Comparative evaluation of intracranial oligodendroglioma and astrocytoma of similar grades using conventional and T1-weighted DCE-MRI
| Autor: | Abhinav Gupta, Rakesh Gupta, Jitender Saini, Virendra Yadav, Mamta Gupta, Rana Patir, Anup Singh, Sandeep Vaishya, Sunita Ahlawat, Suhail P. Parvaze |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Oligodendroglioma
Astrocytoma 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Statistical significance T1 weighted Medicine Humans Radiology Nuclear Medicine and imaging neoplasms Neuroradiology Retrospective Studies business.industry Brain Neoplasms Glioma medicine.disease Mr imaging Magnetic Resonance Imaging nervous system diseases Cerebral blood flow Neurology (clinical) Cardiology and Cardiovascular Medicine business Nuclear medicine 030217 neurology & neurosurgery Calcification |
| Zdroj: | Neuroradiology. 63(8) |
| ISSN: | 1432-1920 |
| Popis: | This retrospective study was performed on a 3T MRI to determine the unique conventional MR imaging and T1-weighted DCE-MRI features of oligodendroglioma and astrocytoma and investigate the utility of machine learning algorithms in their differentiation. Histologically confirmed, 81 treatment-naive patients were classified into two groups as per WHO 2016 classification: oligodendroglioma (n = 16; grade II, n = 25; grade III) and astrocytoma (n = 10; grade II, n = 30; grade III). The differences in tumor morphology characteristics were evaluated using Z-test. T1-weighted DCE-MRI data were analyzed using an in-house built MATLAB program. The mean 90th percentile of relative cerebral blood flow, relative cerebral blood volume corrected, volume transfer rate from plasma to extracellular extravascular space, and extravascular extracellular space volume values were evaluated using independent Student’s t test. Support vector machine (SVM) classifier was constructed to differentiate two groups across grade II, grade III, and grade II+III based on statistically significant features. Z-test signified only calcification among conventional MR features to categorize oligodendroglioma and astrocytoma across grade III and grade II+III tumors. No statistical significance was found in the perfusion parameters between two groups and its subtypes. SVM trained on calcification also provided moderate accuracy to differentiate oligodendroglioma from astrocytoma. We conclude that conventional MR features except calcification and the quantitative T1-weighted DCE-MRI parameters fail to discriminate between oligodendroglioma and astrocytoma. The SVM could not further aid in their differentiation. The study also suggests that the presence of more than 50% T2-FLAIR mismatch may be considered as a more conclusive sign for differentiation of IDH mutant astrocytoma. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full text from SpringerLink