Noninvasive assessment of H3 K27M mutational status in diffuse midline gliomas by using apparent diffusion coefficient measurements

MRI-Based Score to Recognize Thalamic Glioma Grade in Children: Morphology, Diffusion, and Arterial-Spin-Labeling Perfusion

PURPOSE

Thalamic gliomas are found predominantly in children and can be classified into two main types with different prognoses and management: diffuse midline glioma (DMG) H3K27-altered and low-grade glioma (LGG). Our aim was to find imaging features distinguishing these tumors and to develop a diagnostic score.

PATIENTS AND METHODS

A retrospective study spanning September 1999 to May 2021 involved pediatric patients with thalamic gliomas, categorized into H3K27-altered DMG and LGG groups. Preoperative imaging, including morphology, diffusion, and arterial-spin-labeling perfusion, was reviewed blindly and compared between the two groups. A diagnostic score was formulated based on significant findings. Results were validated using an internal and external validation cohort.

RESULTS

Sixty-six patients were included (median age, 9 years; interquartile range [IQR] [5-13]; 38 girls) with 37 DMG H3K27-altered and 29 LGG. DMG H3K27-altered tumors exhibited larger volumes (median 64 cc, IQR [36-88] vs 26 cc, IQR [15-37], p < 0.001), greater heterogeneity in T2-weighted signal and enhancement (62% [22/37] vs 31% [9/29], p = 0.04, and 97% [32/33] vs 56% [15/27], p = 0.0008, respectively), lower minimum relative apparent diffusion coefficient (ADC) (0.92 (IQR [0.76-1.23]) vs 1.55 (IQR [1.40-1.72]), p < 0.001), and higher relative maximum cerebral blood flow (CBF) levels (2.08 (IQR [1.48-3.05]) vs 0.84 (IQR [0.45-1]), p < 0.001). A diagnostic score integrating tumor diameter, solid content predominance, relative ADC, and relative CBF achieved 100% sensitivity and specificity in distinguishing DMG H3K27-altered tumors from LGG (full score available for 36 patients), with good results in external and internal validation cohorts (12 patients).

CONCLUSION

The morphological, diffusion, and arterial spin labeling imaging characteristics of pediatric thalamic tumors enable excellent differentiation of DMG H3K27-altered and LGG.

Advanced imaging techniques and non-invasive biomarkers in pediatric brain tumors: state of the art

In the pediatric age group, brain neoplasms are the second most common tumor category after leukemia, with an annual incidence of 6.13 per 100,000. Conventional MRI sequences, complemented by CT whenever necessary, are fundamental for the initial diagnosis and surgical planning as well as for post-operative evaluations, assessment of response to treatment, and surveillance; however, they have limitations, especially concerning histopathologic or biomolecular phenotyping and grading. In recent years, several advanced MRI sequences, including diffusion-weighted imaging, diffusion tensor imaging, arterial spin labelling (ASL) perfusion, and MR spectroscopy, have emerged as a powerful aid to diagnosis as well as prognostication; furthermore, other techniques such as diffusion kurtosis, amide proton transfer imaging, and MR elastography are being translated from the research environment to clinical practice. Molecular imaging, especially PET with amino-acid tracers, complement MRI in several aspects, including biopsy targeting and outcome prediction. Finally, radiomics with radiogenomics are opening entirely new perspectives for a quantitative approach aiming at identifying biomarkers that can be used for personalized, precision management strategies.

Identification of prognostic imaging biomarkers in H3 K27-altered diffuse midline gliomas in adults: impact of tumor oxygenation imaging biomarkers on survival

PURPOSE

To investigate prognostic markers for H3 K27-altered diffuse midline gliomas (DMGs) in adults with clinical, qualitative and quantitative imaging phenotypes, including tumor oxygenation characteristics.

METHODS

Retrospective chart and imaging reviews were conducted on 32 adults with H3 K27-altered DMGs between 2017 and 2023. Clinical and qualitative imaging characteristics were analyzed. Quantitative imaging assessment was performed from the tumor mask via automatic segmentation to calculate normalized cerebral blood volume (nCBV), capillary transit time heterogeneity (CTH), oxygen extraction fraction (OEF), relative cerebral metabolic rate of oxygen (rCMRO2), and mean ADC values. Leptomeningeal metastases (LM) was diagnosed with imaging. Cox analyses were conducted to determine predictors of overall survival (OS) in entire patients and a subgroup of patients with contrast-enhancing (CE) tumor.

RESULTS

The median patient age was 40.5 years (range 19.9-75.7), with an OS of 30.3 months (interquartile range 11.3-32.3). In entire patients, the presence of LM was the only independent predictor of OS (hazard ratio [HR] = 6.01, P = 0.009). In the subgroup of 23 (71.9%) patients with CE tumors, rCMRO2 of CE tumor (HR = 1.08, P = 0.019) and the presence of LM (HR = 5.92, P = 0.043) were independent predictors of OS.

CONCLUSION

The presence of LM was independently associated with poor prognosis in adult patients with H3 K27-altered DMG. In patients with CE tumors, higher rCMRO2 of CE tumor, which may reflect higher metabolic activity in the tumor oxygenation microenvironment, may be a useful imaging biomarker to predict poor prognosis.

Noninvasive prediction of BRAF V600E mutation status of pleomorphic xanthoastrocytomas with MRI morphologic features and diffusion-weighted imaging

OBJECTIVES

Seeking a noninvasive predictor for BRAF V600E mutation status of pleomorphic xanthoastrocytomas (PXAs) is essential for their prognoses and therapeutic use of BRAF inhibitors. We aimed to noninvasively diagnose BRAF V600E-mutated PXAs using MRI morphologic, DWI and clinical parameters.

