Orthopedics

Accelerometer-measured postoperative physical activity confers a significant mortality benefit following joint arthroplasty.

AIMS: The aim of this study was to examine the association between postoperative physical activity and mortality following hip and knee arthroplasty. METHODS: A retrospective cohort study was conducted using the UK Biobank dataset, linked to hospital and death registry data. Adults undergoing hip or knee arthroplasty with valid postoperative accelerometer data were included. Physical activity (PA)...

An in situ non-contact 3D microscopic measurement system for temporal bone anatomy based on stereo imaging.

Accurate quantitative assessment of temporal bone microanatomy is essential for otologic research and surgical planning. However, existing measurement approaches, including manual tools, ex vivo microscopy, and high-resolution computed tomography, are limited by contact requirements, indirect measurement, insufficient spatial resolution, or the inability to provide efficient quantitative feedback ...

A two-stage deep-learning model using MobileNetV2 and U-Net for CT-based muscle volume assessment in total hip arthroplasty.

Preoperative muscle strength is an important predictor of functional recovery after total hip arthroplasty (THA); however, accurate assessment is diff...

Grading knee cartilage degeneration and meniscal injury with combined ACS-accelerated T1ρ and T2 mapping.

OBJECTIVE: To evaluate the diagnostic performance of artificial intelligence-compressed sensing (ACS)-accelerated T1ρ mapping combined with convention...

Transformer-based models in dentistry: a systematic review.

BACKGROUND: Transformer-based architectures have rapidly gained prominence in medical imaging due to their ability to model long-range dependencies an...

Spinal cord reserve is associated with multi-dimensional clinical resilience in multiple sclerosis.

OBJECTIVE: Spinal canal area (SCaA)-a proxy for maximal lifetime spinal cord growth-has recently been associated with concurrent disability and future...

Clinical Implementation of Opportunistic Screening for Osteoporosis.

Opportunistic screening leverages existing imaging examinations performed for unrelated routine clinical indications to systematically extract quantit...

Evaluating generative AI responses at the 3-month timepoint following total knee arthroplasty.

BACKGROUND: Patients increasingly seek health information prior to and following total knee arthroplasty (TKA), often using generative AI chatbots int...

Repeatability of AI-quantified incidental findings on lung cancer screening CT scans in the NELSON trial.

OBJECTIVES: Computed tomography (CT) scans for lung cancer screening provide the opportunity of quantifying incidental findings. We evaluated the repe...

Decentralized neural dynamics and sensory constraints shape brittle star locomotion.

Brittle stars move with remarkable whole-body coordination despite lacking a central brain. With five identical arms radiating from a central disc, th...

Balancing accuracy and efficiency in lumbar spine image segmentation using multi-scale attention and residual learning.

Accurate automated segmentation of Lumbar Spine Structures (LSS) in Magnetic Resonance Imaging (MRI) is important for effective diagnosis and treatmen...

A semantic segmentation model to predict subcellular glycogen localization using transmission electron microscopy images.

Transmission electron microscopy (TEM) is the gold standard for assessing subcellular glycogen localization in skeletal muscle fibres, but conventiona...

Computer-aided diagnosis system for thoracic computed tomography of rib fractures in older emergency patients: A preliminary study.

The peculiarities of older individuals related to osteoporosis and hyperostosis may lead to a higher rate of misdiagnosis of rib fractures on computed...

EDRNet-based adolescent idiopathic scoliosis screening method using bare-back images.

BACKGROUND: Adolescent idiopathic scoliosis (AIS) affects 2-3% of adolescents. Current screening relies on X-rays, which limits large-scale applicatio...

Multimodal Deep Learning for Predicting Deep Vein Thrombosis Risk After Total Knee Arthroplasty: A Clinical Study.

BACKGROUND: Deep vein thrombosis (DVT) following total knee arthroplasty (TKA) remains a major postoperative complication. Conventional risk assessmen...

Hybrid deep learning ensemble model for detecting small to medium rotator cuff tears from shoulder radiographs.

BACKGROUND: Rotator cuff tears (RCTs) represent a common orthopedic condition, the diagnosis of which often requires advanced imaging techniques. Nota...

The AI implementation gap in trauma radiography: standalone versus discretionary AI-integrated fracture detection.

OBJECTIVE: In emergency trauma care, artificial intelligence (AI) may aid fracture detection on radiographs, potentially reducing radiologists' worklo...

Longitudinal patient-reported outcomes after spinal fusion for adolescent idiopathic scoliosis: recovery trajectories and insights into surgical timing.

PURPOSE: Health-related quality-of-life (HRQOL) assessment provides insight into patient's subjective experiences that complement traditional clinical...

Explainable machine learning on resting-state magnetoencephalography power spectra reveals neural alterations in knee osteoarthritis.

This study aimed to investigate abnormal patterns of resting-state magnetoencephalography (MEG) power spectra in patients with knee osteoarthritis (KO...

CORR Insights®: Development and Internal Evaluation of EAST-BMS (East Asian Survival Tool for Bone Metastasis Surgery): A Multinational Machine-learning Survival Prediction Model for Patients Undergoing Surgery for Nonspinal Bone Metastasis in East Asia.