Artificial intelligence-based thigh muscle volume profiling on CT in elderly East Asian patients with hip fracture

Skeletal muscle mass and quality are critical determinants of outcomes in hip fracture patients. However, most prior studies have relied on 2D cross-sectional area measurements, which may not accurately reflect the complex 3D muscle distribution. This study aimed to quantify 3D thigh muscle volume and intramuscular adipose tissue (IMAT) in a large elderly East Asian hip fracture cohort using an AI-assisted segmentation pipeline.

A total of 1,287 patients from a multi-center hip fracture cohort were included. Preoperative whole-thigh CT scans were analyzed using a validated AI-based 3D UNETR segmentation model to delineate 26 individual muscles. Height-normalized muscle volumes (cm³/m²) and IMAT percentages (%) were computed for four anatomic regions: anterior, medial, posterior, and gluteal.

The gluteal group exhibited the largest height-normalized muscle volume (855.64 ± 216.38 cm³/m²), followed by the anterior group (784.57 ± 243.17 cm³/m²). On an individual level, the gluteus maximus was the largest single muscle. Paradoxically, the gluteal group showed the highest IMAT percentage (1.43 ± 0.84%), higher than the anterior (0.57 ± 0.42%) and medial groups (0.71 ± 0.51%). Specifically, the highest IMAT percentages were observed in the multifidus (1.93 ± 1.31%) and tensor fasciae latae (1.92 ± 1.03%), which contrasts with the relatively preserved primary locomotive muscles such as the vastus medialis (0.38 ± 0.32%).

Elderly hip fracture patients exhibited a dissociation between muscle quantity and quality. The relatively high fatty degeneration observed in stabilizing muscles, including the gluteal muscles and multifidus, despite their large volume, may reflect muscle composition patterns potentially related to postural function. These findings should be considered hypothesis-generating and require validation in prospective studies incorporating direct functional assessments.