METHODS

The clinical findings, anatomical MRI characteristics, and diffusion parameters of 36 pathologically confirmed PXAs were retrospectively analyzed, and BRAF V600E-mutated (n = 16) and wild-type (n = 20) groups were compared. A binary logistic-regression analysis was performed, and a ROC curve was calculated to determine the independent predictors of BRAF V600E mutation status, diagnostic accuracy, and optimal cut-off value.

RESULTS

A comparison of findings between groups showed that BRAF V600E-mutated PXAs were more frequent in children and young adults (≤ 35 years; P = 0.042) who often had histories of seizures (P = 0.004). Furthermore, BRAF V600E-mutated PXAs generally presented as solitary masses (P = 0.024), superficial locations with meningeal attachment (P < 0.001), predominantly cystic with mural nodules (P = 0.005), and had greater minimal ADC ratio (ADCratio) values of the tumor and peritumoral edema (P < 0.001). Binary logistic regression showed that age ≤ 35 years, solitary mass, superficial locations with meningeal attachment, and a greater minimal ADCratio of the tumor were independent predictors of BRAF V600E-mutated PXAs. The combination of all four independent predictors resulted in the highest sensitivity (100%) and specificity (90%), with AUC = 0.984.

CONCLUSION

The BRAF V600E mutation status of PXAs could be noninvasively predicted using clinical and MRI characteristics.

CRITICAL RELEVANCE STATEMENT

The noninvasive diagnostic criteria for BRAF V600E-mutated PXAs could offer guidance for the administration of BRAF V600E mutation inhibitors in the future.

Molecular and Pathological Features of Paediatric High-Grade Gliomas

Paediatric high-grade gliomas are among the most common malignancies found in children. Despite morphological similarities to their adult counterparts, there are profound biological and molecular differences. Furthermore, and thanks to molecular biology, the diagnostic pathology of paediatric high-grade gliomas has experimented a dramatic shift towards molecular classification, with important prognostic implications, as is appropriately reflected in both the current WHO Classification of Tumours of the Central Nervous System and the WHO Classification of Paediatric Tumours. Emphasis is placed on histone 3, IDH1, and IDH2 alterations, and on Receptor of Tyrosine Kinase fusions. In this review we present the current diagnostic categories from the diagnostic pathology perspective including molecular features.

Clinical, qualitative imaging biomarkers, and tumor oxygenation imaging biomarkers for differentiation of midline-located IDH wild-type glioblastomas and H3 K27-altered diffuse midline gliomas in adults

PURPOSE

To compare the clinical, qualitative and quantitative imaging phenotypes, including tumor oxygenation characteristics of midline-located IDH-wildtype glioblastomas (GBMs) and H3 K27-altered diffuse midline gliomas (DMGs) in adults.

METHODS

Preoperative MRI data of 55 adult patients with midline-located IDH-wildtype GBM or H3 K27-altered DMG (32 IDH-wildtype GBM and 23 H3 K27-altered DMG patients) were included. Qualitative imaging assessment was performed. Quantitative imaging assessment including the tumor volume, normalized cerebral blood volume, capillary transit time heterogeneity (CTH), oxygen extraction fraction (OEF), relative cerebral metabolic rate of oxygen values, and mean ADC value were performed from the tumor mask via automatic segmentation. Univariable and multivariable logistic analyses were performed.

RESULTS

On multivariable analysis, age (odds ratio [OR] = 0.92, P = 0.015), thalamus or medulla location (OR = 10.48, P = 0.013), presence of necrosis (OR = 0.15, P = 0.038), and OEF (OR = 0.01, P = 0.042) were independent predictors to differentiate H3 K27-altered DMG from midline-located IDH-wildtype GBM. The area under the curve, accuracy, sensitivity, and specificity of the multivariable model were 0.88 (95 % confidence interval: 0.77-0.95), 81.8 %, 82.6 %, and 81.3 %, respectively.

CONCLUSIONS

Along with younger age, tumor location, less frequent necrosis, and lower OEF may be useful imaging biomarkers to differentiate H3 K27-altered DMG from midline-located IDH-wildtype GBM. Tumor oxygenation imaging biomarkers may reflect the less hypoxic nature of H3 K27-altered DMG than IDH-wildtype GBM and may contribute to differentiation.

Prediction of H3K27M alteration in midline gliomas of the brain using radiomics: A multi-institute study

Background

Noninvasive prediction of H3K27M-altered Diffuse midline gliomas is important because of the involvement of deep locations and proximity to eloquent structures. We aim to predict H3K27M alteration in midline gliomas using radiomics features of T2W images.

Methods

Radiomics features extracted from 124 subjects (69 H3K27M-altered/55 H3K27M-wild type). T2W images were resampled to 1 × 1 × 1mm3 voxel size, preprocessed, and normalized for artifact correction, intensity variations. The feature set was normalized and subjected to reduction by variance thresholding, correlation coefficient thresholding, and sequential feature selector. Adaptive synthesis oversampling technique was used to oversample the training data. Random forest classifier (RFC), Decision tree classifier (DTC), and K-nearest neighbors classifier (KNN) were trained over the training dataset and the performance was assessed over the internal test dataset and external test data set (52 subjects: 33 H3K27M-altered/19-H3K27M-wild type).

Results

DTC achieved a validation score of 77.33% (5-fold cross-validation) and an accuracy of 80.64%, 75% on internal and external test datasets. RFC achieved a validation score of 80.7% (5-fold cross-validation) an accuracy of 80.6%, and 73% on internal and external test datasets. DTC achieved a validation score of 78.67% (5-fold cross-validation) an accuracy of 80.64%, and 61.53% on internal and external test datasets. The accuracy score of DTC, RFC, and KNN on the internal test dataset was approximately 80% while on the external test dataset, DTC achieved 75% accuracy, RFC achieved 73% accuracy and KNN achieved 65.1% accuracy.

