Back

Ultrasound-guided skeletal muscle biopsy technique permits measurement of structural, functional, cellular and biochemical properties

Barber, A.; Willbanks, A.; Meza, G.; Ferey, J.; Meyer, G.; Dayanidhi, S.; Arnold, W. D.; Lieber, R. L.; Roy, I.

2026-01-02 rehabilitation medicine and physical therapy
10.64898/2025.12.30.25343237 medRxiv
Show abstract

Human muscle biopsies are often required to study or diagnose diseases. However, traditional approaches are challenging due to limited sample size, quality, or patient discomfort. Fine-gauge needle biopsies ([≥]14-gauge), present an alternative but yield insufficient sample sizes for histology or function. Ultrasound guidance, coupled with vacuum-assisted, single needle-insertion multiple sampling addresses these challenges. In 19 healthy participants (mean age: 30.1{+/-}10 years, 42% male), 2-3 samples were collected from a single needle insertion into the vastus lateralis (VL) and tibialis anterior (TA). Summed VL and TA sample masses averaged 148{+/-}38mg and 166{+/-}64mg, with dimensions of 15.83{+/-}8 x 2.9{+/-}0.6mm2 (VL) and 15.07{+/-}7 x 3.1{+/-}0.9mm2 (TA). VL had a mean fiber cross-sectional area of 4,347{+/-}1,931{micro}m2, with 221{+/-}86 fibers quantified. Samples were of sufficient size and quality for thorough analyses from a single biopsy procedure, including mitochondrial respirometry, RT-PCR, collagen content, and biomechanical function. Fibers produced typical isometric stress values of 187kPa with a passive modulus of 239kPa (peak) and 79kPa (stress-relaxed). This procedure was well tolerated, with an average immediate pain rating of 1.5{+/-}1 (range:0-4, scale: 1-10) and 24-hour follow-up rating of 1.7{+/-}1 (range:0-4). This report describes an approach that yields high-quality muscle samples suitable for histological and biochemical analyses while minimizing discomfort.

Published in Scientific Reports (predicted rank #7) · training set

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.