Automated analysis of rabbit knee calcified cartilage morphology using micro-computed tomography and deep learning

Structural dynamics of calcified cartilage (CC) are poorly understood. Conventionally, CC structure is analyzed using histological sections. Micro-computed tomography (µCT) allows for three-dimensional (3D) imaging of mineralized tissues; however, the segmentation between bone and mineralized cartilage is challenging. Here, we present state-of-the-art deep learning segmentation for µCT images to assess 3D CC morphology. The sample includes 16 knees from 12 New Zealand White rabbits dissected into osteochondral samples from six anatomical regions: lateral and medial femoral condyles, lateral and medial tibial plateaus, femoral groove, and patella (n = 96). The samples were imaged with µCT and processed for conventional histology. Manually segmented CC from the images was used to train segmentation models with different encoder–decoder architectures. The models with the greatest out-of-fold evaluation Dice score were selected. CC thickness was compared across 24 regions, co-registered between the imaging modalities using Pearson correlation and Bland–Altman analyses. Finally, the anatomical CC thickness variation was assessed via a Linear Mixed Model analysis. The best segmentation models yielded average Dice of 0.891 and 0.807 for histology and µCT segmentation, respectively. The correlation between the co-registered regions was strong (r = 0.897, bias = 21.9 µm, standard deviation = 21.5 µm). Finally, both methods could separate the CC thickness between the patella, femoral, and tibial regions (p < 0.001). As a conclusion, the proposed µCT analysis allows for ex vivo 3D assessment of CC morphology. We demonstrated the biomedical relevance of the method by quantifying CC thickness in different anatomical regions with a varying mean thickness. CC was thickest in the patella and thinnest in the tibial plateau. Our method is relatively straightforward to implement into standard µCT analysis pipelines, allowing the analysis of CC morphology. In future research, µCT imaging might be preferable to histology, especially when analyzing dynamic changes in cartilage mineralization. It could also provide further understanding of 3D morphological changes that may occur in mineralized cartilage, such as thickening of the subchondral plate in osteoarthritis and other joint diseases.     

Optical coherence tomography enables accurate measurement of equine cartilage thickness for determination of speed of sound

Background and purpose — Arthroscopic estimation of articular cartilage thickness is important for scoring of lesion severity, and measurement of cartilage speed of sound (SOS)—a sensitive index of changes in cartilage composition. We investigated the accuracy of optical coherence tomography (OCT) in measurements of cartilage thickness and determined SOS by combining OCT thickness and ultrasound (US) time-of-flight (TOF) measurements.

Material and methods — Cartilage thickness measurements from OCT and microscopy images of 94 equine osteochondral samples were compared. Then, SOS in cartilage was determined using simultaneous OCT thickness and US TOF measurements. SOS was then compared with the compositional, structural, and mechanical properties of cartilage.

Results — Measurements of non-calcified cartilage thickness using OCT and microscopy were significantly correlated (ρ = 0.92; p < 0.001). With calcified cartilage included, the correlation was ρ = 0.85 (p < 0.001). The mean cartilage SOS (1,636 m/s) was in agreement with the literature. However, SOS and the other properties of cartilage lacked any statistically significant correlation.

Interpretation — OCT can give an accurate measurement of articular cartilage thickness. Although SOS measurements lacked accuracy in thin equine cartilage, the concept of SOS measurement using OCT appears promising.     

New algorithm for simulation of proteoglycan loss and collagen degeneration in the knee joint: Data from the osteoarthritis initiative

Osteoarthritis is a harmful joint disease but prediction of disease progression is problematic. Currently, there is only one modeling framework which can be applied to predict the progression of knee osteoarthritis but it only considers degenerative changes in the collagen fibril network. Here, we have developed the framework further by considering all of the major tissue changes (proteoglycan content, fluid flow, and collagen fibril network) occurring in osteoarthritis. While excessive levels of tissue stresses controlled degeneration of the collagen fibril network, excessive levels of tissue strains controlled the decrease in proteoglycan content and the increase in permeability. We created four knee joint models with increasing degrees of complexity based on the depth‐wise composition. Models were tested for normal and abnormal, physiologically relevant, loading conditions in the knee. Finally, the predicted depth‐wise compositional changes from each model were compared against experimentally observed compositional changes in vitro. The model incorporating the typical depth‐wise composition of cartilage produced the best match with experimental observations. Consistent with earlier in vitro experiments, this model simulated the greatest proteoglycan depletion in the superficial and middle zones, while the collagen fibril degeneration was located mostly in the superficial zone. The presented algorithm can be used for predicting simultaneous collagen degeneration and proteoglycan loss during the development of knee osteoarthritis. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:1673–1683, 2018.

     

The 125I-labelled fibrinogen uptake test in elective hip surgery

The value of the 125I-labelled fibrinogen uptake test as a screening method for deep vein thrombosis was estimated in 49 patients (97 extremities) undergoing elective hip operations. The legs were monitored preoperatively, on the 1st, 2nd and 4th postoperative days. Contrast venography, as a reference method, was performed on the 5th postoperative day. The sensitivity was 73%, specificity 85%, positive predictive value 63%, negative predictive value 86% and correlation coefficient 55%. 78% of fibrinogen uptakes appeared within the first 24 hours, and 6% on the 4th postoperative day. Only 1 of 3 patients with a positive fibrinogen uptake test in the femoral region had roentgenologic evidence of deep vein thrombosis. According to these results the isotope-labelled fibrinogen uptake test can also be utilized as a screening method in elective hip surgery.     

Rapid X-Ray-Based 3-D Finite Element Modeling of Medial Knee Joint Cartilage Biomechanics During Walking

Finite element (FE) modeling is becoming an increasingly popular method for analyzing knee joint mechanics and biomechanical mechanisms leading to osteoarthritis (OA). The most common and widely available imaging method for knee OA diagnostics is planar X-ray imaging, while more sophisticated imaging methods, e.g., magnetic resonance imaging (MRI) and computed tomography (CT), are seldom used. Hence, the capability to produce accurate biomechanical knee joint models directly from X-ray imaging would bring FE modeling closer to clinical use. Here, we extend our atlas-based framework by generating FE knee models from X-ray images (N = 28). Based on measured anatomical landmarks from X-ray and MRI, knee joint templates were selected from the atlas library. The cartilage stresses and strains of the X-ray-based model were then compared with the MRI-based model during the stance phase of the gait. The biomechanical responses were statistically not different between MRI- vs. X-ray-based models when the template obtained from X-ray imaging was the same as the MRI template. However, if this was not the case, the peak values of biomechanical responses were statistically different between X-ray and MRI models. The developed X-ray-based framework may pave the way for a clinically feasible approach for knee joint FE modeling.