Conclusions

H3K27M alteration is a potential immunotherapeutic marker and is associated with poor prognosis and radiomics features extracted from conventional T2W-images can help in identifying H3K27M-altered cases non-invasively with high precision.

Radiomic Features Based on MRI Predict Progression-Free Survival in Pediatric Diffuse Midline Glioma/Diffuse Intrinsic Pontine Glioma

Purpose: Biopsy-based assessment of H3 K27 M status helps in predicting survival, but biopsy is usually limited to unusual presentations and clinical trials. We aimed to evaluate whether radiomics can serve as prognostic marker to stratify diffuse intrinsic pontine glioma (DIPG) subsets. Methods: In this retrospective study, diagnostic brain MRIs of children with DIPG were analyzed. Radiomic features were extracted from tumor segmentations and data were split into training/testing sets (80:20). A conditional survival forest model was applied to predict progression-free survival (PFS) using training data. The trained model was validated on the test data, and concordances were calculated for PFS. Experiments were repeated 100 times using randomized versions of the respective percentage of the training/test data. Results: A total of 89 patients were identified (48 females, 53.9%). Median age at time of diagnosis was 6.64 years (range: 1-16.9 years) and median PFS was 8 months (range: 1-84 months). Molecular data were available for 26 patients (29.2%) (1 wild type, 3 K27M-H3.1, 22 K27M-H3.3). Radiomic features of FLAIR and nonenhanced T1-weighted sequences were predictive of PFS. The best FLAIR radiomics model yielded a concordance of .87 [95% CI: .86-.88] at 4 months PFS. The best T1-weighted radiomics model yielded a concordance of .82 [95% CI: .8-.84] at 4 months PFS. The best combined FLAIR + T1-weighted radiomics model yielded a concordance of .74 [95% CI: .71-.77] at 3 months PFS. The predominant predictive radiomic feature matrix was gray-level size-zone. Conclusion: MRI-based radiomics may predict progression-free survival in pediatric diffuse midline glioma/diffuse intrinsic pontine glioma.

Multimodal MRI radiomic models to predict genomic mutations in diffuse intrinsic pontine glioma with missing imaging modalities

Purpose

Predicting H3.1, TP53, and ACVR1 mutations in DIPG could aid in the selection of therapeutic options. The contribution of clinical data and multi-modal MRI were studied for these three predictive tasks. To keep the maximum number of subjects, which is essential for a rare disease, missing data were considered. A multi-modal model was proposed, collecting all available data for each patient, without performing any imputation.

Methods

A retrospective cohort of 80 patients with confirmed DIPG and at least one of the four MR modalities (T1w, T1c, T2w, and FLAIR), acquired with two different MR scanners was built. A pipeline including standardization of MR data and extraction of radiomic features within the tumor was applied. The values of radiomic features between the two MR scanners were realigned using the ComBat method. For each prediction task, the most robust features were selected based on a recursive feature elimination with cross-validation. Five different models, one based on clinical data and one per MR modality, were developed using logistic regression classifiers. The prediction of the multi-modal model was defined as the average of all possible prediction results among five for each patient. The performances of the models were compared using a leave-one-out approach.

Results

The percentage of missing modalities ranged from 6 to 11% across modalities and tasks. The performance of each individual model was dependent on each specific task, with an AUC of the ROC curve ranging from 0.63 to 0.80. The multi-modal model outperformed the clinical model for each prediction tasks, thus demonstrating the added value of MRI. Furthermore, regardless of performance criteria, the multi-modal model came in the first place or second place (very close to first). In the leave-one-out approach, the prediction of H3.1 (resp. ACVR1 and TP53) mutations achieved a balanced accuracy of 87.8% (resp. 82.1 and 78.3%).

Conclusion

Compared with a single modality approach, the multi-modal model combining multiple MRI modalities and clinical features was the most powerful to predict H3.1, ACVR1, and TP53 mutations and provided prediction, even in the case of missing modality. It could be proposed in the absence of a conclusive biopsy.

Imaging features associated with H3 K27-altered and H3 G34-mutant gliomas: a narrative systematic review

Background

Advances in molecular diagnostics accomplished the discovery of two malignant glioma entities harboring alterations in the H3 histone: diffuse midline glioma, H3 K27-altered and diffuse hemispheric glioma, H3 G34-mutant. Radiogenomics research, which aims to correlate tumor imaging features with genotypes, has not comprehensively examined histone-altered gliomas (HAG). The aim of this research was to synthesize the current published data on imaging features associated with HAG.

Methods

A systematic search was performed in March 2022 using PubMed and the Cochrane Library, identifying studies on the imaging features associated with H3 K27-altered and/or H3 G34-mutant gliomas.

Results

Forty-seven studies fulfilled the inclusion criteria, the majority on H3 K27-altered gliomas. Just under half (21/47) were case reports or short series, the remainder being diagnostic accuracy studies. Despite heterogeneous methodology, some themes emerged. In particular, enhancement of H3 K27M-altered gliomas is variable and can be less than expected given their highly malignant behavior. Low apparent diffusion coefficient values have been suggested as a biomarker of H3 K27-alteration, but high values do not exclude this genotype. Promising correlations between high relative cerebral blood volume values and H3 K27-alteration require further validation. Limited data on H3 G34-mutant gliomas suggest some morphologic overlap with 1p/19q-codeleted oligodendrogliomas.

Conclusions

The existing data are limited, especially for H3 G34-mutant gliomas and artificial intelligence techniques. Current evidence indicates that imaging-based predictions of HAG are insufficient to replace histological assessment. In particular, H3 K27-altered gliomas should be considered when occurring in typical midline locations irrespective of enhancement characteristics.

