To utilize a novel imaging technique employing ultrasound computed tomography (USCT) integrated with full waveform inversion (FWI) for the quantitative assessment of muscle fat content.

Thirty-nine ex-vivo fresh pig hindlimb models were scanned using a ring-array USCT system (512-element, 0.9 MHz). High-resolution acoustic velocity images were reconstructed using a frequency-domain multiscale FWI algorithm. Following sound speed image acquisition, fat area percentage was calculated based on the acoustic speed difference between muscle tissue and adipose tissue. Pathological analysis (hematoxylin-eosin [HE] staining) served as the gold standard for measuring fat area percentage for comparative validation. Correlation and agreement between USCT and pathological results were assessed using Pearson correlation analysis, intraclass correlation coefficient (ICC), and Bland-Altman plot analysis.

The muscle fat content measured by USCT was (17.79±8.97)%, while the pathological measurement result was (19.90±9.42)%. Correlation analysis revealed a significant positive correlation between USCT and pathological intramuscular fat content (r = 0.874, P<0.001). Agreement analysis showed an ICC of 0.853 (95% confidence interval: 0.704-0.925, P<0.05) between USCT and pathological results. The Bland-Altman plot indicated that the limits of agreement (LOA) ranging from -11.22% to 6.99%. There was a systematic bias between USCT and pathological measurements of intramuscular fat content (mean difference=-2.11%). Post-deboning USCT imaging clearly differentiated skin, fat, and muscle tissues, significantly enhancing quantitative accuracy.

This study demonstrates that USCT technology based on sound speed inversion can effectively quantify muscle fat content. It provides a novel non-invasive approach for the early diagnosis of muscle degenerative diseases and establishes a crucial technical foundation for the precise imaging assessment of musculoskeletal metabolic disorders.