Feasibility of magnetic resonance imaging manual segmentation of human intercostal muscles: a morphological analysis approach

Background Intercostal muscles (ICM) are essential for thoracic stability and respiratory mechanics. In musculoskeletal disorders and respiratory dysfunction, alterations in ICM structure and function may contribute to impaired ventilatory performance and reduced clinical capacity. Despite their physiological importance, fundamental properties of internal and external ICM fascicles—such as fascicle length, muscle volume, and interfascicular spacing—remain insufficiently described. This is mainly due to the limited spatial resolution of conventional imaging techniques such as ultrasound, computed tomography (CT), and electromyography (EMG), which cannot resolve individual ICM fascicles with sufficient detail for quantitative analysis. Methods This study aimed to address this gap. Eleven high-resolution thoracic T1- and T2-weighted magnetic resonance imaging (MRI) datasets were manually segmented using 3D Slicer software to characterize internal and external ICM fascicles. Standardized coronal, sagittal, and para-axial sequences were used to extract fascicle-specific parameters, including length, orientation relative to muscle course, volume, physiological cross-sectional area (PCSA), and interfascicular distance. Results Coronal imaging allowed reliable measurement of fascicle length and orientation for internal ICM. However, assessment of external ICM required additional para-axial sequence analysis to identify fascicle layers and attachment sites. Volumetric analysis and PCSA calculation for both internal and external ICM were feasible only through combined coronal and para-axial imaging. Results demonstrated that fascicle volume and length were proportionally related to calculated PCSA values. Conclusion Manual segmentation enabled detailed physiological assessment of ICM and demonstrated both the potential and limitations of current imaging modalities. Quantification of volume, PCSA, and especially external ICM remains challenging due to the structural complexity of the thoracic wall and reliance on axial planes. Nevertheless, this study presents a practical imaging protocol for thoracic musculoskeletal assessment. It enables refined morphometric analysis using high-resolution imaging and establishes a foundation for future biomechanical modeling and individualized therapeutic approaches. Importantly, it provides the first successful example of quantitative analysis of parasternal intercostal muscle morphology in healthy individuals, forming a basis for comparative studies in patient populations with respiratory impairment.

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Journal
Frontiers in Musculoskeletal Disorders
Published
2026-01-12
DOI
https://doi.org/10.3389/fmscd.2025.1677352
Primary Topic
Chronic Obstructive Pulmonary Disease (COPD) Research
Type
article
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article

Feasibility of magnetic resonance imaging manual segmentation of human intercostal muscles: a morphological analysis approach

Laura Steingruber, Maria Hammer, Paul L. Moll, S. Raab et al.
Frontiers in Musculoskeletal Disorders
Chronic Obstructive Pulmonary Disease (COPD) Research
article

Feasibility of magnetic resonance imaging manual segmentation of human intercostal muscles: a morphological analysis approach

Laura Steingruber, Maria Hammer, Paul L. Moll, S. Raab, Marco Koch, Patrick Ruess
article en

Abstract

Background Intercostal muscles (ICM) are essential for thoracic stability and respiratory mechanics. In musculoskeletal disorders and respiratory dysfunction, alterations in ICM structure and function may contribute to impaired ventilatory performance and reduced clinical capacity. Despite their physiological importance, fundamental properties of internal and external ICM fascicles—such as fascicle length, muscle volume, and interfascicular spacing—remain insufficiently described. This is mainly due to the limited spatial resolution of conventional imaging techniques such as ultrasound, computed tomography (CT), and electromyography (EMG), which cannot resolve individual ICM fascicles with sufficient detail for quantitative analysis. Methods This study aimed to address this gap. Eleven high-resolution thoracic T1- and T2-weighted magnetic resonance imaging (MRI) datasets were manually segmented using 3D Slicer software to characterize internal and external ICM fascicles. Standardized coronal, sagittal, and para-axial sequences were used to extract fascicle-specific parameters, including length, orientation relative to muscle course, volume, physiological cross-sectional area (PCSA), and interfascicular distance. Results Coronal imaging allowed reliable measurement of fascicle length and orientation for internal ICM. However, assessment of external ICM required additional para-axial sequence analysis to identify fascicle layers and attachment sites. Volumetric analysis and PCSA calculation for both internal and external ICM were feasible only through combined coronal and para-axial imaging. Results demonstrated that fascicle volume and length were proportionally related to calculated PCSA values. Conclusion Manual segmentation enabled detailed physiological assessment of ICM and demonstrated both the potential and limitations of current imaging modalities. Quantification of volume, PCSA, and especially external ICM remains challenging due to the structural complexity of the thoracic wall and reliance on axial planes. Nevertheless, this study presents a practical imaging protocol for thoracic musculoskeletal assessment. It enables refined morphometric analysis using high-resolution imaging and establishes a foundation for future biomechanical modeling and individualized therapeutic approaches. Importantly, it provides the first successful example of quantitative analysis of parasternal intercostal muscle morphology in healthy individuals, forming a basis for comparative studies in patient populations with respiratory impairment.

Frontiers in Musculoskeletal DisordersVol. 3
University of Stuttgart (DE), Technische Hochschule Augsburg (DE), University of Augsburg (DE), Waldkrankenhaus Rudolf Elle (DE), Jena University Hospital (DE), Friedrich Schiller University Jena (DE)
Openalex Percentile: Top 91%
Chronic Obstructive Pulmonary Disease (COPD) Research
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