knee replacement (TKR). Using gold standard labels from the Osteoarthritis Initiative database the balanced accuracy (BA), the area under the Receiver Operating Characteristic curve (AUC), and weighted kappa statistics are evaluated. Features based on shape encodings of femur, tibia, and menisci plus the performed measurements showed most potential as KOA biomarkers. Differentiation between non-arthritic and severely arthritic knees yielded BAs of up to 99%, 84% were achieved for diagnosis of early KOA. Weighted kappa values of 0.73, 0.72, and 0.78 were achieved for classification of the grade of medial JSN, lateral JSN, and KLG, respectively. The AUC was 0.61 and 0.76 for prediction of incident KOA and TKR within one year, respectively. Quantitative features from automated segmentations provide novel biomarkers for KLG and JSN classification and show potential for incident KOA and TKR prediction. The validity of these features should be further evaluated, especially as extensions of CNN-based approaches. To foster such developments we make all segmentations publicly available together with this publication.

We provide a meta-analysis for clinicians and researchers regarding the psychometric properties of the WOMET as a patient-reported outcome measure (PROM) for patients with meniscal pathologies.

Meniscus tears are usually classified as degenerative or traumatic tears according to their pathogenesis. At present, traumatic meniscal tears are generally believed to have high healing potential. In recent years, multiple treatments have been described for traumatic meniscal tears, such as the inside-out technique, outside-in technique, all-inside technique, biological augmentation of meniscal repair, meniscectomy, and non-surgical treatment. However, the functional recovery of the knee joint and healing of the meniscus after treatment are quite different from the results reported in the literature, which requires more reliable evidence-based medical findings. This study will evaluate evidence from multiple types of research comparing different therapies for traumatic meniscal tears in adults.

The in vitro determination of realistic loads acting in knee ligaments, articular cartilage, menisci and their attachments during daily activities require the creation of physiological muscle forces, ground reaction force and unconstrained kinematics. However, no in vitro test setup is currently available that is able to simulate such physiological loads during squatting and jump landing exercises. Therefore, a novel knee joint simulator allowing such physiological loads in combination with realistic, rapid movements is presented. To gain realistic joint positions and muscle forces serving as input parameters for the simulator, a combined in vivo motion analysis and inverse dynamics (MAID) study was undertaken with 11 volunteers performing squatting and jump landing exercises. Subsequently, an in vitro study using nine human knee joint specimens was conducted to prove the functionality of the simulator. To do so, slow squatting without muscle force simulation representing quasi-static loading conditions and slow squatting and jump landing with physiological muscle force simulation were carried out. During all tests ground reaction force, tibiofemoral contact pressure, and tibial rotation characteristics were simultaneously recorded. The simulated muscle forces obtained were in good correlation (0.48 ≤ R ≤ 0.92) with those from the in vivo MAID study. The resulting vertical ground reaction force showed a correlation of R = 0.93. On the basis of the target parameters of ground reaction force, tibiofemoral contact pressure and tibial rotation, it could be concluded that the knee joint load was loaded physiologically. Therefore, this is the first in vitro knee joint simulator allowing squatting and jump landing exercises in combination with physiological muscle forces that finally result in realistic ground reaction forces and physiological joint loading conditions.

