Forecasting Molecular Features in IDH-Wildtype Gliomas: The State of the Art of Radiomics Applied to Neurosurgery

MRI radiomics model for predicting TERT promoter mutation status in glioblastoma

BACKGROUND AND PURPOSE

The presence of TERT promoter mutations has been associated with worse prognosis and resistance to therapy for patients with glioblastoma (GBM). This study aimed to determine whether the combination model of different feature selections and classification algorithms based on multiparameter MRI can be used to predict TERT subtype in GBM patients.

METHODS

A total of 143 patients were included in our retrospective study, and 2553 features were obtained. The datasets were randomly divided into training and test sets in a ratio of 7:3. The synthetic minority oversampling technique was used to achieve data balance. The Pearson correlation coefficients were used for dimension reduction. Three feature selections and five classification algorithms were used to model the selected features. Finally, 10-fold cross validation was applied to the training dataset.

RESULTS

A model with eight features generated by recursive feature elimination (RFE) and linear discriminant analysis (LDA) showed the greatest diagnostic performance (area under the curve values for the training, validation, and testing sets: 0.983, 0.964, and 0.926, respectively), followed by relief and random forest (RF), analysis of variance and RF. Furthermore, the relief was the optimal feature selection for separately evaluating those five classification algorithms, and RF was the most preferable algorithm for separately assessing the three feature selectors. ADC entropy was the parameter that made the greatest contribution to the discrimination of TERT mutations.

CONCLUSIONS

Radiomics model generated by RFE and LDA mainly based on ADC entropy showed good performance in predicting TERT promoter mutations in GBM.

Supramaximal versus gross total resection in Glioblastoma, IDH wild-type and Astrocytoma, IDH-mutant, grade 4, effect on overall and progression free survival: systematic review and meta-analysis

PURPOSE

To synthesize the evidence on the impact on progression-free survival (PFS) and overall survival (OS) of supramaximal resection (SMR) over gross total resection (GTR) in Glioblastoma, IDH wild-type and Astrocytoma, IDH-mutant, grade 4 (Glioblastoma).

METHODS

The PubMed, Scopus, Web of Science, Ovid and Cochrane databases were systematically searched (up to November 30, 2022). Studies reporting OS and PFS on adult humans with a suspected Glioblastoma, treated either with a SMR or GTR were included. Hazard ratios were estimated for each study and treatment effects were calculated through DerSimonian and Laird random effects models.

RESULTS

The literature search yielded 14 studies published between 2013 and 2022, enrolling a total of 6779 patients. Analysis of the included studies reveals significantly better clinical outcomes favoring SMR over GTR in terms of PFS (HR 0.67; p = 0.0007), and OS (HR 0.7; p = 0.0001).

CONCLUSION

Glioblastoma, IDH wild-type and Astrocytoma, IDH-mutant, grade 4, are aggressive tumors with a very short long-term OS. SMR is an effective therapeutic approach contributing to increased PFS and OS in patients with this catastrophic disease.