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Purpose <p>Imaging modalities, particularly magnetic resonance imaging (MRI), have become the gold standard for assessing lesion characteristics of traumatic spinal cord injuries (SCI). Diffusion tensor imaging (DTI), an advanced MRI technique, offers insights into microstructural changes in white matter tracts. While previous studies focused on either acute or chronic SCI, few have examined longitudinal changes during the transition from acute to chronic stages of injury. This study addresses this gap by analyzing the evolution of DTI metrics over the first year following cervical SCI.</p> Methods <p>This prospective longitudinal study involved 52&#xa0;patients with traumatic cervical SCI. MRI and neurological examinations using the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) were performed 1&#xa0;month, 3&#xa0;months, and 1&#xa0;year post-injury. Linear mixed model analyses assessed DTI measures over time.</p> Results <p>Fractional anisotropy (FA) values gradually decreased in the reference area at the cranio-cervical junction (C0–C4; <i>p</i> &lt; 0.001), indicating ongoing tissue degeneration up to one year after injury, independent of initial clinical severity. FA values at the lesion site correlated moderately with the total motor score&#xa0;1&#xa0;month post-SCI (R = 0.37, <i>p</i> = 0.033). Mean diffusivity (MD) increased significantly over time (<i>p</i> &lt; 0.001), suggesting progressive microstructural changes. Axial diffusivity (AD) decreased until 3&#xa0;months after injury (<i>p</i> &lt; 0.001), then returned to its initial values by 1&#xa0;year, reflecting dynamic pathophysiological events.</p> Conclusion <p>This study highlights the potential of DTI for monitoring microstructural changes after SCI. Longitudinal imaging offers insights into evolving pathology, supports prognostic modeling, and may aid treatment monitoring and outcome prediction.</p> Graphic abstract <p></p>

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Evolution of MRI Parameters from the Subacute to Chronic Phase After Human Traumatic Cervical Spinal Cord Injury: a Prospective, Observational Study. Part 2: Diffusion Tensor Imaging Characteristics.

  • 期刊论文

  • 发表日期：

    2025年10月24日

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  • Andreas Grillhösl,
  • Iris Leister,
  • Florian Högel,
  • Ludwig Sanktjohanser,
  • Matthias Vogel,
  • Orpheus Mach,
  • Doris Maier,
  • Lukas Grassner

摘要

Purpose

Imaging modalities, particularly magnetic resonance imaging (MRI), have become the gold standard for assessing lesion characteristics of traumatic spinal cord injuries (SCI). Diffusion tensor imaging (DTI), an advanced MRI technique, offers insights into microstructural changes in white matter tracts. While previous studies focused on either acute or chronic SCI, few have examined longitudinal changes during the transition from acute to chronic stages of injury. This study addresses this gap by analyzing the evolution of DTI metrics over the first year following cervical SCI.

Methods

This prospective longitudinal study involved 52 patients with traumatic cervical SCI. MRI and neurological examinations using the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) were performed 1 month, 3 months, and 1 year post-injury. Linear mixed model analyses assessed DTI measures over time.

Results

Fractional anisotropy (FA) values gradually decreased in the reference area at the cranio-cervical junction (C0–C4; p < 0.001), indicating ongoing tissue degeneration up to one year after injury, independent of initial clinical severity. FA values at the lesion site correlated moderately with the total motor score 1 month post-SCI (R = 0.37, p = 0.033). Mean diffusivity (MD) increased significantly over time (p < 0.001), suggesting progressive microstructural changes. Axial diffusivity (AD) decreased until 3 months after injury (p < 0.001), then returned to its initial values by 1 year, reflecting dynamic pathophysiological events.

Conclusion

This study highlights the potential of DTI for monitoring microstructural changes after SCI. Longitudinal imaging offers insights into evolving pathology, supports prognostic modeling, and may aid treatment monitoring and outcome prediction.

Graphic abstract