AI-based Hip Fracture Classification from Pelvic X-ray Images Using a Hybrid PEFT-ViT and XGBoost Model.

Biplane Fractures of the Distal Femur: A Proposed Computed Tomography-Based Classification and Surgical Management

Abstract Introduction: Management of periarticular fractures requires a careful understanding of fracture characteristics and proper pre-operative planning. We suggest a new computerized tomography (CT) based classification system, which assists in planning surgical approaches and in implant selection, and provides an...

CT-based assessment of posterior ligamentous complex integrity in AO spine type A1–A2 thoracolumbar junction fractures under conditions of diagnostic uncertainty

Purpose: The diagnosis of posterior ligamentous complex (PLC) injury in thoracolumbar fractures remains a major challenge under conditions of diagnostic uncertainty, particularly when magnetic resonance imaging (MRI) is unavailable or delayed. This study aimed to develop and internally validate a quantitative CT-based...

EP1.40 Defining the Spectrum of Acetabular Dysplasia: A 3D Clockface Classification System in a Large Periacetabular Osteotomy Cohort

Abstract Introduction Traditional classification of acetabular dysplasia in mature hips relies on plain radiographs and the lateral center edge angle (LCEA), which fail to capture the full complexity of the femoral head-acetabulum relationship. While CT-based measurements and early 3D analyses have improved morphologic...

Classification of vertebral compression fractures using CT-based radiomics: a viable alternative to MRI

To evaluate whether CT-based machine learning models can accurately detect and differentiate fresh from old vertebral compression fractures (VCFs). From June 2018 to December 2024, patients with VCFs from two hospitals who underwent both CT and MRI within one week of each other were retrospectively enrolle...

Automated Cortical Thickness Index Measurement in Pelvic Radiographs Using a Multi-Stage Deep Learning Framework.

Radiographic Classification of Low-Energy Distal Radius Fracture Status Using Automated Hand Segmentation.