IDH-mutant grade 4 astrocytoma: a comparison integrating the clinical, pathological, and survival features between primary and secondary patients

OBJECTIVE

IDH-mutant grade 4 astrocytomas (AIDHmut/G4) are divided into primary de novo (pAIDHmut/G4) and secondary with a history of prior lower-grade gliomas (LGGs; sAIDHmut/G4). The mutational spectrum and DNA methylation patterns are homogeneous within de novo pAIDHmut/G4 and evolved sAIDHmut/G4, but the two groups have different diagnoses, management, and outcomes. This study sought to systematically compare the clinical, pathological, and survival characteristics between them.

METHODS

Of the 871 grade 4 astrocytomas with data for IDH mutation, 698 (80.1%) were primary and 173 (19.9%) were secondary. Of the 698 primary tumors, 103 (14.8%) were pAIDHmut/G4, and of the 173 secondary tumors, 108 (62.4%) were sAIDHmut/G4. Clinical, pathological, and survival features were compared between pAIDHmut/G4 and sAIDHmut/G4. Multivariate analyses were performed to identify prognostic factors.

RESULTS

Patients with sAIDHmut/G4 had significantly shorter median overall survival (OS; 11.8 vs 34.2 months, hazard ratio [HR] 2.69, 95% confidence interval [CI] 1.367-5.306, p = 0.004) and progression-free survival (PFS; 8.5 vs 24.3 months, HR 2.83, 95% CI 1.532-5.235, p = 0.001) than patients with pAIDHmut/G4. In patients with sAIDHmut/G4, resection status and chemotherapy were independent prognostic factors for OS and PFS; in patients with pAIDHmut/G4, LGG component, resection status, and O6-methylguanine DNA methyltransferase promoter methylation were independent prognostic factors. The therapeutic strategies of LGGs did not influence survival of patients with sAIDHmut/G4, but patients who had not received radiotherapy or chemotherapy when they were diagnosed with LGGs were found to benefit from radiotherapy or chemotherapy when they progressed to sAIDHmut/G4.

CONCLUSIONS

The different clinical characteristics, survival, and risk factors between sAIDHmut/G4 and pAIDHmut/G4 provide a reference to guide treatment decisions in AIDHmut/G4.

MRI-Based Radiomics Combined with Deep Learning for Distinguishing IDH-Mutant WHO Grade 4 Astrocytomas from IDH-Wild-Type Glioblastomas

This study aimed to investigate the potential of quantitative radiomic data extracted from conventional MR images in discriminating IDH-mutant grade 4 astrocytomas from IDH-wild-type glioblastomas (GBMs). A cohort of 57 treatment-naïve patients with IDH-mutant grade 4 astrocytomas (n = 23) and IDH-wild-type GBMs (n = 34) underwent anatomical imaging on a 3T MR system with standard parameters. Post-contrast T1-weighted and T2-FLAIR images were co-registered. A semi-automatic segmentation approach was used to generate regions of interest (ROIs) from different tissue components of neoplasms. A total of 1050 radiomic features were extracted from each image. The data were split randomly into training and testing sets. A deep learning-based data augmentation method (CTGAN) was implemented to synthesize 200 datasets from the training sets. A total of 18 classifiers were used to distinguish two genotypes of grade 4 astrocytomas. From generated data using 80% training set, the best discriminatory power was obtained from core tumor regions overlaid on post-contrast T1 using the K-best feature selection algorithm and a Gaussian naïve Bayes classifier (AUC = 0.93, accuracy = 0.92, sensitivity = 1, specificity = 0.86, PR_AUC = 0.92). Similarly, high diagnostic performances were obtained from original and generated data using 50% and 30% training sets. Our findings suggest that conventional MR imaging-based radiomic features combined with machine/deep learning methods may be valuable in discriminating IDH-mutant grade 4 astrocytomas from IDH-wild-type GBMs.

GammaTile Brachytherapy Combined With External Beam Radiation Therapy for the Treatment of a Partially Resected Secondary Glioblastoma (WHO Grade 4 IDH-Mutant Astrocytoma): Matching External Beam Dose Gradient to Brachytherapy Dose Fall-Off

Reirradiation of recurrent glioblastomas is most commonly managed with hypofractionated external beam radiation with a modest overall effect. GammaTile, which is a Cesium-131 source embedded in collagen mesh, is an approach that allows the surgical bed of resectable intracranial tumors to receive a greater biological dose than is possible with any form of external beam radiation therapy (EBRT). In this case report, a 28-year-old male presents with a WHO grade 4 isocitrate dehydrogenase (IDH)-mutant astrocytoma (formerly secondary glioblastoma) of the left occipital/parietal lobe after receiving 45 Gy and two cycles of adjuvant temozolomide four years prior for a grade 3 IDH-mutant astrocytoma. The patient proceeded to undergo craniotomy with maximal safe resection and application of GammaTile to a dose of 60 Gy at 5mm depth. Shortly afterward, he developed symptomatic progression of disease in the bilateral splenium and left thalamus/basal ganglia. We irradiated the undertreated residual disease with EBRT to a dose of 35 Gy in 10 fractions without introducing excessive dose to the GammaTile irradiated volume. This was achieved by creating one portion of the planning target volume with a homogeneous dose and another part where the delivered dose decreased with the GammaTile dose buildup. Treatment planning utilized the Gradient Optimization feathering technique with non-coplanar volumetric modulated arc therapy. The resulting composite between the hypofractionated EBRT and GammaTile dose distribution created an approximate dose equivalent of 50 Gy in 2 Gy fractions to the residual disease with no hot spots or areas of under coverage. This is the first report showing the feasibility of combining GammaTile with dose-matched EBRT volumes in a reproducible manner to sub-totally resected, recurrent intracranial neoplasms.