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Correlation between dynamic susceptibility contrast perfusion MRI and genomic alterations in glioblastoma
Kerem Ozturk1, Esra Soylu1, Zuzan Cayci2
1Department of Radiology, University of Minnesota Health, B-226 Mayo Memorial Building, MMC 292, 420 Delaware Street S.E., Minneapolis, MN, 55455, USA.
Purpose:
To determine if dynamic susceptibility contrast perfusion MR imaging (DSC-pMRI) can predict significant genomic alterations in glioblastoma (GB).
Methods:
A total of 47 patients with treatment-naive GB (M/F: 23/24, mean age: 54 years, age range: 20-90 years) having DSC-pMRI with leakage correction and genomic analysis were reviewed. Mean relative cerebral blood volume (rCBV), maximum rCBV, relative percent signal recovery (rPSR), and relative peak height (rPH) were derived from T2* signal intensity-time curves by ROI analysis. Major genomic alterations of IDH1-132H, MGMT, p53, EGFR, ATRX, and PTEN status were correlated with DSC-pMRI-derived GB parameters. Statistical analysis was performed utilizing the independent-samples t-test, ROC (receiver operating characteristic) curve analysis, and multivariable stepwise regression model.
Results:
rCBVmean and rCBVmax were significantly different in relation to the IDH1, MGMT, p53, and PTEN mutation status (all p < 0.05). The rPH of the p53 mutation-positive GBs (mean 5.8 ± 2.8) was significantly higher than those of the p53 mutation-negative GBs (mean 4.0 ± 1.5) (p = 0.022). Multivariable stepwise regression analysis revealed that the presence of IDH-1 mutation (B = - 2.81, p = 0.005) was associated with decreased rCBVmean; PTEN mutation (B = - 1.21, p = 0.003) and MGMT methylation (B = - 1.47, p = 0.038) were associated with decreased rCBVmax; and ATRX loss (B = - 1.05, p = 0.008) was associated with decreased rPH.
Conclusion:
Significant associations were identified between DSC-pMRI-derived parameters and major genomic alterations, including IDH-1 mutation, MGMT methylation, ATRX loss, and PTEN mutation status in GB.
Insights
Dynamic susceptibility contrast perfusion MR imaging (DSC-pMRI) can predict key genomic alterations in glioblastoma (GB). Perfusion parameters correlate with IDH-1 mutation, MGMT methylation, ATRX loss, and PTEN mutation status, aiding in non-invasive tumor profiling.
Area of Science:
- Neuroimaging
- Oncology
- Genomics
Background:
- Glioblastoma (GB) is an aggressive brain tumor with significant genomic heterogeneity.
- Accurate non-invasive prediction of these genomic alterations is crucial for personalized treatment strategies.
- Dynamic susceptibility contrast perfusion MR imaging (DSC-pMRI) offers insights into tumor vascularity.
Purpose of the Study:
- To investigate the potential of DSC-pMRI parameters in predicting significant genomic alterations in treatment-naive glioblastoma.
- To correlate quantitative perfusion metrics with specific genetic mutations and epigenetic modifications.
Main Methods:
- Retrospective analysis of 47 treatment-naive glioblastoma patients undergoing DSC-pMRI and genomic analysis.
- Derivation of perfusion parameters including relative cerebral blood volume (rCBV) and relative peak height (rPH).
- Statistical correlation of DSC-pMRI metrics with IDH1, MGMT, p53, EGFR, ATRX, and PTEN genomic status using t-tests, ROC analysis, and regression models.
Main Results:
- Significant differences in rCBVmean and rCBVmax were observed in relation to IDH1, MGMT, p53, and PTEN mutations (p < 0.05).
- Higher rPH was noted in p53 mutation-positive GBs compared to negative ones (p = 0.022).
- Multivariable regression identified associations between IDH-1 mutation, PTEN mutation, MGMT methylation, and ATRX loss with decreased rCBVmean, rCBVmax, and rPH.
Conclusions:
- DSC-pMRI-derived parameters demonstrate significant associations with key genomic alterations in glioblastoma.
- Perfusion imaging may serve as a valuable non-invasive tool for inferring genomic profiles of glioblastoma.
- These findings support the integration of DSC-pMRI into routine glioblastoma assessment for personalized medicine.
