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Órgano Oficial de difusión científica de la Asociación Mexicana de Cirujanos de Columna A. C. y de la Sociedad Iberolatinoamericana de Columna. SILACO.

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Scielo

2026, Number 4

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Cir Columna 2026; 4 (4)

A new era in cervical myelopathy: the first microstructural classification impacting early diagnosis, treatment decisionmaking, and an algorithm for therapeutic optimization

Contreras GJ

Language: Spanish
References: 16
Page: 314-319
PDF size: 594.13 Kb.


ABSTRACT

Introduction: cervical spondylosis, one of the leading causes of degenerative cervical myelopathy (DCM), results from spinal canal narrowing secondary to multifactorial degenerative processes. Conventional imaging techniques often fail to detect early microstructural damage, delaying diagnosis and worsening clinical outcomes. Objectives: this study proposes an innovative diagnostic algorithm that integrates diffusion tensor imaging (DTI) and fractional anisotropy (FA) to identify early alterations associated with DCM, with the aim of improving classification, enabling timely intervention, and optimizing treatment outcomes. Material and methods: a literature review was conducted, including etiopathogenic, epidemiological, pathophysiological, diagnostic, and therapeutic aspects of cervical myelopathy across various degrees of stenosis, as well as the incorporation of advanced diffusion MRI techniques into the current diagnostic algorithm. Results: key elements in the gradual progression of cervical myelopathy were identified. The average reported diagnostic delay is 6.3 years, and patients typically require multiple consultations before receiving a definitive diagnosis. The literature highlights that fractional anisotropy enables more sensitive detection of spinal cord microstructural damage. Based on this evidence, previous cervical stenosis classifications were unified into a single system incorporating FA values, providing a more accurate representation of the degree of medullary involvement. Additionally, a revised diagnostic algorithm was proposed, integrating this classification to improve early detection and clinical decision-making. Conclusions: early recognition of microstructural damage is essential for optimizing the management of DCM. The adoption of an updated diagnostic algorithm and a diffusion-based adapted classification represents a crucial step toward the effective integration of these concepts into clinical practice.


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