Perfusion and diffusion-weighted imaging parameters: Comparison between pre- and postbiopsy MRI for high-grade glioma

We aimed to evaluate the differences in dynamic susceptibility contrast (DSC)- magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI) parameters between the pre- and postbiopsy MRI obtained before treatment in patients with diffuse midline glioma, H3K27-altered. The data of 25 patients with pathologically proven diffuse midline glioma, H3K27-altered, were extracted from our hospital's database between January 2017 and August 2021. Twenty (median age, 13 years; range, 3-52 years; 12 women) and 8 (13.5 years; 5-68 years; 1 woman) patients underwent preoperative DSC-MRI and DWI before and after biopsy, respectively. The normalized corrected relative cerebral blood volume (ncrCBV), normalized relative cerebral blood flow (nrCBF), and normalized maximum, mean, and minimum apparent diffusion coefficient (ADC) were calculated using the volumes-of-interest of the tumor and normal-appearing reference region. The macroscopic postbiopsy changes (i.e., biopsy tract, tissue defect, and hemorrhage) were meticulously excluded from the postbiopsy measurements. The DSC-MRI and DWI parameters of the pre- and postbiopsy groups were compared using the Mann-Whitney U test. The ncrCBV was significantly lower in the postbiopsy group than in the prebiopsy group [prebiopsy group: median 1.293 (range, 0.513 to 2.547) versus postbiopsy group: 0.877 (0.748 to 1.205), P = .016]. No significant difference was observed in the nrCBF and normalized ADC values, although the median nrCBF was lower in the postbiopsy group. The DSC-MRI parameters differed between the pre- and postbiopsy MRI obtained pretreatment, although the macroscopic postbiopsy changes were carefully excluded from the analysis. The results emphasize the potential danger of integrating and analyzing DSC-MRI parameters derived from pre- and postbiopsy MRI.

Adult diffuse midline gliomas H3 K27-altered: review of a redefined entity

INTRODUCTION

Diffuse midline glioma (DMG) H3 K27-altered is a type of high-grade gliomas first recognized as a new entity in the 2016 World Health Organization Classification of Central Nervous System (CNS) Tumors as DMG H3 K27M-mutant, recently renamed in the new 2021 WHO classification. The aim of this review is to describe the characteristics of diffuse midline gliomas H3 K27-altered in the adult population.

METHODS

We performed a review of the current literature regarding the genetic, clinical, imaging characteristics and management of diffuse midline gliomas H3 K27-altered in adult patients.

RESULTS

The 2021 WHO classification now designates the previously recognized DMG H3K27M-mutant as DMG H3 K27-altered, recognizing the alternative mechanisms by which the pathogenic pathway can be altered. Thus, the diagnostic criteria for this entity consist of diffuse growth pattern, midline anatomic location, and H3 K27-specific neuroglial mutations. DMGs' characteristic midline location makes them difficult to surgically resect and biopsy, carrying high mortality and morbidity rates, with median survival ranging from 9 to 12 months in adult patients.

CONCLUSION

The diagnosis of DMGs H3 K27-altered in adult patients should be considered upon neurological symptoms associated with an infiltrative midline brain tumor detected on imaging. Future studies are necessary to continue refining their characteristics in this age group.

Prediction of H3 K27M-mutant in midline gliomas by magnetic resonance imaging: a systematic review and meta-analysis

PURPOSE

To summarize the predictive value of MRI for H3 K27M-mutant in midline gliomas using meta-analysis.

METHODS

Systematic electronic searches of the PubMed, Embase, ISI Web of Science, and Cochrane Library up to Jun 31, 2021, were conducted by two experienced neuroradiologists with the keywords of "MRI," "Glioma," and "H3 K27M." The hierarchical summary receiver-operating characteristic (HSROC) model was used to calculate the pooled sensitivity, specificity, positive likelihood ratio (LR +), negative likelihood ratio (LR -), and diagnostic odds ratio (DOR). Coupled forest plots were used to evaluate the heterogeneity of the included studies.

RESULTS

Of seven original studies with a total of 593 patients, 240 glioma patients were included, with 45.5-70.6% H3 K27M-mutant gliomas. Using MRI, a pooled sensitivity of 0.78 (95% CI, 0.66-0.87), specificity of 0.85 (95% CI, 0.76-0.91), LR + of 5.07 (95% CI, 3.19-8.08), LR - of 0.26 (95% CI, 0.16-0.42), and DOR of 19.80 (95% CI, 9.28-42.28) were achieved for H3 K27M-mutant prediction. Significant heterogeneity was observed among the studies in terms of sensitivity (Q = 16.83, df = 7, p = 0.02; I² = 58.40 [95% CI, 25.83-90.97]), LR - (Q = 16.61, df = 7, p = 0.02; I² = 57.87 [95% CI, 24.81-90.93]), and DOR (Q = 14.05, df = 7, p = 0.05; I² = 50.18 [95% CI, 10.06-90.31]).

CONCLUSIONS

This meta-analysis demonstrated a clinical value of MRI to predict H3 K27M-mutant in midline gliomas with a pooled sensitivity of 0.78 and specificity of 0.85.

Multiparametric MRI-Based Radiomics Model for Predicting H3 K27M Mutant Status in Diffuse Midline Glioma: A Comparative Study Across Different Sequences and Machine Learning Techniques

Objectives

The performance of multiparametric MRI-based radiomics models for predicting H3 K27M mutant status in diffuse midline glioma (DMG) has not been thoroughly evaluated. The optimal combination of multiparametric MRI and machine learning techniques remains undetermined. We compared the performance of various radiomics models across different MRI sequences and different machine learning techniques.

