Three-dimensional morphometry of the normal nasal septum on computed tomography: sex- and age-specific reference values from 1,373 adults

Abstract Purpose. Normative data for the three-dimensional anatomy of the nasal septum are sparse. We applied automated segmentation to a large series of adults with radiologically normal sinonasal anatomy to establish sex- and age-specific reference values for septal size, thickness, and midline deviation. Methods. Retrospective cross-sectional study of 1,373 adults (394 men, 979 women; age 18 to 90 years) with sinus computed tomography reported as normal. The septum was segmented by a validated three-dimensional convolutional network (held-out Dice 0.983), and 12 parameters were computed from each segmentation: volume, surface area, maximal and mean sagittal cross-sectional area, three linear extents, three thickness measures, and maximal midline deviation and deviation angle. Reference percentiles were computed by sex and by sex within four age bands; age trends were estimated by linear and quantile regression. Results. Median septal volume was 16,710 mm³ in men (5th to 95th percentile 13,594 to 20,455) and 12,500 mm³ in women (9,963 to 15,329); median mean thickness was 4.89 and 4.29 mm. All size and thickness parameters were larger in men. In men, volume, depth, height, and maximal thickness increased by 1.2 to 1.4% per decade of age; in women they were constant (sex-by-age interaction P ≤ 0.021). Midline deviation did not vary with age, and its 95th percentile was about 3 mm in both sexes. Conclusion. These sex- and age-specific percentiles provide a quantitative reference for interpreting septal anatomy on computed tomography, planning septal surgery, and selecting reference geometries for airflow modeling.

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Publication Details

Journal
Research Square
Published
2026-11-01
DOI
https://doi.org/10.21203/rs.3.rs-11297009/v1
Primary Topic
Nasal Surgery and Airway Studies
Type
preprint
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preprint

Three-dimensional morphometry of the normal nasal septum on computed tomography: sex- and age-specific reference values from 1,373 adults

Tanya J. Rath, Amar Miglani, Michael T. Sramek, H G Gibbs et al.
3 links
Research Square
Nasal Surgery and Airway Studies
preprint

Three-dimensional morphometry of the normal nasal septum on computed tomography: sex- and age-specific reference values from 1,373 adults

Tanya J. Rath, Amar Miglani, Michael T. Sramek, H G Gibbs, Stephen Bansberg, Michael Marino
preprint en

Abstract

Abstract Purpose. Normative data for the three-dimensional anatomy of the nasal septum are sparse. We applied automated segmentation to a large series of adults with radiologically normal sinonasal anatomy to establish sex- and age-specific reference values for septal size, thickness, and midline deviation. Methods. Retrospective cross-sectional study of 1,373 adults (394 men, 979 women; age 18 to 90 years) with sinus computed tomography reported as normal. The septum was segmented by a validated three-dimensional convolutional network (held-out Dice 0.983), and 12 parameters were computed from each segmentation: volume, surface area, maximal and mean sagittal cross-sectional area, three linear extents, three thickness measures, and maximal midline deviation and deviation angle. Reference percentiles were computed by sex and by sex within four age bands; age trends were estimated by linear and quantile regression. Results. Median septal volume was 16,710 mm³ in men (5th to 95th percentile 13,594 to 20,455) and 12,500 mm³ in women (9,963 to 15,329); median mean thickness was 4.89 and 4.29 mm. All size and thickness parameters were larger in men. In men, volume, depth, height, and maximal thickness increased by 1.2 to 1.4% per decade of age; in women they were constant (sex-by-age interaction P ≤ 0.021). Midline deviation did not vary with age, and its 95th percentile was about 3 mm in both sexes. Conclusion. These sex- and age-specific percentiles provide a quantitative reference for interpreting septal anatomy on computed tomography, planning septal surgery, and selecting reference geometries for airflow modeling.

Research Square
Mayo Clinic in Arizona (US), Mayo Clinic Hospital (US)
Good health and well-being
Nasal Surgery and Airway Studies
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