Diagnostic yield of the combined Magnetic Resonance Imaging and Magnetic Resonance Spectroscopy to predict malignant brain tumor
- PDF  |
- DOI: https://doi.org/10.15562/bmj.v%25vi%25i.1486  |
- Published: 2020-04-01
Search for the other articles from the author in:
Google Scholar | PubMed | BMJ Journal
Search for the other articles from the author in:
Google Scholar | PubMed | BMJ Journal
Search for the other articles from the author in:
Google Scholar | PubMed | BMJ Journal
Search for the other articles from the author in:
Google Scholar | PubMed | BMJ Journal
Search for the other articles from the author in:
Google Scholar | PubMed | BMJ Journal
Search for the other articles from the author in:
Google Scholar | PubMed | BMJ Journal
Introduction: Brain tumor is a neoplasm originating from various type of intracranial tissue. Histopathology is the gold standard to diagnose brain tumor. However, due to its invasive nature, the biopsy procedure poses a substantial risk. Therefore, advanced imaging, such as conventional Magnetic Resonance Imaging (MRI) and Magnetic Resonance Spectroscopy (MRS), has been widely developed to determine brain tumor type. Conventional MRI has been a routine examination for a suspected brain tumor in Indonesia, and with the utilization of MRS, could theoretically improve the diagnostic yield. This study aims to find diagnostic properties of conventional MRI, Choline/Creatine and Choline/NAA ratio extracted from MRS, and as a combined parameter to differentiate brain tumor type.
Methods: This cross-sectional study involved 52 patients who underwent conventional MRI, MRS, and histopathology examination for a suspected brain tumor. The cut-off from Dean Criteria of conventional MRI, Choline/Creatine and Choline/NAA ratio to classify tumor type was determined from the ROC curve and then the diagnostic parameters were calculated from cross-tabulation. Also, a novel approach was made with logical-mathematical equation (disjunction/ Ë… / “or†and conjunction/ Ë„ / “andâ€) to combined parameter obtained from MRI and MRS to predict histopathological brain tumor type.
Results: Conventional MRI combined with MRS improve diagnostic yield compared to a single parameter with a sensitivity of 87.5%, a specificity of 88.6%, accuracy of 88.5%, PPV of 58.3%, NPV of 97.5%, LR+ of 7.68, dan LR- of 0.1.
Conclusion: Combination of conventional MRI and MRS parameter could improve the diagnostic yield in differentiating the type of brain tumor.