TY - JOUR
T1 - New insights into the impact of bed rest on lumbopelvic muscles
T2 - a computer-vision model approach to measure fat fraction changes
AU - Wesselink, Evert O.
AU - Hides, Julie
AU - Elliott, James M.
AU - Hoggarth, Mark
AU - Weber, Kenneth A.
AU - Salomoni, Sauro E.
AU - Tran, Vienna
AU - Lindsay, Kirsty
AU - Hughes, Luke
AU - Weber, Tobias
AU - Scott, Jonathan
AU - Hodges, Paul W.
AU - Caplan, Nick
AU - De Martino, Enrico
N1 - Publisher Copyright:
Copyright © 2025 the American Physiological Society.
PY - 2025/1
Y1 - 2025/1
N2 - Space agencies plan crewed missions to the Moon and Mars. However, microgravity-induced lumbopelvic deconditioning, characterized by an increased fat fraction (FF) due to reduced physical activity, poses a significant challenge to spine health. This study investigates the spatial distribution of FF in the lumbopelvic muscles to identify the most affected regions by deconditioning, utilizing a computer-vision model and a tile-based approach to assess FF changes. Twenty-four healthy individuals (8 F) were recruited, and automatic segmentation of the lumbopelvic muscles was applied before and after 59 days of head-down tilt bed rest (HDTBR + 59) and 13 days of reconditioning (R + 13). Axial Dixon sequence images were acquired from 3 T magnetic resonance imaging. FF in the lumbar multifidus (LM), lumbar erector spinae (LES), quadratus lumborum, psoas major, gluteus maximus (GMax), gluteus medius (GMed), and gluteus minimus (GMin) muscles from the upper margin of L1 vertebra to the inferior border of GMax muscle were automatically derived using a computer-vision model. Lumbar muscles were segmented into eight tiles (superficial and deep, lateral to medial), and gluteal muscles into regions (anterior/superior for GMed and GMin, superior/inferior for GMax). At HDTBR + 59, the deep centrolateral region at L5/S1 for LM (18.7 ± 15.7%, P < 0.001; d = 0.97) and the deep medial region at Upper L4 for LES (5.4 ± 5.9%, P < 0.001; d = 0.34) showed the largest increase in FF compared with baseline data collection. These regions did not recover at R + 13 (P < 0.05; d ≥ 0.25). These findings highlight the need to target deep fascicles of LM and LES in countermeasure strategies to mitigate microgravity-induced lumbopelvic deconditioning, optimizing spine health, and performance.
AB - Space agencies plan crewed missions to the Moon and Mars. However, microgravity-induced lumbopelvic deconditioning, characterized by an increased fat fraction (FF) due to reduced physical activity, poses a significant challenge to spine health. This study investigates the spatial distribution of FF in the lumbopelvic muscles to identify the most affected regions by deconditioning, utilizing a computer-vision model and a tile-based approach to assess FF changes. Twenty-four healthy individuals (8 F) were recruited, and automatic segmentation of the lumbopelvic muscles was applied before and after 59 days of head-down tilt bed rest (HDTBR + 59) and 13 days of reconditioning (R + 13). Axial Dixon sequence images were acquired from 3 T magnetic resonance imaging. FF in the lumbar multifidus (LM), lumbar erector spinae (LES), quadratus lumborum, psoas major, gluteus maximus (GMax), gluteus medius (GMed), and gluteus minimus (GMin) muscles from the upper margin of L1 vertebra to the inferior border of GMax muscle were automatically derived using a computer-vision model. Lumbar muscles were segmented into eight tiles (superficial and deep, lateral to medial), and gluteal muscles into regions (anterior/superior for GMed and GMin, superior/inferior for GMax). At HDTBR + 59, the deep centrolateral region at L5/S1 for LM (18.7 ± 15.7%, P < 0.001; d = 0.97) and the deep medial region at Upper L4 for LES (5.4 ± 5.9%, P < 0.001; d = 0.34) showed the largest increase in FF compared with baseline data collection. These regions did not recover at R + 13 (P < 0.05; d ≥ 0.25). These findings highlight the need to target deep fascicles of LM and LES in countermeasure strategies to mitigate microgravity-induced lumbopelvic deconditioning, optimizing spine health, and performance.
KW - artificial intelligence
KW - bed rest study
KW - Dixon sequence
KW - intramuscular fatty infiltration
KW - magnetic resonance imaging
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U2 - 10.1152/japplphysiol.00502.2024
DO - 10.1152/japplphysiol.00502.2024
M3 - Article
C2 - 39611883
AN - SCOPUS:85214029578
SN - 8750-7587
VL - 138
SP - 157
EP - 168
JO - Journal of Applied Physiology
JF - Journal of Applied Physiology
IS - 1
ER -