Orthopedics

An interpretable PET/CT-based radiomic-clinical model for predicting bone marrow involvement in follicular lymphoma: comparison of pelvic and spine-pelvis VOI frameworks.

PURPOSE: To investigate the feasibility of non-invasively identifying bone marrow involvement (BMI) in follicular lymphoma (FL) using baseline 18F-FDG PET/CT combined with multidimensional feature fusion, and to compare the impact of different bone marrow volume-of-interest (VOI) frameworks on model performance. METHODS: This retrospective study included 187 patients with newly diagnosed FL, 93 of...

MDVM-UNet: lumbar MRI segmentation and lordosis angle measurement via a dual-driven mechanism.

With the rising incidence of degenerative lumbar spine disorders, accurate segmentation of spinal structures based on magnetic resonance imaging (MRI) is crucial for intelligent clinical diagnosis and surgical planning, while automated measurement of the lumbar lordosis angle based on segmentation can further support quantitative assessment of the condition. To overcome the issues of limited recep...

Artificial Intelligence-Enhanced Identification of Incidental Findings in Prostate MRI.

OBJECTIVES: The use of prostate magnetic resonance imaging (MRI) is increasing, and coverage often captures substantial portions of the pelvis, visual...

A Multiassessment and Multiprofessional Agents Approach for Medical Chatbot Risk Estimation: Development and Evaluation Study.

BACKGROUND: Assessing chatbot responses across 3 domains-medical, ethical, and legal-is essential to ensuring the safe use of artificial intelligence ...

Osteoarthritis phenotypes: advancing precision medicine through clinical, structural, and molecular stratification.

PURPOSE: Osteoarthritis (OA) is now understood as a heterogeneous syndrome driven by diverse biological, biomechanical, metabolic, genetic, and molecu...

Interpretable machine learning model integrating MRI-derived paraspinal muscle parameters for predicting new vertebral compression fractures after vertebral augmentation.

OBJECTIVES: To develop and validate interpretable machine learning (ML) models incorporating MRI-derived paraspinal muscle parameters to predict new v...

Structure-aware retinal disentanglement reveals the genetic architecture of ocular and systemic diseases.

Deep learning effectively extracts retinal phenotypes but often functions as an entangled black box, obscuring specific genetic mechanisms and hinderi...

Distinct 3-Dimensional Anatomic Patterns Including Flatter Surfaces and Greater Sagittal Inclinations of Intra-articular Structures Are Reliably Identified Through an Artificial Intelligence-Based Pipeline in Anterior Cruciate Ligament-Injured Knees.

PURPOSE: To evaluate whether an automated AI-based pipeline can identify 3-dimensional (3D) anatomic patterns associated with anterior cruciate ligame...

Editorial Commentary: Traveling to A New Dimension in Anterior Cruciate Ligament Injury Risk Stratification: Holistic 3-Dimensional Knee Phenotyping via Automated Artificial Intelligence Pipelines.

Morphologic risk stratification for anterior cruciate ligament injury has historically relied upon isolated two-dimensional radiographic parameters (e...

Global Trends and Research Hotspots in Soccer Injury Literature: A Bibliometric Analysis (1904-2025).

IMPORTANCE: Soccer is associated with a substantial global injury burden, particularly involving lower-extremity and head injuries. Despite extensive ...

On the use of generative models for demographic inference in malaria vectors from genomic data.

Malaria in sub-Saharan Africa is transmitted by mosquitoes from the Anopheles genus. Efforts to control the spread of malaria have often focused on th...

Artificial intelligence in small tissue biopsies: diagnostic applications, histochemical integration, and methodological challenges in surgical pathology.

Small tissue biopsies, including renal core biopsies, bone marrow trephines, gastrointestinal endoscopic samples, prostate needle cores, liver biopsie...

Acoustic-based intraoperative assessment of femoral stem initial stability in cementless THA via sensitive frequency band identification.

Intraoperative assessment of femoral stem initial stability in cementless total hip arthroplasty (THA) predominantly relies on subjective tactile and ...

Generalizable CT-free PET attenuation and scatter correction via few-shot cross domain adaptation.

The rapid advancements in PET technology, coupled with the need for accurate and efficient imaging, necessitate the development of robust and generali...

Veterinary fracture diagnosis: a deep learning model for dogs long bone fractures.

Bone fractures in dogs are common orthopaedic conditions that require accurate diagnosis and rapid intervention. Traditional radiographic interpretati...

Retinal biological age correlates with bone mineral density and fracture risk score and predicts incident osteoporosis.

Osteoporosis often lacks accessible screening tools, leading to underdiagnosis and increased fracture risk. We explored the potential of a retinal agi...

Tetrahedral framework nucleic acids as a promising vehicle for small molecule drugs of traditional Chinese medicine: application to disease prevention and treatment.

The modernization of Traditional Chinese Medicine (TCM) faces considerable challenges, primarily due to the poor water solubility, low chemical stabil...

Development and Validation of an AI-Integrated System for Automated Fracture Detection and Pedicle Puncture Planning in Lumbar Osteoporotic Vertebral Compression Fractures Based on the Nine-Grid Area Division Method.

OBJECTIVE: The clinical application of the Nine-grid Area Division Method for pedicle puncture in L-OVCF is limited by high technical thresholds and l...

Underperformance of Machine Learning Algorithms Predicting Extended Lengths of Stay and Readmission in Underrepresented Patient Cohorts After Primary Total Hip Arthroplasty.

BACKGROUND: The demand for total hip arthroplasty (THA) is increasing, yet disparities in access and outcomes persist across racial, ethnic, and socio...

MRI-based radiomics explainable model for predicting recurrence of limb chronic osteomyelitis in limb bones treated by Masquelet technique.

AIMS: This study aimed to develop a machine learning model for predicting chronic osteomyelitis recurrence (COR) following the Masquelet technique (MT...