Methods

A total of 102 patients with pathologically confirmed DMG were retrospectively enrolled (27 with H3 K27M-mutant and 75 with H3 K27M wild-type). Radiomics features were extracted from eight sequences, and 18 feature sets were conducted by independent combination. There were three feature matrix normalization algorithms, two dimensionality-reduction methods, four feature selectors, and seven classifiers, consisting of 168 machine learning pipelines. Radiomics models were established across different feature sets and machine learning pipelines. The performance of models was evaluated using receiver operating characteristic curves with area under the curve (AUC) and compared with DeLong’s test.

Results

The multiparametric MRI-based radiomics models could accurately predict the H3 K27M mutant status in DMG (highest AUC: 0.807–0.969, for different sequences or sequence combinations). However, the results varied significantly between different machine learning techniques. When suitable machine learning techniques were used, the conventional MRI-based radiomics models shared similar performance to advanced MRI-based models (highest AUC: 0.875–0.915 vs. 0.807–0.926; DeLong’s test, p > 0.05). Most models had a better performance when generated with a combination of MRI sequences. The optimal model in the present study used a combination of all sequences (AUC = 0.969).

Conclusions

The multiparametric MRI-based radiomics models could be useful for predicting H3 K27M mutant status in DMG, but the performance varied across different sequences and machine learning techniques.

MRI-based radiomics signature and clinical factor for predicting H3K27M mutation in pediatric high-grade gliomas located in the midline of the brain

OBJECTIVE

To develop a nomogram based on MRI radiomics and clinical features for preoperatively predicting H3K27M mutation in pediatric high-grade gliomas (pHGGs) with a midline location of the brain.

METHODS

The institutional database was reviewed to identify patients with pHGGs with a midline location of the brain who underwent tumor biopsy with preoperative MRI scans between June 2016 and June 2021. A total of 107 patients with pHGGs, including 79 patients with H3K27M mutation, were consecutively included and randomly divided into training and test sets. Radiomics features were extracted from fluid-attenuated inversion recovery (FLAIR), diffusion-weighted (DW) and post-contrast T1-weighted images, and apparent diffusion coefficient (ADC) maps. The minimum redundancy maximum relevance (MRMR) and least absolute shrinkage and selection operator (LASSO) logistic regression were performed for radiomics signature construction. Clinical and radiological features were analyzed to select clinical predictors. A nomogram was then developed by incorporating the radiomics signature and selected clinical predictors.

RESULTS

Nine radiomics features were selected to construct the radiomics signature, which showed a favorable discriminatory ability in training and test sets with an area under the curve (AUC) of 0.95 and 0.92, respectively. Ring enhancement was identified as an independent clinical predictor (p < 0.01). The nomogram, constructed with radiomics signature and ring enhancement, showed good calibration and discrimination in training and testing sets (AUC: 0.95 and 0.90 respectively).

CONCLUSIONS

The nomogram which combined radiomics signature and ring enhancement had a satisfactory ability to predict H3K27M mutation in pHGGs with a midline of the brain.

KEY POINTS

• Conventional MRI features were not powerful enough to predict H3K27M mutation status in pediatric high-grade gliomas (pHGGs) with a midline location of the brain. • An MRI-based radiomics signature showed satisfactory ability to predict H3K27M mutation status of pHGGs located in the midline of the brain. • Associating the radiomics signature with clinical factors improved predictive performance.

Diffusion and perfusion imaging biomarkers of H3 K27M mutation status in diffuse midline gliomas

PURPOSE

H3K27M-mutant diffuse midline gliomas (M-DMGs) exhibit a clinically aggressive course. We studied diffusion-weighted imaging (DWI) and perfusion (PWI) MRI features of DMG with the hypothesis that DWI-PWI metrics can serve as biomarkers for the prediction of the H3K27M mutation status in DMGs.

METHODS

A retrospective review of the institutional database (imaging and histopathology) of patients with DMG (July 2016 to July 2020) was performed. Tumoral apparent diffusion coefficient (ADC) and peritumoral ADC (PT ADC) values and their normalized values (nADC and nPT ADC) were computed. Perfusion data were analyzed with manual arterial input function (AIF) and leakage correction (LC) Boxerman-Weiskoff models. Normalized maximum relative CBV (rCBV) was evaluated. Intergroup analysis of the imaging variables was done between M-DMGs and wild-type (WT-DMGs) groups.

RESULTS

Ninety-four cases (M-DMGs-n = 48 (51%) and WT-DMGs-n = 46(49%)) were included. Significantly lower PT ADC (mutant-1.1 ± 0.33, WT-1.23 ± 0.34; P = 0.033) and nPT ADC (mutant-1.64 ± 0.48, WT-1.83 ± 0.54; P = 0.040) were noted in the M-DMGs. The rCBV (mutant-25.17 ± 27.76, WT-13.73 ± 14.83; P = 0.018) and nrCBV (mutant-3.44 ± 2.16, WT-2.39 ± 1.25; P = 0.049) were significantly higher in the M-DMGs group. Among thalamic DMGs, the min ADC, PT ADC, and nADC and nPT ADC were lower in M-DMGs while nrCBV (corrected and uncorrected) was significantly higher. Receiver operator characteristic curve analysis demonstrated that PT ADC (cut-off-1.245), nPT ADC (cut-off-1.853), and nrCBV (cut-off-1.83) were significant independent predictors of H3K27M mutational status in DMGs.

CONCLUSION

DWI and PWI features hold value in preoperative prediction of H3K27M-mutation status in DMGs.

Dynamic susceptibility contrast-MRI parameters, ADC values, and the T2-FLAIR mismatch sign are useful to differentiate between H3-mutant and H3-wild-type high-grade midline glioma

OBJECTIVES

Diffuse midline gliomas, H3K27-altered (DMG-A), are malignant gliomas with an unfavorable prognosis. Knowledge of dynamic susceptibility contrast (DSC) MRI findings and imaging differences with high-grade midline glioma without H3K27 alteration (DMG-W) has been limited. We compared the DSC, ADC, and conventional MRI findings between DMG-A and DMG-W.

