Association of partial T2-FLAIR mismatch sign and isocitrate dehydrogenase mutation in WHO grade 4 gliomas: results from the ReSPOND consortium

DSC-PWI presurgical differentiation of grade 4 astrocytoma and glioblastoma in young adults: rCBV percentile analysis across enhancing and non-enhancing regions

PURPOSE

The presurgical discrimination of IDH-mutant astrocytoma grade 4 from IDH-wildtype glioblastoma is crucial for patient management, especially in younger adults, aiding in prognostic assessment, guiding molecular diagnostics and surgical planning, and identifying candidates for IDH-targeted trials. Despite its potential, the full capabilities of DSC-PWI remain underexplored. This research evaluates the differentiation ability of relative-cerebral-blood-volume (rCBV) percentile values for the enhancing and non-enhancing tumor regions compared to the more commonly used mean or maximum preselected rCBV values.

METHODS

This retrospective study, spanning 2016-2023, included patients under 55 years (age threshold based on World Health Organization recommendations) with grade 4 astrocytic tumors and known IDH status, who underwent presurgical MR with DSC-PWI. Enhancing and non-enhancing regions were 3D-segmented to calculate voxel-level rCBV, deriving mean, maximum, and percentile values. Statistical analyses were conducted using the Mann-Whitney U test and AUC-ROC.

RESULTS

The cohort consisted of 59 patients (mean age 46; 34 male): 11 astrocytoma-4 and 48 glioblastoma. While glioblastoma showed higher rCBV in enhancing regions, the differences were not significant. However, non-enhancing astrocytoma-4 regions displayed notably higher rCBV, particularly in lower percentiles. The 30th rCBV percentile for non-enhancing regions was 0.705 in astrocytoma-4, compared to 0.458 in glioblastoma (p = 0.001, AUC-ROC = 0.811), outperforming standard mean and maximum values.

CONCLUSION

Employing an automated percentile-based approach for rCBV selection enhances differentiation capabilities, with non-enhancing regions providing more insightful data. Elevated rCBV in lower percentiles of non-enhancing astrocytoma-4 is the most distinguishable characteristic and may indicate lowly vascularized infiltrated edema, contrasting with glioblastoma's pure edema.

Clinical and imaging characteristics of supratentorial glioma with IDH2 mutation

PURPOSE

The rarity of IDH2 mutations in supratentorial gliomas has led to gaps in understanding their radiological characteristics, potentially resulting in misdiagnosis based solely on negative IDH1 immunohistochemical staining. We aimed to investigate the clinical and imaging characteristics of IDH2-mutant gliomas.

METHODS

We analyzed imaging data from adult patients with pathologically confirmed diffuse lower-grade gliomas and known IDH1/2 alteration and 1p/19q codeletion statuses obtained from the records of our institute (January 2011 to August 2022, Cohort 1) and The Cancer Imaging Archive (TCIA, Cohort 2). Two radiologists evaluated clinical information and radiological findings using standardized methods. Furthermore, we compared the data for IDH2-mutant and IDH-wildtype gliomas. Multivariate logistic regression was used to identify the predictors of IDH2 mutation status, and receiver operating characteristic curve analysis was employed to assess the predictive performance of the model.

RESULTS

Of the 20 IDH2-mutant supratentorial gliomas, 95% were in the frontal lobes, with 75% classified as oligodendrogliomas. Age and the T2-FLAIR discordance were independent predictors of IDH2 mutations. Receiver operating characteristic curve analysis for the model using age and T2-FLAIR discordance demonstrated a strong potential for discriminating between IDH2-mutant and IDH-wildtype gliomas, with an area under the curve of 0.96 (95% CI, 0.91-0.98, P = .02).

CONCLUSION

A high frequency of oligodendrogliomas with 1p/19q codeletion was observed in IDH2-mutated gliomas. Younger age and the presence of the T2-FLAIR discordance were associated with IDH2 mutations and these findings may help with precise diagnoses and treatment decisions in clinical practice.

Presurgical diagnosis of diffuse gliomas in adults: Post-WHO 2021 practical perspectives from radiologists in neuro-oncology units

The 2021 World Health Organization classification of CNS tumours was greeted with enthusiasm as well as an initial potential overwhelm. However, with time and experience, our understanding of its key aspects has notably improved. Using our collective expertise gained in neuro-oncology units in hospitals in different countries, we have compiled a practical guide for radiologists that clarifies the classification criteria for diffuse gliomas in adults. Its format is clear and concise to facilitate its incorporation into everyday clinical practice. The document includes a historical overview of the classifications and highlights the most important recent additions. It describes the main types in detail with an emphasis on their appearance on imaging. The authors also address the most debated issues in recent years. It will better prepare radiologists to conduct accurate presurgical diagnoses and collaborate effectively in clinical decision making, thus impacting decisions on treatment, prognosis, and overall patient care.

