RESUMO
CONTEXT: Gliomas are the most common brain tumors. In addition to conventional magnetic resonance imaging (MRI) techniques, a variety of new techniques offers more than the anatomic information. The new MRI techniques include perfusion-weighted imaging (PWI) and diffusion-weighted imaging (DWI). AIMS: The aim of this study is to assess the sensitivity, specificity, predictive value, and accuracy of diffusion- and perfusion-weighted MRI in the preoperative grading of gliomas. SETTING/DESIGN: The study was conducted in the Department of Neurosurgery, Pathology, and Radiodiagnosis, Sher-e-Kashmir Institute of Medical Sciences, Kashmir, India, which is the only tertiary care neurosurgical center in the state. It was a prospective study. PATIENTS AND METHODS: Thirty-one consecutive patients with gliomas were included in the study. All the patients were evaluated by a standard conventional contrast-enhanced study on Siemens 1.5 Tesla MRI. In addition to the standard MRI, diffusion- and perfusion-weighted MRI were also performed. The histopathological grading of the tumor was done as per the WHO classification of 2007. The sensitivity, specificity, predictive value, and accuracy of diffusion- and perfusion-weighted MRI in determining tumor grade were calculated. Comparison was done between PWI, DWI findings, and WHO histopathological grading. ANALYSIS METHOD: The statistical analysis was done using the Statistical Package for the Social Sciences, and receiver operating characteristic curves were used to estimate sensitivity, specificity, and accuracy. RESULTS: The overall sensitivity of PWI (with regional cerebral blood volume cutoff of 1.7) in the preoperative assessment of high-grade gliomas was 82.6% and specificity was 75%, the positive predictive value (PPV) was 90.48%, and the negative predictive value (NPV) was 60%. The overall accuracy was 80.65%. In case of DWI, the sensitivity was 69.57% and the specificity was 75%, and the PPV and NPVs were 88.8% and 46.15%, respectively. The overall accuracy was 71%. CONCLUSION: Our results clearly show higher accuracy of diffusion- and perfusion-weighted MRI in assessment of glioma grade as compared to conventional MRI. This information can prove very useful for the operating neurosurgeon in preoperative assessment and surgical planning. Postoperatively, the neuropathologist can also benefit from such information.
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CONTEXT: Pediatric brain tumors are a vexing problem for the neurosurgeon due to the fragile patient cohort. We attempt to find parameters which can help us to treat and prognosticate these patients in a better way. AIMS: This study aims to correlate clinical presentation, outcome, and histological grade with P53 and Ki-67 expression in primary pediatric brain tumors. SETTING DESIGN: This was a prospective, observational study. PATIENTS AND METHODS: Forty-seven patients with primary brain tumors in the age group 0-18 years were included in this study. Clinical presentation was noted. Patients were operated, and specimen was sent for histopathological and immunohistochemistry examination for p53 and Ki-67. The WHO classification of 2007 was used to grade the tumors. Follow-up was done at 3 and 6 months with Glasgow outcome score. Expression of p53 and Ki-67 in different tumors was correlated with clinical presentation, tumor grade and outcome. ANALYSIS METHOD: Statistical Package for Social Science version 17. P < 0.05 was considered statistically significant. RESULTS: There was statistically significant correlation between high tumor grade and high Ki-67 levels (P = 0.000). On post hoc analysis, there was a significant difference between p53 levels in Grade 1 and Grade 4 tumors. There was statistically significant correlation between neurological deficit and higher p53 levels (P = 0.040). There was statistically significant correlation between poor outcome and higher p53 (P = 0.034) and Ki-67 (P = 0.000) levels at 3 months follow-up which continued at 6 months. CONCLUSIONS: From this study, we conclude that p53 and Ki-67 expression in pediatric brain tumors is associated with poor outcome and correlates with tumor grade. Moreover, p53 expression correlates with neurological deficit.