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<p>Precise measurement of Spinal Cord Cross-Sectional Area (SC-CSA) is crucial for monitoring SC health and diagnosing neurodegenerative diseases. Accurate measurement of SC-CSA is challenging due to several factors such as SC curvature, patient positioning, segmentation methods, and limitations of Magnetic Resonance Imaging (MRI) resolution. Traditional methods that rely on vertebral levels as a reference suffer from inter-subject variability and limited reproducibility. In this study, we propose a novel landmark-based method to define robust anatomical references for standardizing the delineation of SC segment boundaries for SC-CSA measurements. This approach relies on consecutive spinal nerve midpoints (CNMPs) as anatomical references, providing more precise segment delineation and consistent SC-CSA measurements. We validated the effectiveness and robustness of our method using two public datasets of healthy individuals: the first comprises MRI images from different scanners and centers, and the second offers three different head positions for the cervical SC. Experimental results show an intra-subject mean coefficient of variation across head positions of 4.01 ± 2.89% for the proposed CNMP-based landmarks, compared to 4.46 ± 3.10% for vertebral-based landmarks. This demonstrates that the proposed CNMP method can serve as a reliable reference for reducing the variability of CSA measurements compared to the vertebral levels method. Our findings suggest that this approach could potentially aid in the diagnosis of pathological cohorts.</p>

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Spinal nerves as landmarks for spinal cord segment delineation: cervical cross-sectional area measurement in healthy subjects

  • 期刊论文

  • 发表日期：

    2026年5月7日

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  • Tayssir Boushila,
  • Mouna Sahnoun,
  • Fathi Kallel,
  • Nadia Bouattour,
  • Mariem Damak

摘要

Precise measurement of Spinal Cord Cross-Sectional Area (SC-CSA) is crucial for monitoring SC health and diagnosing neurodegenerative diseases. Accurate measurement of SC-CSA is challenging due to several factors such as SC curvature, patient positioning, segmentation methods, and limitations of Magnetic Resonance Imaging (MRI) resolution. Traditional methods that rely on vertebral levels as a reference suffer from inter-subject variability and limited reproducibility. In this study, we propose a novel landmark-based method to define robust anatomical references for standardizing the delineation of SC segment boundaries for SC-CSA measurements. This approach relies on consecutive spinal nerve midpoints (CNMPs) as anatomical references, providing more precise segment delineation and consistent SC-CSA measurements. We validated the effectiveness and robustness of our method using two public datasets of healthy individuals: the first comprises MRI images from different scanners and centers, and the second offers three different head positions for the cervical SC. Experimental results show an intra-subject mean coefficient of variation across head positions of 4.01 ± 2.89% for the proposed CNMP-based landmarks, compared to 4.46 ± 3.10% for vertebral-based landmarks. This demonstrates that the proposed CNMP method can serve as a reliable reference for reducing the variability of CSA measurements compared to the vertebral levels method. Our findings suggest that this approach could potentially aid in the diagnosis of pathological cohorts.