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A high failure rate is associated with fracture plates in proximal humerus fractures. The causes of failure remain unclear due to the complexity of the problem including the number and position of the screws, their length and orientation in the space. Finite element (FE) analysis has been used for the analysis of plating of proximal humeral fractures, but due to computational costs is unable to fully explore all potential screw combinations. Surrogate modelling is a viable solution, having the potential to significantly reduce the computational cost whilst requiring a moderate number of training sets. This study aimed to develop adaptive neural network (ANN)‐based surrogate models to predict the strain in the humeral bone as a result of changing the length of the screws. The ANN models were trained using data from FE simulations of a single humerus, and after defining the best training sample size, multiple and single‐output models were developed. The best performing ANN model was used to predict all the possible screw length configurations. The ANN predictions were compared with the FE results of unseen data, showing a good correlation (R2 = 0.99) and low levels of error (RMSE = 0.51%–1.83% strain). The ANN predictions of all possible screw length configurations showed that the screw that provided the medial support was the most influential on the predicted strain. Overall, the ANN‐based surrogate model accurately captured bone strains and has the potential to be used for more complex problems with a larger number of variables. [ABSTRACT FROM AUTHOR]

Irregularities in retinal shape have been shown to correlate with axial length, a major risk factor for retinal detachment. To further investigate this association, a comparison was performed of the swept-source optical coherence tomography (SS OCT) peripheral retinal shape of eyes that had either a posterior vitreous detachment (PVD) or vitrectomy for retinal detachment. The objective was to identify a biomarker that can be tested as a predictor for retinal detachment. Eyes with a PVD (N = 88), treated retinal detachment (N = 67), or retinal tear (N = 53) were recruited between July 2020 and January 2022 from hospital retinal clinics in South Australia. The mid-peripheral retina was imaged in four quadrants with SS OCT. The features explored were patient age, eye axial length, and retinal shape irregularity quantified in the frequency domain. A discriminant analysis classifier to identify retinal detachment eyes was trained with two-thirds and tested with one-third of the sample. Retinal detachment eyes had greater irregularity than PVD eyes. A classifier trained using shape features from the superior and temporal retina had a specificity of 84% and a sensitivity of 48%. Models incorporating axial length were less successful, suggesting peripheral retinal irregularity is a better biomarker for retinal detachment than axial length. Mid-peripheral retinal irregularity can identify eyes that have experienced a retinal detachment. [ABSTRACT FROM AUTHOR]

Biomechanical factors (e.g., joint loading) have a significant role in the progression of osteoarthritis (OA). However, some relationships between in vivo joint loading indices and tibial cartilage thickness are conflicting. This study investigated relationships between pre‐operative in vivo external knee joint moments, joint alignment and regional tibial cartilage thickness using micro‐CT in subjects with end‐stage knee OA. Tibial plateaus from 25 patients that underwent knee replacement for OA were micro‐CT scanned (17 µm/voxel). Prior to surgery, subjects underwent gait analysis to calculate external knee moments. The mechanical axis deviation (MAD) was obtained from pre‐operative radiographs. Cartilage thickness (Cart.Th) was analyzed from micro‐CT images, in anteromedial, anterolateral, posteromedial and posterolateral subregions of interest. Medial‐to‐lateral Cart.Th ratios were also explored. Relationships between Cart.Th and joint loading indices were examined using Pearson's correlations. Significant correlations were found between Cart.Th and joint loading indices, positive anteromedially with the first peak knee adduction moment (r = 0.55, p < 0.01) and external rotation moment (ERM; r = 0.52, p < 0.01), and negative with MAD (r = −0.76, p < 0.001). In the lateral regions, these correlations had opposite signs. The medial‐to‐lateral Cart.Th ratio correlated strongly with ERM (r = 0.63, p = 0.001) and MAD (r = −0.75, p < 0.001). Joint loading indices correlated with regional cartilage thickness values and their medial‐to‐lateral ratios in end‐stage knee OA subjects, with higher regional loads corresponding to thinner cartilage. These relationships have the opposite sign compared to the subchondral bone microarchitecture found in our previous study on the same specimens, which may suggest a complementary bone–cartilage interplay in response to loading. [ABSTRACT FROM AUTHOR]

This preliminary study quantified tibia cartilage thickness (Cart.Th), subchondral bone plate thickness (SBPl.Th) and subchondral trabecular bone (STB) microarchitecture in subjects with varus‐ or valgus‐ malaligned knees diagnosed with end‐stage knee osteoarthritis (OA) and compared them to controls (non‐OA). Tibial plateaus from 25 subjects with knee‐OA (undergoing knee arthroplasty) and 15 cadavers (controls) were micro‐CT scanned (17 µm/voxel). Joint alignment was classified radiographically for OA subjects (varus‐aligned n = 18, valgus‐aligned n = 7). Cart.Th, SBPl.Th, STB bone volume fraction (BV/TV) and their medial‐to‐lateral ratios were analyzed in anteromedial, anterolateral, posteromedial and posterolateral subregions. Varus‐OA and valgus‐OA were compared to controls. Compared to controls (1.19–1.54 mm), Cart.Th in varus‐OA was significantly lower anteromedially (0.58 mm, −59%) and higher laterally (2.19–2.47 mm, +60–63%); in valgus‐OA, Cart.Th was significantly higher posteromedially (1.86 mm, +56%). Control medial‐to‐lateral Cart.Th ratios were around unity (0.8–1.1), in varus‐OA significantly below (0.2–0.6) and in valgus‐OA slightly above (1.0–1.3) controls. SBPl.Th and BV/TV were significantly higher medially in varus‐OA (0.58‐0.72 mm and 37–44%, respectively) and laterally in valgus‐OA (0.60–0.61 mm and 32–37%), compared to controls (0.26–0.47 mm and 18–37%). In varus‐OA, the medial‐to‐lateral SBPl.Th and BV/TV ratios were above unity (1.4–2.4) and controls (0.8–2.1); in valgus‐OA they were closer to unity (0.8‐1.1) and below controls. Varus‐ and valgus‐OA tibia differ significantly from controls in Cart.Th, SBPl.Th and STB microarchitecture depending on joint alignment, suggesting structural changes in OA may reflect differences in medial‐to‐lateral load distribution upon the tibial plateau. Here we identified an inverse relationship between cartilage thickness and underlying subchondral bone, suggesting a whole‐joint response in OA to daily stimuli. [ABSTRACT FROM AUTHOR]