Sub-region based radiomics analysis for prediction of isocitrate dehydrogenase and telomerase reverse transcriptase promoter mutations in diffuse gliomas

AIM

To enhance the prediction of mutation status of isocitrate dehydrogenase (IDH) and telomerase reverse transcriptase (TERT) promoter, which are crucial for glioma prognostication and therapeutic decision-making, via sub-regional radiomics analysis based on multiparametric magnetic resonance imaging (MRI).

MATERIALS AND METHODS

A retrospective study was conducted on 401 participants with adult-type diffuse gliomas. Employing the K-means algorithm, tumours were clustered into two to four subregions. Sub-regional radiomics features were extracted and selected using the Mann-Whitney U-test, Pearson correlation analysis, and least absolute shrinkage and selection operator, forming the basis for predictive models. The performance of model combinations of different sub-regional features and classifiers (including logistic regression, support vector machines, K-nearest neighbour, light gradient boosting machine, and multilayer perceptron) was evaluated using an external test set.

RESULTS

The models demonstrated high predictive performance, with area under the receiver operating characteristic curve (AUC) values ranging from 0.918 to 0.994 in the training set for IDH mutation prediction and from 0.758 to 0.939 for TERT promoter mutation prediction. In the external test sets, the two-cluster radiomics features and the logistic regression model yielded the highest prediction for IDH mutation, resulting in an AUC of 0.905. Additionally, the most effective predictive performance with an AUC of 0.803 was achieved using the four-cluster radiomics features and the support vector machine model, specifically for TERT promoter mutation prediction.

CONCLUSION

The present study underscores the potential of sub-regional radiomics analysis in predicting IDH and TERT promoter mutations in glioma patients. These models have the capacity to refine preoperative glioma diagnosis and contribute to personalised therapeutic interventions for patients.

Patterns of T2-FLAIR discordance across a cohort of adult-type diffuse gliomas and deviations from the classic T2-FLAIR mismatch sign

PURPOSE

T2-FLAIR mismatch serves as a highly specific but insensitive marker for IDH-mutant (IDHm) astrocytoma with potential limitations in real-world application. We aimed to assess the utility of a broader definition of T2-FLAIR discordance across a cohort of adult-type diffuse lower-grade gliomas (LrGG) to see if specific patterns emerge and additionally examine factors determining deviation from the classic T2-FLAIR mismatch sign.

METHODS

Preoperative MRIs of non-enhancing adult-type diffuse LrGGs were reviewed. Relevant demographic, molecular, and MRI data were compared across tumor subgroups.

RESULTS

Eighty cases satisfied the inclusion criteria. Highest discordance prevalence and > 50% T2-FLAIR discordance volume were noted with IDHm astrocytomas (P < 0.001), while < 25% discordance volume was associated with oligodendrogliomas (P = 0.03) and IDH-wildtype (IDHw) LrGG (P = 0.004). "T2-FLAIR matched pattern" was associated with IDHw LrGG (P < 0.001) and small or minimal areas of discordance with oligodendrogliomas (P = 0.03). Sensitivity and specificity of classic mismatch sign for IDHm astrocytoma were 25.7% and 100%, respectively (P = 0.06). Retained ATRX expression and/or non-canonical IDH mutation (n = 10) emerged as a significant factor associated with absence of classic T2-FLAIR mismatch sign in IDHm astrocytomas (100%, P = 0.02) and instead had minimal discordance or matched pattern (40%, P = 0.04).

CONCLUSION

T2-FLAIR discordance patterns in adult-type diffuse LrGGs exist on a diverging but distinct spectrum of classic mismatch to T2-FLAIR matched patterns. Specific molecular markers may play a role in deviations from classic mismatch sign.

Quantification of T2-FLAIR Mismatch in Nonenhancing Diffuse Gliomas Using Digital Subtraction

BACKGROUND AND PURPOSE

The T2-FLAIR mismatch sign on MR imaging is a highly specific imaging biomarker of isocitrate dehydrogenase (IDH)-mutant astrocytomas, which lack 1p/19q codeletion. However, most studies using the T2-FLAIR mismatch sign have used visual assessment. This study quantified the degree of T2-FLAIR mismatch using digital subtraction of fluid-nulled T2-weighted FLAIR images from non-fluid-nulled T2-weighted images in human nonenhancing diffuse gliomas and then used this information to assess improvements in diagnostic performance and investigate subregion characteristics within these lesions.

