• BACKGROUND
    • The trabecular architecture of proximal femur plays a crucial role in hip stability and load distribution and is often ignored in hip fracture fixation due to limited anatomical knowledge. This study analyses trabecular morphology and stress distribution, aiming to provide an anatomical foundation for optimising implant designs.
  • MATERIALS AND METHODS
    • Twenty-one formalin-fixed human pelvises (twelve male, nine female) were prepared using P45 sectional plastination. They were sliced into 3 mm sections in the coronal, sagittal, and horizontal planes and then photographed. A 3D femur model was created from computed tomographic scans and analysed for finite element analysis (FEA) using Mimics, 3-matics, and Abaqus software to simulate static and dynamic loads, visualising stress paths for compressive and tensile regions and identifying fracture-vulnerable zones.
  • RESULTS
    • Two main trabecular systems were identified: the medial and lateral systems. The medial system includes a primary vertical trabecular group extending from the femoral shaft's medial calcar to the head and two primary horizontal groups arching from the lateral shaft, greater trochanter, and femoral neck's anterolateral and posterolateral walls toward the medial side, intersecting with the primary vertical group in the head. Secondary vertical group intersects with secondary horizontal group at the neck-trochanteric junction to form the lateral system. FEA showed peak compressive stress along the vertical groups, calcar, and medial cortex, and tensile stress along the horizontal groups, greater trochanter, and lateral cortex, creating balanced support that stabilises the femoral neck and shaft.
  • CONCLUSION
    • The strength of proximal femur depends on dense cortical bone, calcar femorale, lateral and medial trabecular systems, and greater trochanter. While anterolateral and posterolateral areas of femoral neck and intertrochanteric regions are potential weak zones. Trabecular pattern follows stress paths, optimising load distribution. These insights aid in designing robotic and bionic implants that mimic natural stress patterns, reducing complications.