98%
921
2 minutes
20
Objective: Computed tomography (CT) can deliver multiple parameters relevant to osteoarthritis. In this study we demonstrate that a 3-D multiparametric approach at the weight bearing knee with cone beam CT is feasible, can include multiple parameters from across the joint space, and can reveal stronger relationships with disease status in combination.
Design: 33 participants with knee weight bearing CT (WBCT) were analysed with joint space mapping and cortical bone mapping to deliver joint space width (JSW), subchondral bone plate thickness, endocortical thickness, and trabecular attenuation at both sides of the joint. All data were co-localised to the same canonical surface. Statistical parametric mapping (SPM) was applied in uni- and multivariate models to demonstrate significant dependence of parameters on Kellgren & Lawrence grade (KLG). Correlation between JSW and bony parameters and 2-week test-retest repeatability were also calculated.
Results: SPM revealed that the central-to-posterior medial tibiofemoral joint space was significantly narrowed by up to 0.5 mm with significantly higher tibial trabecular attenuation up to 50 units for each increment in KLG as single features, and in a wider distribution when combined (p<0.05). These were also more strongly correlated with worsening KLG grade category. Test-retest repeatability was subvoxel (0.37 mm) for nearly all thickness parameters.
Conclusions: 3-D JSW and tibial trabecular attenuation are repeatable and significantly dependent on radiographic disease severity at the weight bearing knee joint not just alone, but more strongly in combination. A quantitative multiparametric approach with WBCT may have potential for more sensitive investigation of disease progression in osteoarthritis.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9559750 | PMC |
http://dx.doi.org/10.1016/j.ostima.2022.100069 | DOI Listing |
Abdom Radiol (NY)
September 2025
Department of Radiology, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics and Gynecology and Pediatrics, Fujian Medical University, Fuzhou, China.
Background: We aimed to develop and validate a radiomics-based machine learning nomogram using multiparametric magnetic resonance imaging to preoperatively predict substantial lymphovascular space invasion in patients with endometrial cancer.
Methods: This retrospective dual-center study included patients with histologically confirmed endometrial cancer who underwent preoperative magnetic resonance imaging (MRI). The patients were divided into training and test sets.
JB JS Open Access
September 2025
Division of Orthopedic Surgery, Department of Regenerative and Transplant Medicine, Niigata University Graduate School of Medical and Dental Science, Niigata, Japan.
Background: Lower extremity alignment in knee osteoarthritis (OA) is conventionally assessed using standing radiographs. However, symptoms often manifest during gait. Understanding dynamic alignment during gait may help characterize disease progression and inform treatment strategies.
View Article and Find Full Text PDFNeural Netw
September 2025
Shanghai Maritime University, Shanghai, 201306, China. Electronic address:
Cross-modal hashing aims to leverage hashing functions to map multimodal data into a unified low-dimensional space, realizing efficient cross-modal retrieval. In particular, unsupervised cross-modal hashing methods attract significant attention for not needing external label information. However, in the field of unsupervised cross-modal hashing, there are several pressing issues to address: (1) how to facilitate semantic alignment between modalities, and (2) how to effectively capture the intrinsic relationships between data, thereby constructing a more reliable affinity matrix to assist in the learning of hash codes.
View Article and Find Full Text PDFPLoS One
September 2025
Department of design fundamentals, Faculty of Mechanical Engineering, Industrial University of Ho Chi Minh City, Ho Chi Minh City, Vietnam.
The slider-crank mechanism (SCM) is fundamental to various mechanical systems. However, optimizing its dynamic performance remains a pressing challenge due to excessive torque, joint reactions, and energy consumption. This study introduces two key innovations to address these challenges: (1) the integration of springs into SCM to optimize dynamic performance and (2) a novel hybrid optimization approach combining the Conjugate Direction with Orthogonal Shift (CDOS) method and Parameter Space Investigation (PSI).
View Article and Find Full Text PDFJ Am Chem Soc
September 2025
Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou 215123, Jiangsu P. R. China.
Advances in molecular analysis and characterization techniques should revolutionize the methods for scientific exploration across physics, chemistry, and biology, fundamentally overturning our understanding of interactions and processes that govern molecular behavior at the microscopic level. Currently, the absence of a molecular analysis method that can both quantify molecules and achieve single-molecule spatial resolution hinders our study of complex molecular systems in sorption and catalysis. Here, we propose a quantitative analysis strategy for small molecules confined in ZSM-5, a zeolite material extensively used in catalysis and gas separation, based on low-dose transmission electron microscopy.
View Article and Find Full Text PDF