MATERIALS AND METHODS

Two cohorts of treatment-naïve, nonenhancing gliomas with known IDH and 1p/19q status were studied (n = 71 from The Cancer Imaging Archive (TCIA) and n = 34 in the institutional cohort). 3D volumes of interest corresponding to the tumor were segmented, and digital subtraction maps of T2-weighted MR imaging minus T2-weighted FLAIR MR imaging were used to partition each volume of interest into a T2-FLAIR mismatched subregion (T2-FLAIR mismatch, corresponding to voxels with positive values on the subtraction maps) and nonmismatched subregion (T2-FLAIR nonmismatch corresponding to voxels with negative values on the subtraction maps). Tumor subregion volumes, percentage of T2-FLAIR mismatch volume, and T2-FLAIR nonmismatch subregion thickness were calculated, and 2 radiologists assessed the T2-FLAIR mismatch sign with and without the aid of T2-FLAIR subtraction maps.

RESULTS

Thresholds of ≥42% T2-FLAIR mismatch volume classified IDH-mutant astrocytoma with a specificity/sensitivity of 100%/19.6% (TCIA) and 100%/31.6% (institutional); ≥25% T2-FLAIR mismatch volume showed 92.0%/32.6% and 100%/63.2% specificity/sensitivity, and ≥15% T2-FLAIR mismatch volume showed 88.0%/39.1% and 93.3%/79.0% specificity/sensitivity. In IDH-mutant astrocytomas with ≥15% T2-FLAIR mismatch volume, T2-FLAIR nonmismatch subregion thickness was negatively correlated with the percentage T2-FLAIR mismatch volume (P < .0001) across both cohorts. The percentage T2-FLAIR mismatch volume was higher in grades 3-4 compared with grade 2 IDH-mutant astrocytomas (P < .05), and ≥15% T2-FLAIR mismatch volume IDH-mutant astrocytomas were significantly larger than <15% T2-FLAIR mismatch volume IDH-mutant astrocytoma (P < .05) across both cohorts. When evaluated by 2 radiologists, the additional use of T2-FLAIR subtraction maps did not show a significant difference in interreader agreement, sensitivity, or specificity compared with a separate evaluation of T2-FLAIR and T2-weighted MR imaging alone.

CONCLUSIONS

T2-FLAIR digital subtraction maps may be a useful, automated tool to obtain objective segmentations of tumor subregions based on quantitative thresholds for classifying IDH-mutant astrocytomas using the percentage T2 FLAIR mismatch volume with 100% specificity and exploring T2-FLAIR mismatch/T2-FLAIR nonmismatch subregion characteristics. Conversely, the addition of T2-FLAIR subtraction maps did not enhance the sensitivity or specificity of the visual T2-FLAIR mismatch sign assessment by experienced radiologists.

The T2-FLAIR mismatch sign in oncologic neuroradiology: History, current use, emerging data, and future directions

The T2-Fluid-Attenuated Inversion Recovery (T2-FLAIR) mismatch sign is a radiogenomic marker that is easily discernible on preoperative conventional MR imaging. Application of strict criteria (adult population, cerebral hemisphere location, and classic imaging morphology) permits the noninvasive preoperative diagnosis of isocitrate dehydrogenase (IDH)-mutant 1p/19q-non-codeleted diffuse astrocytoma with near-perfect specificity, albeit with variably low sensitivity. This leads to improved preoperative planning and patient counseling. More recent research has shown that the application of less strict criteria compromises the near-perfect specificity of the sign but remains adequate for ruling out IDH-wildtype (glioblastoma) phenotype, which bears a far grimmer prognosis compared to IDH-mutant diffuse astrocytic disease. In this review, we elaborate on the various definitions of the T2-FLAIR mismatch sign present in the literature, illustrate these with images obtained at a comprehensive cancer center, discuss the potential of the mismatch sign for application to certain pediatric-type brain tumors, namely dysembryoplastic neuroepithelial tumor and diffuse midline glioma, and elaborate upon the clinical, histologic, and molecular associations of the T2-FLAIR mismatch sign as recognized to date. Finally, the sign's correlates in diffusion- and perfusion-weighted imaging are presented, and opportunities to further maximize the diagnostic and prognostic applications of the sign in the context of the 2021 revision of the WHO Classification of Central Nervous System Tumors are discussed.