MRI Patterns and Disability Correlation in Multiple Sclerosis: A Prospective Study from a Tertiary Care Center in Pakistan

Authors

  • Qudsia Shah Department of Radiology, Lady Reading Hospital, Peshawar
  • Heraa Javed Department of Radiology, MMC General Hospital, Peshawar
  • Sajad Ahmed Department of Radiology, Indus Medical College Hospital, Tando Mohammed Khan
  • Muhammad Sharif Department of Pulmonology, Lady Reading Hospital, Peshawar
  • Bareera Zahoor Department of Radiology, Lady Reading Hospital, Peshawar
  • Abdul Qahar Department of Neurology, Lady Reading Hospital, Peshawar – Pakistan

DOI:

https://doi.org/10.36552/pjns.v29i3.1124

Abstract

Objective: To evaluate the magnetic resonance imaging (MRI) characteristics of multiple sclerosis (MS) in a tertiary care setting and determine their correlation with clinical disability using the Expanded Disability Status Scale (EDSS).

Materials and Methods: This prospective observational study was conducted at the Department of Radiology, Lady Reading Hospital, Peshawar, over six months. A total of 84 patients diagnosed with MS as per the 2017 revised McDonald criteria were included. Standardized brain and spinal MRI sequences were analyzed for lesion distribution, contrast enhancement, T1 black holes, and spinal cord involvement. 

Results: The mean age was 33.2 ± 8.7 years; 72.6% were female. The most common lesions were periventricular (90.5%), followed by juxtacortical (65.5%), infratentorial (41.7%), and spinal cord (38%). T1 black holes were present in 33.3% of cases. EDSS > 4 was seen in 34.5% of patients. Significant associations were observed between EDSS > 4 and the presence of T1 black holes (p = 0.005), spinal cord lesions (p = 0.012), and infratentorial lesions (p = 0.030). Logistic regression identified T1 black holes (OR = 3.4), spinal cord lesions (OR= 2.8), and infratentorial lesions (OR = 2.5) as independent predictors of disability.

Conclusion: MRI lesion topography, particularly T1 black holes, spinal cord, and infratentorial involvement, correlates strongly with functional disability in MS. These imaging features can aid in early risk stratification and guide treatment planning in resource-limited settings.

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Published

2025-08-31

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Original Articles