METHODS

In this single institutional retrospective study, the electronic database of our hospital between June 2015 and May 2021 was searched. Twenty and 17 patients with DMG-A (median, 13 years; range, 3-52 years; 11 females) and DMG-W (median, 40 years; 7-73 years; 9 females), respectively, were found. Normalized relative cerebral blood flow (nrCBF) and normalized corrected relative cerebral blood volume (ncrCBV); normalized maximum, mean, and minimum ADC values; and the prevalence of T2-FLAIR mismatch sign were compared between the two groups using Mann-Whitney U tests and Fisher's exact test.

RESULTS

The nrCBF and ncrCBV were significantly lower in DMG-A compared with DMG-W (nrCBF: median 0.88 [range, 0.19-2.67] vs. 1.47 [range, 0.57-4.90] (p < 0.001); ncrCBV: 1.17 [0.20-2.67] vs. 1.56 [0.60-4.03] (p = 0.008)). Normalized maximum ADC (nADC_max) was significantly higher in DMG-A (median 2.37 [1.25-3.98] vs. 1.95 [1.23-2.77], p = 0.02). T2-FLAIR mismatch sign was significantly more common in DMG-A (11/20 (55.0%) vs. 1/17 (5.9%), p = 0.0017). When at least two of nrCBF < 1.11, nADC_max ≥ 2.48, and T2-FLAIR mismatch sign were positive, the diagnostic performance was the highest with accuracy of 0.81.

CONCLUSION

DSC-MRI parameters, ADC values, and the T2-FLAIR mismatch sign are useful to differentiate between DMG-A and DMG-W.

KEY POINTS

• Diffuse midline glioma, H3K27-altered (DMG-A), showed a significantly lower normalized relative cerebral blood flow and volume compared with H3K27-wild-type counterparts (DMG-W). • T2-fluid-attenuated inversion recovery (FLAIR) mismatch sign was significantly more frequent in DMG-A compared to DMG-W. • Indicators that combined DSC parameters, ADC values, and T2-FLAIR mismatch sign, with or without age, are useful to distinguish the two tumors.

Advanced Diagnosis of Glioma by Using Emerging Magnetic Resonance Sequences

Glioma, the most common primary brain tumor in adults, can be difficult to discern radiologically from other brain lesions, which affects surgical planning and follow-up treatment. Recent advances in MRI demonstrate that preoperative diagnosis of glioma has stepped into molecular and algorithm-assisted levels. Specifically, the histology-based glioma classification is composed of multiple different molecular subtypes with distinct behavior, prognosis, and response to therapy, and now each aspect can be assessed by corresponding emerging MR sequences like amide proton transfer-weighted MRI, inflow-based vascular-space-occupancy MRI, and radiomics algorithm. As a result of this novel progress, the clinical practice of glioma has been updated. Accurate diagnosis of glioma at the molecular level can be achieved ahead of the operation to formulate a thorough plan including surgery radical level, shortened length of stay, flexible follow-up plan, timely therapy response feedback, and eventually benefit patients individually.

Diffuse midline gliomas, H3 K27M-mutant are associated with less peritumoral edema and contrast enhancement in comparison to glioblastomas, H3 K27M-wildtype of midline structures

Purpose

The entity ‘diffuse midline glioma, H3 K27M-mutant (DMG)’ was introduced in the revised 4^th edition of the 2016 WHO classification of brain tumors. However, there are only a few reports on magnetic resonance imaging (MRI) of these tumors. Thus, we conducted a retrospective survey focused on MRI features of DMG compared to midline glioblastomas H3 K27M-wildtype (mGBM-H3wt).

Methods

We identified 24 DMG cases and 19 mGBM-H3wt patients as controls. After being retrospectively evaluated for microscopic evidence of microvascular proliferations (MVP) and tumor necrosis by two experienced neuropathologists to identify the defining histological criteria of mGBM-H3wt, the samples were further analyzed by two experienced readers regarding imaging features such as shape, peritumoral edema and contrast enhancement.

Results

The DMG were found in the thalamus in 37.5% of cases (controls 63%), in the brainstem in 50% (vs. 32%) and spinal cord in 12.5% (vs. 5%). In MRI and considering MVP, DMG were found to be by far less likely to develop peritumoral edema (OR: 0.13; 95%-CL: 0.02–0.62) (p = 0.010). They, similarly, were associated with a significantly lower probability of developing strong contrast enhancement compared to mGBM-H3wt (OR: 0.10; 95%-CL: 0.02–0.47) (P = 0.003).

Conclusion

Despite having highly variable imaging features, DMG exhibited markedly less edema and lower contrast enhancement in MRI compared to mGBM-H3wt. Of these features, the enhancement level was associated with evidence of MVP.

Prediction of H3K27M mutation status of diffuse midline gliomas using MRI features

BACKGROUND AND PURPOSE

Presurgical prediction of H3K27M mutation in diffuse midline gliomas (DMGs) on MRI is desirable. The purpose of this study is to elaborate conventional MRI (cMRI) features of H3K27M-mutant DMGs and identify features that could discriminate them from wild-type (WT) DMGs.

METHODS

CMRI features of 123 patients with DMG were evaluated conforming to the institutional research protocols. Multimodality MRI was performed on 1.5 or 3.0 Tesla MR Scanners with imaging protocol, including T1-weighted (w), T2w, fluid-attenuated inversion recovery, diffusion-weighted, susceptibility-weighted, and postcontrast T1w sequences. Pertinent cMRI features were annotated along the lines of Visually AcceSAble Rembrandt Images features, and Intra Tumoral Susceptibility Signal score (ITSS) was evaluated. R software was used for statistical analysis.