The objective of this study was to identify, on a symptomatic knee osteoarthritis (OA) cohort, the risk factors associated with the progression of the disease. More specifically, we investigated the correlation between knee cartilage volume loss from subregions over the span of 24 months by means of quantitative magnetic resonance imaging (qMRI) with demographic, clinical, radiological, and MRI structural changes. A cohort of 107 patients with knee OA selected from a large trial evaluating the effect of a bisphosphonate underwent x-rays and MRI of the knee at baseline and 24 months. Joint space width (JSW) and joint space narrowing (JSN) and cartilage volume loss over time in subregions of the tibial plateaus and femoral condyles were quantitated. Structural changes in the subchondral bone (hypersignal) and in the menisci (tear and extrusion) were also evaluated. The greatest cartilage volume loss was found in the medial compartment, and risk factors included female gender, JSW, meniscal lesions, and bone changes at baseline. Subregion analysis revealed that the greatest cartilage volume loss at 24 months was found in the central area of the medial tibial plateau (15%; p < 0.0001) and of the medial femoral condyle (12%; p < 0.0001). These findings were associated with the presence at baseline of meniscal extrusion, particularly severe meniscal extrusion, medial and severe meniscal tear, bone hypersignal, high body mass index (BMI), smaller JSW, increases in Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain and patient global scores over time, and greater JSN. Parameters predicting medial central femoral condyle cartilage volume loss at 24 months were lateral meniscal tear, SF-36 and BMI at baseline, and JSN. At the medial central tibial plateau, the parameters were severe meniscal extrusion, severe lateral meniscal tear, and bone hypersignal in the lateral compartment at baseline, and WOMAC pain change. Meniscal damage and bone changes are the features most closely associated with the greatest subregional cartilage volume loss. Interestingly, for the first time, JSN was strongly associated with cartilage loss in the central areas of plateaus and condyles. This study also further confirms the correlation between cartilage volume loss and JSN and symptomatic changes at 24 months.

Virtual representations of the knee joint can provide clinicians, scientists, and engineers the tools to explore mechanical functions of the knee and its tissue structures in health and disease. Modeling and simulation approaches such as finite element analysis also provide the possibility to understand the influence of surgical procedures and implants on joint stresses and tissue deformations. A large number of knee joint models are described in the biomechanics literature. However, freely accessible, customizable, and easy-to-use models are scarce. Availability of such models can accelerate clinical translation of simulations, where labor-intensive reproduction of model development steps can be avoided. Interested parties can immediately utilize readily available models for scientific discovery and clinical care. Motivated by this gap, this study aims to describe an open source and freely available finite element representation of the tibiofemoral joint, namely Open Knee, which includes the detailed anatomical representation of the joint's major tissue structures and their nonlinear mechanical properties and interactions. Three use cases illustrate customization potential of the model, its predictive capacity, and its scientific and clinical utility: prediction of joint movements during passive flexion, examining the role of meniscectomy on contact mechanics and joint movements, and understanding anterior cruciate ligament mechanics. A summary of scientific and clinically directed studies conducted by other investigators are also provided. The utilization of this open source model by groups other than its developers emphasizes the premise of model sharing as an accelerator of simulation-based medicine. Finally, the imminent need to develop next-generation knee models is noted. These are anticipated to incorporate individualized anatomy and tissue properties supported by specimen-specific joint mechanics data for evaluation, all acquired in vitro from varying age groups and pathological states.

Osteoarthritis (OA) induces inflammation and degeneration of all joint components including cartilage, joint capsule, bone and bone marrow, and ligaments. Particularly intraarticular ligaments, which connect the articulating bones such as the anterior cruciate ligament (ACL) and meniscotibial ligaments, fixing the fibrocartilaginous menisci to the tibial bone, are prone to the inflamed joint milieu in OA. However, the pathogenesis of ligament degeneration on the cellular level, most likely triggered by OA associated inflammation, remains poorly understood. Hence, this review sheds light into the intimate interrelation between ligament degeneration, synovitis, joint cartilage degradation, and dysbalanced subchondral bone remodeling. Various features of ligament degeneration accompanying joint cartilage degradation have been reported including chondroid metaplasia, cyst formation, heterotopic ossification, and mucoid and fatty degenerations. The entheses of ligaments, fixing ligaments to the subchondral bone, possibly influence the localization of subchondral bone lesions. The transforming growth factor (TGF)β/bone morphogenetic (BMP) pathway could present a link between degeneration of the osteochondral unit and ligaments with misrouted stem cell differentiation as one likely reason for ligament degeneration, but less studied pathways such as complement activation could also contribute to inflammation. Facilitation of OA progression by changed biomechanics of degenerated ligaments should be addressed in more detail in the future.