¹Hochschule Hannover, Hannover, Germany
²Memorial University of Newfoundland, St. John's, Canada
³Simon Fraser University, Burnaby, Canada
⁴Huntsman Cancer Institute, Salt Lake City, United States
⁵University of Utah, Salt Lake City, United States

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Introduction: Intermuscular adipose tissue (IMAT), a fat depot located between muscle fibers, has emerged as a clinically relevant biomarker in oncology [1]. IMAT area can be quantified using computed tomography (CT) imaging. Most previous studies have relied on a single axial CT slice at the level of the third lumbar vertebra (L3) [2]. However, this approach limits the ability to assess IMAT distribution across the full thoracic and lumbar spine. This study investigates the axial distribution of IMAT and skeletal muscle (SKM) tissue in cancer-free adults, including subgroup analyses by sex, body mass index (BMI), and age – factors known to influence cancer risk and prognosis.

Methods: We analyzed 30 whole-body CT scans from cancer-free adults available through The Cancer Imaging Archive (TCIA) [3]. Segmentation and quantification of thoracic to lumbar levels (T1–L5) were performed using the Data Analysis Facilitation Suite (DAFS) Express^®. The software generates multiplanar reconstructions to verify anatomical landmarks and define regions of interest prior to automated segmentation. This AI-based tool uses a deep learning algorithm with high reported accuracy and reproducibility (Dice coefficients >0.97, ICCs >0.99) [4], [5]. For all 17 thoracic to lumbar vertebral levels, mean IMAT and SKM areas (cm²) were calculated and visualized using line plots of group means to illustrate distributional patterns. Stratified analyses were performed by sex (male vs. female), age (<50 vs. ≥50 years), and BMI (normal: <25; overweight: ≥25 to <30; obese: ≥30 kg/m²). Statistical differences between groups were tested using independent t-tests for sex and age comparisons and one-way ANOVA for BMI categories. P-values <0.05 were considered statistically significant. All analyses and visualizations were performed using Python version 3.11.9.

Results: Thirty participants were included (47% male, 53% female), with a median age of 47 ± 12.8 years and a median BMI of 27.4 ± 4.9 kg/m². IMAT area was lowest at L4 (7.66 ± 3.34 cm²) and highest at T1 (43.52 ± 15.78 cm²). SKM area was lowest at T10 (90.16 ± 31.42 cm²) and highest at T2 (236.13 ± 65.33 cm²). Similar distribution patterns were observed across subgroups (e.g., male vs. female). Mean IMAT values differed significantly across BMI groups at 14 of the 17 spinal levels, with the highest values observed in the obese group. SKM values were significantly different across BMI groups at 8 of 17 levels, with the highest values identified in overweight participants. No statistically significant differences in IMAT were observed between male and female participants. However, males had significantly higher SKM values compared to females (p<0.00001 at all 17 levels). No significant differences in IMAT or SKM were observed in age-stratified analyses.

Discussion: Our findings demonstrate distinct, level-specific distribution patterns of IMAT and SKM along the axial spine, with variation by sex and BMI. Understanding normative IMAT and SKM distribution across spinal levels in cancer-free adults – both overall and by key demographic subgroups – provides a critical reference for identifying disease-related alterations in cancer patients. Such reference data may support early detection of abnormal tissue distribution patterns associated with onset of disease or treatment response in the future.

The authors declare that they have no competing interests.

The authors declare that an ethics committee vote is not required.

References

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