Artificial Intelligence-Enhanced Quantitative 3D Analysis of Distal Radioulnar Ligament Insertion Footprints of the...

Area of Science:

• Orthopedics
• Radiology
• Anatomy

Background:

• Distal radioulnar ligaments (DRULs) are key stabilizers of the distal radioulnar joint (DRUJ).
• Previous studies on the triangular fibrocartilage complex (TFCC) and DRUL footprints show inconsistent morphometric data.
• Methodological variations and small sample sizes limit the clinical application of existing anatomical knowledge.

Purpose of the Study:

• To quantitatively evaluate the three-dimensional (3D) anatomy of the TFCC.
• To assess the ulnar footprints of superficial and deep DRUL components.
• To compare the accuracy of direct measurement, 3D scanning, and AI-enhanced MRI for DRUL anatomical evaluation.

Main Methods:

• Eleven adult cadaveric upper limbs were scanned using 3.0-Tesla MRI.
• AI algorithms were employed for super-resolution enhancement and semi-automatic segmentation of MRI images.
• Measurements were taken using direct dissection, 3D scanning, and AI-enhanced MRI, with subsequent validation.

Main Results:

• AI-enhanced MRI showed excellent agreement (ICC=0.95-0.96) with 3D scanning for DRUL footprint areas.
• 3D scanning demonstrated excellent agreement (ICC=0.97-0.98) with direct measurements for DRUL dimensions.
• The deep DRUL footprint area was significantly larger than the superficial footprint area.

Conclusions:

• AI-enhanced MRI offers a highly accurate and reliable method for anatomical measurements of DRULs.
• This AI approach surpasses traditional methods like direct measurement and 3D scanning in precision.
• Improved anatomical data from AI can enhance clinical understanding and treatment of DRUJ pathologies.