RESULTS

Sixty-one DMGs were H3K27M-mutant (mutant DMGs). The patients in the H3K27M-mutant DMG group were younger compared to the WT-DMG group (mean age 24.13 ± 13.13 years vs. 35.79±18.74 years) (p = 0.016). The two groups differed on five cMRI features--(1) enhancement quality (p = 0.032), (2) thickness of enhancing margin (p = 0.05), (3) proportion of edema (p = 0.002), (4) definition of noncontrast-enhancing tumor (NCET) margin (p = 0.001), and (5) cortical invasion (p = 0.037). The mutant DMGs showed greater enhancement and greater thickness of enhancing margin, while the WT DMGs exhibited significantly larger edema proportion with poorly defined NCET margins and cortical invasion. ITSS was not significantly different among the groups.

CONCLUSION

CMRI features like enhancement quality, the thickness of the enhancing margin, proportion of edema, definition of NCET margin, and cortical invasion can discriminate between the H3K27M-mutant and WT DMGs.

Radiogenomics of diffuse intrinsic pontine gliomas (DIPGs): correlation of histological and biological characteristics with multimodal MRI features

OBJECTIVES

The diffuse intrinsic pontine gliomas (DIPGs) are now defined by the type of histone H3 mutated at lysine 27. We aimed to correlate the multimodal MRI features of DIPGs, H3K27M mutant, with their histological and molecular characteristics.

METHODS

Twenty-seven treatment-naïve children with histopathologically confirmed DIPG H3K27M mutant were prospectively included. MRI performed prior to biopsy included multi-b-value diffusion-weighted imaging, ASL, and dynamic susceptibility contrast (DSC) perfusion imaging. The ADC and cerebral blood flow (CBF) and blood volume (CBV) were measured at the biopsy site. We assessed quantitative histological data, including microvascular density, nuclear density, and H3K27M-positive nuclear density. Gene expression profiling was also assessed in the samples. We compared imaging and histopathological data according to histone subgroup. We correlated MRI quantitative data with histological data and gene expression.

RESULTS

H3.1K27M mutated tumors showed higher ADC values (median 3151 μm²/s vs 1741 μm²/s, p = 0.003), and lower perfusion values (DSC-rCBF median 0.71 vs 1.43, p = 0.002, and DSC-rCBV median 1.00 vs 1.71, p = 0.02) than H3.3K27M ones. They had similar microvascular and nuclear density, but lower H3K27M-positive nuclear density (p = 0.007). The DSC-rCBV was positively correlated to the H3K27M-positive nuclear density (rho = 0.74, p = 0.02). ADC values were not correlated with nuclear density nor perfusion values with microvascular density. The expression of gated channel activity-related genes tended to be inversely correlated with ADC values and positively correlated with DSC perfusion.

CONCLUSIONS

H3.1K27M mutated tumors have higher ADC and lower perfusion values than H3.3K27M ones, without direct correlation with microvascular or nuclear density. This may be due to tissular edema possibly related to gated channel activity-related gene expression.

KEY POINTS

• H3.1K27M mutant DIPG had higher apparent diffusion coefficient (p = 0.003), lower α (p = 0.048), and lower relative cerebral blood volume (p = 0.02) than H3.3K27M mutant DIPG at their biopsy sites. • Biopsy samples obtained within the tumor's enhancing portion showed higher microvascular density (p = 0.03) than samples obtained outside the tumor's enhancing portion, but similar H3K27M-positive nuclear density (p = 0.84). • Relative cerebral blood volume measured at the biopsy site was significantly correlated with H3K27M-positive nuclear density (rho = 0.74, p = 0.02).

Machine Learning-Based Multiparametric Magnetic Resonance Imaging Radiomics for Prediction of H3K27M Mutation in Midline Gliomas

OBJECTIVE

H3K27M mutation in gliomas has prognostic implications. Previous magnetic resonance imaging (MRI) studies have reported variable rates of tumoral enhancement, necrotic changes, and peritumoral edema in H3K27M-mutant gliomas, with no distinguishing imaging features compared with wild-type gliomas. We aimed to construct an MRI machine learning (ML)-based radiomic model to predict H3K27M mutation in midline gliomas.

METHODS

A total of 109 patients from 3 academic centers were included in this study. Fifty patients had H3K27M mutation and 59 were wild-type. Conventional MRI sequences (T1-weighted, T2-weighted, T2-fluid-attenuated inversion recovery, postcontrast T1-weighted, and apparent diffusion coefficient maps) were used for feature extraction. A total of 651 radiomic features per each sequence were extracted. Patients were randomly selected with a 7:3 ratio to create training (n = 76) and test (n = 33) data sets. An extreme gradient boosting algorithm (XGBoost) was used in ML-based model development. Performance of the model was assessed by area under the receiver operating characteristic curve.

RESULTS

Pediatric patients accounted for a larger proportion of the study cohort (60 pediatric [55%] vs. 49 adult [45%] patients). XGBoost with additional feature selection had an area under the receiver operating characteristic curve of 0.791 and 0.737 in the training and test data sets, respectively. The model achieved accuracy, precision (positive predictive value), recall (sensitivity), and F1 (harmonic mean of precision and recall) measures of 72.7%, 76.5%, 72.2%, and 74.3%, respectively, in the test set.

CONCLUSIONS

Our multi-institutional study suggests that ML-based radiomic analysis of multiparametric MRI can be a promising noninvasive technique to predict H3K27M mutation status in midline gliomas.

