TB Research

Diagnostic Accuracy of Magnetic Resonance Imaging for Central Nervous System Associated Infectious Diseases

Muhammad Ahmad Raza, Muazzam Tufail, Laamia Altuf, Kinza Chaudhary, Sidra Ghazanfar, Syeda Kiran Aftab Bukhari, Wajiha Sohail Khan

Journal of Health and Rehabilitation Research · 2024-08

Abstract

Background: Central nervous system infections (CNSIs) are a significant cause of morbidity and mortality globally. Accurate diagnosis is crucial for effective management and improved outcomes.Objective: To determine the diagnostic accuracy of magnetic resonance imaging (MRI) for CNS-associated infectious diseases.Methods: A retrospective study was conducted on 95 patients hospitalized with CNSIs at Sheikh Zayed Hospital, Lahore, between December 2022 and January 2024. Diagnoses were confirmed through clinical examination, cerebrospinal fluid analysis, and MRI findings. MRI's diagnostic performance was evaluated for tuberculosis meningitis, viral meningitis, purulent meningitis, and cryptococcal meningitis. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated using SPSS version 25.0.Results: MRI demonstrated varying accuracy for different CNS infections: Tuberculosis Meningitis (sensitivity 55.00%, specificity 47.06%, accuracy 51.28%), Purulent Meningitis (sensitivity 70.00%, specificity 50.00%, accuracy 66.66%), Viral Meningitis (sensitivity 78.57%, specificity 25.00%, accuracy 66.66%), Cryptococcal Meningitis (sensitivity 83.33%, specificity 37.50%, accuracy 69.23%).Conclusion: MRI is a valuable diagnostic tool for CNSIs, particularly for cryptococcal meningitis, but its efficacy varies across different infections, highlighting the need for multimodal diagnostic approaches to enhance accuracy and patient care.

MeSH terms

  • Medicine
  • Viral meningitis
  • Magnetic resonance imaging
  • Meningitis
  • Tuberculous meningitis
  • Diagnostic accuracy
  • Cryptococcal meningitis
  • Medical diagnosis
  • Tuberculosis
  • Retrospective cohort study
  • Predictive value
  • Radiology
  • Internal medicine