ArticleOrthopaedic surgery2026
Artificial Intelligence-Enhanced Quantitative 3D Analysis of Distal Radioulnar Ligament Insertion Footprints of the Triangular Fibrocartilage Complex With Interactive Validation.
Article in Orthopaedic surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Disc degeneration did not lead to an increased incidence of adjacent vertebral fractures in wedge-type OVCF patients.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2026Article
- Artificial Intelligence-Enhanced Quantitative 3D Analysis of Distal Radioulnar Ligament Insertion Footprints of the Triangular Fibrocartilage Complex With Interactive Validation.Orthopaedic surgery · 2026Article
- Degenerative scoliosis may trigger higher incidence of adjacent vertebral fractures following percutaneous vertebroplasty: a clinical evidence-based biomechanical research.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2026Article
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Authors and funding
14 authors.
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Abstract
objectivesThe distal radioulnar ligaments (DRULs) serve as primary stabilizers to the distal radioulnar joint (DRUJ). Existing cadaveric studies report heterogeneous morphometric data of the three-dimensional (3D) anatomy of the triangular fibrocartilage complex (TFCC) and the ulnar footprints of the DRULs due to methodological variations and small sample sizes, limiting the translation of precise anatomical knowledge to clinical practice. This study quantitatively evaluated the 3D anatomy of the TFCC and the insertions of both superficial and deep DRULs components using three different methods with subsequent interactive validation: (1) direct measurement, (2) 3D scan, and (3) artificial intelligence (AI) enhanced magnetic resonance imaging.
methodsEleven adult cadaveric upper limbs were included. All specimens underwent 3.0-Tesla MRI scans, which were then processed by AI algorithms for super-resolution enhancement and semi-automatic segmentation. The areas of deep and superficial limbs of DRUL ulnar footprint were measured in the super-resolution MRI images using the Slicer software. The specimens were then dissected and anatomical measurements of dorsal-volar maximal length and radial-ulnar maximum length of deep ulnar DRUL footprint were performed on the specimens' photographs. Anatomical measurements of ulna, radius, triangular fibrocartilage, and ulnar insertions footprint of both superficial and deep DRULs were conducted subsequently using a 3D scanner. Primary outcome measures included the area and morphological classification (irregular quadrilateral, ribbon, semilunar) of the deep and superficial ulnar DRUL footprints. Statistical analysis encompassed intraclass correlation coefficients (ICC) for agreement assessment and multiple linear regression to explore associations.
resultsThe mean area of the deep foveal fibers of DRUL was 43.39 ± 13.49 mm
conclusionsCompared to direct measurement and 3D scan, the AI algorithms developed and validated for wrist MRI image enhancement demonstrated high accuracy and reliability in anatomical measurements of DRULs.
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