Value of Apparent Diffusion Coefficient and Relative Cerebral Blood Volume Calculated by MRI for Grading of Brain Tumors | ||||
| The Medical Journal of Cairo University | ||||
| Article 61, Volume 87, December, December 2019, Page 4505-4511 PDF (467.67 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/mjcu.2019.80695 | ||||
 View on SCiNiTO | ||||
| Author | ||||
| ISMAIL M. ABDEL HAKIM, M.Sc.; AHMED TOHAMY AHMED, M.D. | ||||
| The Department of Diagnostic Radiology, Faculty of Medicine, Suez Canal University, Egypt | ||||
| Abstract | ||||
| Abstract Background: MRI is the standard technique for diagnosis of brain tumors, but the challenge is determination of brain tumor grade. Aim of Study: To assess the role of Apparent Diffusion Coefficient (ADC) and relative Cerebral Blood Volume (rCBV) in brain tumors grading. Patients and Methods: Our prospective comparative analytic study involved 26 patients that were diagnosed to have brain tumors. All patients were subjected to revision of their medical history, full neurological and cognitive functions assessment, anatomical brain assessment by conventional MRI examination of the brain, diffusion and perfusion MRI with measurement of mADC & rCBV values respectively. Correlation of results with the histopathological findings of the resected tumors as a gold standard were performed. Results: The diagnostic capability of mADC by using cut off value of <1.28 X 10–3mm2/s had a sensitivity of 81.2%, specificity of 100% at p-value of 0.0001. All the low-grade tumors had low perfusion (rCBV <3.22 & <2.33) while most of the high-grade tumors had high perfusion (rCBV >3.22 & >2.33) with significant difference in between (p=0.001 & 0.002). The diagnostic capability of rCBV by using cut off value of >3.22 & >2.33, had a sensitivity of 68.4%, 90.9 respectively and a specificity of 100% at p-value of <0.00. Multivariant logistic regression revealed that rCBV higher than 2.33 and mADC !91281.34 fitted the statistical regression for prediction of high grade tumors in intra-axial brain tumors (p=0.002). Conclusion: Diffusion and perfusion imaging are useful for characterizing intra-axial brain tumors. rCBV measurement can be used to determine the grade of glioma with no added advantage of ADC map. | ||||
| Keywords | ||||
| Diffusion – Perfusion – MRI – Brain tumor – Glioma | ||||
|
Statistics Article View: 99 PDF Download: 218 |
||||
