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<p>Aging is associated with an increased risk of neurodegenerative conditions, including degenerative cervical myelopathy (DCM), a leading cause of neurological disability in older adults. Asymptomatic spinal cord compression (ASCC) represents a potential precursor to DCM, characterized by spinal cord compression in individuals without overt clinical symptoms. Early identification and quantification of ASCC are critical for preventing age-related neurological decline. However, a standardized quantitative definition of ASCC remains lacking. This study aimed to develop a quantitative approach to assess cervical ASCC using high-resolution magnetic resonance imaging (MRI). T2-weighted 3&#xa0;T spine MRI scans from 248 healthy controls (HCs), 53 ASCC individuals, and 55 DCM patients from three datasets conforming to the spine generic protocol were analyzed. An automated pipeline utilizing the Spinal Cord Toolbox was used to compute the maximum spinal cord compression (MSCC) metric at each slice, with peak MSCC serving as a quantitative metric for spinal cord compression. ASCC was identified in 17.6% of participants, predominantly at the C4–C6 spinal levels. While ASCC was observed in younger individuals (median age = 36&#xa0;years), its prevalence increased with age. DCM patients were significantly older (median age = 54&#xa0;years), exhibiting greater peak MSCC (22.4%) than ASCC individuals (13.8%). These findings suggest that spinal cord compression may begin in midlife and progress with aging, potentially contributing to age-related neurological impairments. This study validates an automated MRI-based approach for detecting and quantifying spinal cord compression, enabling large-scale analysis in aging populations. Given that ASCC is more common in older adults, longitudinal studies are necessary to determine its progression and potential conversion to symptomatic DCM. The proposed quantitative method may aid in early detection and monitoring of spinal cord compression, informing clinical decision-making to mitigate neurological decline in aging individuals.</p>

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Quantitative assessment of asymptomatic spinal cord compression using MRI: a multi-center study

  • 期刊论文

  • 发表日期：

    2025年8月15日

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  • Ali F. Khan,
  • Sanaa Hameed,
  • Alaa Baha,
  • Fauziyya Muhammad,
  • Grace Haynes,
  • Amber Dastgir,
  • Suresh K. Gulla,
  • Hakeem J. Shakir,
  • Michael L. Rohan,
  • Yasin Y. Dhaher,
  • Zachary A. Smith

摘要

Aging is associated with an increased risk of neurodegenerative conditions, including degenerative cervical myelopathy (DCM), a leading cause of neurological disability in older adults. Asymptomatic spinal cord compression (ASCC) represents a potential precursor to DCM, characterized by spinal cord compression in individuals without overt clinical symptoms. Early identification and quantification of ASCC are critical for preventing age-related neurological decline. However, a standardized quantitative definition of ASCC remains lacking. This study aimed to develop a quantitative approach to assess cervical ASCC using high-resolution magnetic resonance imaging (MRI). T2-weighted 3 T spine MRI scans from 248 healthy controls (HCs), 53 ASCC individuals, and 55 DCM patients from three datasets conforming to the spine generic protocol were analyzed. An automated pipeline utilizing the Spinal Cord Toolbox was used to compute the maximum spinal cord compression (MSCC) metric at each slice, with peak MSCC serving as a quantitative metric for spinal cord compression. ASCC was identified in 17.6% of participants, predominantly at the C4–C6 spinal levels. While ASCC was observed in younger individuals (median age = 36 years), its prevalence increased with age. DCM patients were significantly older (median age = 54 years), exhibiting greater peak MSCC (22.4%) than ASCC individuals (13.8%). These findings suggest that spinal cord compression may begin in midlife and progress with aging, potentially contributing to age-related neurological impairments. This study validates an automated MRI-based approach for detecting and quantifying spinal cord compression, enabling large-scale analysis in aging populations. Given that ASCC is more common in older adults, longitudinal studies are necessary to determine its progression and potential conversion to symptomatic DCM. The proposed quantitative method may aid in early detection and monitoring of spinal cord compression, informing clinical decision-making to mitigate neurological decline in aging individuals.