Memoona Mushtaq, Sadaf Arooj, Maria Khaliq, Riffat Raja, Seerat Iqbal.
Assessment of Diagnostic Accuracy of MRI in Diagnosing and Characterizing Intra-axial Brain Gliomas.
Pak J Med Res Jan ;60(4):189-93.

Background: Magnetic Resonance Imaging (MRI) has emerged as most prevailing noninvasive radiological modality for the diagnosis of brain tumor, its prognosis, therapeutic assessment, observation of progression or regression of disease and planning of neurosurgical approaches. Objective: To assess the diagnostic accuracy of MRI in diagnosing and characterizing intra-axial brain gliomas taking histopathology as a gold standard. Study type, settings & duration: This prospective research was conducted in the Department of Radiology at Jinnah Hospital, Lahore from March 2016 to August 2016.Methodology:Two hundred patients with space occupying lesions diagnosed on CT scan of age 3 months to 65 years of either gender were included. Pregnant women and contraindication to MRI were omitted. The MRI of all other patients using 1.5 Tesla MR System with a gradient strength of 33 mT/m was performed. MRI study was interpreted by assessing the features favoring malignancy or benignity of gliomas. MRI findings were compared with the histopathology reports. Results :Mean age was 44.41+-7.52 years. Among these 200 patients, 113 (56.50%) were male patients and 87 (43.50%) were female patients making male to female ratio of 1.2:1. In MRI positive patients, 89 were found to be true positive patients while 23 were found to be false positive patients. Among 88 MRI negative patients, 74 were true negative (p=0.367) whereas 14 came out to be False Negative. Overall sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy of MRI in diagnosing malignant cerebral glioma were 86.41%,76.29%, 79.46%, 84.09% and 81.50% respectively. Conclusion: This study demonstrated that MRI is the non-invasive imaging modality of choice with high diagnostic accuracy in diagnosing malignant cerebral gliomas, and has not only radically improved our ability of distinguishing benign and malignant brain tumor pre-operatively but also aids the surgeons for appropriate decision-making.

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