ArticleEuropean spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society2024
Cross-sectional area and fat infiltration of the lumbar spine muscles in patients with back disorders: a deep learning-based big data analysis.
Article in European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- Fatty infiltration and cross-sectional area as indicators of muscle mass in osteoporosis: a meta-regression study.Frontiers in endocrinology · 2025Pooled it
- Clinical significance and future applications of standardized imaging parameters for assessing paraspinal muscle fatty infiltration in lumbar degenerative disease: a narrative review.Journal of orthopaedic surgery and research · 2026Review
- Deep learning-based assessment of paraspinal muscle degeneration and its relationships to muscle function and disability outcomes in chronic low back pain: a prospective study.European radiology · 2026Article
- Automated deep-learning quantification of intramuscular fat in lumbar spine muscles on Dixon MRI: validation and normative reference values from 173 healthy adults.BMC medical imaging · 2026Article
- Spinal disease image segmentation technology integrating U-ResNet and shape-aware attention.Scientific reports · 2026Article
- Bone Mineral Density and Intermuscular Fat Derived from Computed Tomography Images Using Artificial Intelligence Are Associated with Fracture Healing.Bioengineering (Basel, Switzerland) · 2025Article
- Gender difference in cross-sectional area and fat infiltration of thigh muscles in the elderly population on MRI: an AI-based analysis.European radiology experimental · 2025Article
- Article
- Applications of Artificial Intelligence and Machine Learning in Spine MRI.Bioengineering (Basel, Switzerland) · 2024Review
- Deep learning-based structure segmentation and intramuscular fat annotation on lumbar magnetic resonance imaging.JOR spine · 2024Article
- Fat beyond muscle: Assessing epimuscular fat of the lumbar spine and its association with vertebral level, demographics, BMI, and low back pain.Brain & spine · 2024Article
- A Novel MRI-Based Paravertebral Muscle Quality (PVMQ) Score for Evaluating Muscle Quality and Bone Quality: A Comparative Study with the VBQ Score.Clinical interventions in aging · 2024Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeValidated deep learning models represent a valuable option to perform large-scale research studies aiming to evaluate muscle quality and quantity of paravertebral lumbar muscles at the population level. This study aimed to assess lumbar spine muscle cross-sectional area (CSA) and fat infiltration (FI) in a large cohort of subjects with back disorders through a validated deep learning model.
methodsT2 axial MRI images of 4434 patients (n = 2609 females, n = 1825 males; mean age: 56.7 ± 16.8) with back disorders, such as fracture, spine surgery or herniation, were retrospectively collected from a clinical database and automatically segmented. CSA, expressed as the ratio between total muscle area (TMA) and the vertebral body area (VBA), and FI, in percentages, of psoas major, quadratus lumborum, erector spinae, and multifidus were analyzed as primary outcomes.
resultsMale subjects had significantly higher CSA (6.8 ± 1.7 vs. 5.9 ± 1.5 TMA/VBA; p < 0.001) and lower FI (21.9 ± 8.3% vs. 15.0 ± 7.3%; p < 0.001) than females. Multifidus had more FI (27.2 ± 10.6%; p < 0.001) than erector spinae (22.2 ± 9.7%), quadratus lumborum (17.5 ± 7.0%) and psoas (13.7 ± 5.8%) whereas CSA was higher in erector spinae than other lumbar muscles. A high positive correlation between age and total FI was detected (r
conclusionCSA and FI values of paravertebral muscles vary a lot in accordance with subjects' sex, age and clinical conditions. Given also the large inter-muscle differences in CSA and FI, the choice of muscles needs to be considered with attention by spine surgeons or physiotherapists when investigating changes in lumbar muscle morphology in clinical practice.
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