Diffusion Tensor Imaging Parameters in Patients with Meningitis: A Case-control Study
Introduction: Neuroimaging plays an important role in the assessment of meningitis, but conventional Magnetic Resonance Imaging (MRI) is insensitive for early and specific diagnosis. Diffusion Tensor Imaging (DTI) can illustrate disturbances in white matter integrity before they become obvious o...
Main Authors: | , , , , , |
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Format: | Article |
Language: | English |
Published: |
JCDR Research and Publications Private Limited
2023-09-01
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Series: | Journal of Clinical and Diagnostic Research |
Subjects: | |
Online Access: | https://www.jcdr.net/articles/PDF/18391/65460_CE[Ra1]_F(KR)_QC(KK_RV_RDW_SS)_PF1(AG_OM)_PFA(AG_KM)_PN(KM).pdf |
Summary: | Introduction: Neuroimaging plays an important role in the
assessment of meningitis, but conventional Magnetic Resonance
Imaging (MRI) is insensitive for early and specific diagnosis.
Diffusion Tensor Imaging (DTI) can illustrate disturbances in white
matter integrity before they become obvious on conventional MRI.
Aim: To determine DTI parameters, specifically Fractional
Anisotropy (FA) and Apparent Diffusion Coefficient (ADC), in
patients with meningitis and compare them with controls.
Materials and Methods: This case-control study was conducted
over a period of 18 months at Teerthanker Mahaveer Medical
College and Research Centre in Moradabad, Uttar Pradesh, India.
The study included a total of 61 clinically diagnosed meningitis
patients, aged 18 years and above, who were referred to the
Department of Radiodiagnosis for an MRI Brain. Additionally,
61 controls were included. Conventional MRI images were
obtained followed by DTI. FA and ADC values were calculated
by placing Regions Of Interest (ROI) at different levels for both
groups. DTI parameters for different causative organisms
(bacterial, viral, tubercular, and fungal) were compared. Data
was analysed using Statistical Package for the Social Sciences
(SPSS) software version 24.0, and Analysis of Variance (ANOVA)
test was used to identify significant differences. The p-value
<0.05 was considered as statistically significant.
Results: FA values were significantly lower in cases compared
to controls at all levels in the brain (mean whole brain FA
value of 0.30±0.036 in cases vs 0.43±0.030 in controls). ADC
values were significantly higher in cases at the cerebellum,
brainstem, and whole brain levels compared to controls
(mean whole brain ADC value of 0.812±0.095 in cases vs
0.758±0.026 in controls) (p-value<0.05 considered statistically
significant). These differences were evident in patients with
clinically proven meningitis who had a normal appearance on
conventional MRI, demonstrating the superiority of DTI over
conventional MRI for the diagnosis of meningitis. Statistically
significant differences were also found among different
aetiological agents, highlighting the potential utility of DTI in
the differential diagnosis of meningitis cases (mean whole
brain FA of 0.31±0.038 in bacterial cases, 0.029±0.037 in
viral cases, 0.299±0.034 in tubercular cases, and 0.27±0.00
in fungal cases vs. 0.43±0.030 in controls (p-value <0.01)
and mean whole brain ADC values of 0.80±0.051 in bacterial,
0.85±0.14 in viral, 0.79±0.058 in tubercular, 1.03±0.00 in fungal
cases vs. 0.758±0.026 in controls (p-value <0.01)).
Conclusion: DTI is more sensitive than conventional MRI and
is a useful early indicator of inflammatory process in patients
with meningitis. |
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ISSN: | 2249-782X 0973-709X |