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Response Assessment in Long-Term Glioblastoma Survivors Using a Multiparametric MRI-Based Prediction Model
Laiz Laura de Godoy1, Archith Rajan1, Amir Banihashemi2
1Departments of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA.
Brain Sciences
|February 26, 2025
Summary
Multiparametric MRI accurately distinguishes true progression from pseudoprogression in long-term glioblastoma survivors. This imaging approach aids in assessing treatment response and understanding survival outcomes in these patients.
Area of Science:
- Neuro-oncology
- Radiology
- Oncology
Background:
- Early assessment of glioblastoma treatment response is critical for patient prognosis and survival.
- Differentiating true progression (TP) from pseudoprogression (PsP) is essential for appropriate clinical management.
- Long-term glioblastoma survivors present unique challenges in treatment response evaluation.
Purpose of the Study:
- To differentiate true progression (TP) from pseudoprogression (PsP) in long-term glioblastoma survivors using a multiparametric MRI-based predictive model.
- To identify clinical factors associated with survival outcomes in this patient cohort.
- To validate the predictive model against histopathology and modified RANO criteria.
Main Methods:
- Retrospective analysis of six glioblastoma patients with >5 years overall survival.
- Histopathological analysis and modified RANO criteria were used to classify TP and PsP.
- A multiparametric MRI-based prediction model calculated predictive probabilities (PPs) to define TP (PP ≥ 50%) or PsP (PP < 50%).
Main Results:
- The multiparametric MRI model correctly identified all TP (n=3) and PsP (n=3) cases, showing concordance with histopathology/modified RANO criteria.
- Overall survival ranged from 5.1 to 12.3 years.
- Key clinical factors included MGMT promoter methylation (5/6), female sex, good performance status (KPS ≥ 70), and near-total resection.
Conclusions:
- Multiparametric MRI is a valuable tool for assessing treatment response in long-term glioblastoma survivors.
- The predictive model demonstrates high accuracy in differentiating TP from PsP.
- Clinical factors such as MGMT methylation and surgical resection impact survival in glioblastoma.