Regional and Volumetric Parameters for Diffusion-Weighted WHO Grade II and III Glioma Genotyping: A Method Comparison

BACKGROUND AND PURPOSE

Studies consistently report lower ADC values in isocitrate dehydrogenase (IDH) wild-type gliomas than in IDH mutant tumors, but their methods and thresholds vary. This research aimed to compare volumetric and regional ADC measurement techniques for glioma genotyping, with a focus on IDH status prediction.

MATERIALS AND METHODS

Treatment-naïve World Health Organization grade II and III gliomas were analyzed by 3 neuroradiologist readers blinded to tissue results. ADC minimum and mean ROIs were defined in tumor and in normal-appearing white matter to calculate normalized values. T2-weighted tumor VOIs were registered to ADC maps with histogram parameters (mean, 2nd and 5th percentiles) extracted. Nonparametric testing (eta² and ANOVA) was performed to identify associations between ADC metrics and glioma genotypes. Logistic regression was used to probe the ability of VOI and ROI metrics to predict IDH status.

RESULTS

The study included 283 patients with 79 IDH wild-type and 204 IDH mutant gliomas. Across the study population, IDH status was most accurately predicted by ROI mean normalized ADC and VOI mean normalized ADC, with areas under the curve of 0.83 and 0.82, respectively_. The results for ROI-based genotyping of nonenhancing and solid-patchy enhancing gliomas were comparable with volumetric parameters (area under the curve = 0.81-0.84). In rim-enhancing, centrally necrotic tumors (n = 23), only volumetric measurements were predictive (0.90).

CONCLUSIONS

Regional normalized mean ADC measurements are noninferior to volumetric segmentation for defining solid glioma IDH status. Partially necrotic, rim-enhancing tumors are unsuitable for ROI assessment and may benefit from volumetric ADC quantification.

Radiomics of Pediatric Low-Grade Gliomas: Toward a Pretherapeutic Differentiation of BRAF-Mutated and BRAF-Fused Tumors

BACKGROUND AND PURPOSE

B-Raf proto-oncogene, serine/threonine kinase (BRAF) status has important implications for prognosis and therapy of pediatric low-grade gliomas. Currently, BRAF status classification relies on biopsy. Our aim was to train and validate a radiomics approach to predict BRAF fusion and BRAF V600E mutation.

MATERIALS AND METHODS

In this bi-institutional retrospective study, FLAIR MR imaging datasets of 115 pediatric patients with low-grade gliomas from 2 children's hospitals acquired between January 2009 and January 2016 were included and analyzed. Radiomics features were extracted from tumor segmentations, and the predictive model was tested using independent training and testing datasets, with all available tumor types. The model was selected on the basis of a grid search on the number of trees, opting for the best split for a random forest. We used the area under the receiver operating characteristic curve to evaluate model performance.

RESULTS

The training cohort consisted of 94 pediatric patients with low-grade gliomas (mean age, 9.4 years; 45 boys), and the external validation cohort comprised 21 pediatric patients with low-grade gliomas (mean age, 8.37 years; 12 boys). A 4-fold cross-validation scheme predicted BRAF status with an area under the curve of 0.75 (SD, 0.12) (95% confidence interval, 0.62-0.89) on the internal validation cohort. By means of the optimal hyperparameters determined by 4-fold cross-validation, the area under the curve for the external validation was 0.85. Age and tumor location were significant predictors of BRAF status (P values = .04 and <.001, respectively). Sex was not a significant predictor (P value = .96).

CONCLUSIONS

Radiomics-based prediction of BRAF status in pediatric low-grade gliomas appears feasible in this bi-institutional exploratory study.

Advancements in Neuroimaging to Unravel Biological and Molecular Features of Brain Tumors

Simple Summary

Advanced neuroimaging is gaining increasing relevance for the characterization and the molecular profiling of brain tumor tissue. On one hand, for some tumor types, the most widespread advanced techniques, investigating diffusion and perfusion features, have been proven clinically feasible and rather robust for diagnosis and prognosis stratification. In addition, 2-hydroxyglutarate spectroscopy, for the first time, offers the possibility to directly measure a crucial molecular marker. On the other hand, numerous innovative approaches have been explored for a refined evaluation of tumor microenvironments, particularly assessing microstructural and microvascular properties, and the potential applications of these techniques are vast and still to be fully explored.

Abstract

In recent years, the clinical assessment of primary brain tumors has been increasingly dependent on advanced magnetic resonance imaging (MRI) techniques in order to infer tumor pathophysiological characteristics, such as hemodynamics, metabolism, and microstructure. Quantitative radiomic data extracted from advanced MRI have risen as potential in vivo noninvasive biomarkers for predicting tumor grades and molecular subtypes, opening the era of “molecular imaging” and radiogenomics. This review presents the most relevant advancements in quantitative neuroimaging of advanced MRI techniques, by means of radiomics analysis, applied to primary brain tumors, including lower-grade glioma and glioblastoma, with a special focus on peculiar oncologic entities of current interest. Novel findings from diffusion MRI (dMRI), perfusion-weighted imaging (PWI), and MR spectroscopy (MRS) are hereby sifted in order to evaluate the role of quantitative imaging in neuro-oncology as a tool for predicting molecular profiles, stratifying prognosis, and characterizing tumor tissue microenvironments. Furthermore, innovative technological approaches are briefly addressed, including artificial intelligence contributions and ultra-high-field imaging new techniques. Lastly, after providing an overview of the advancements, we illustrate current clinical applications and future perspectives.

Imaging characteristics of H3 K27M histone-mutant diffuse midline glioma in teenagers and adults

Background

To assess anatomical and quantitative diffusion-weighted MR imaging features in a recently classified lethal neoplasm, H3 K27M histone-mutant diffuse midline glioma [World Health Organization (WHO) IV].

Methods

Fifteen untreated gliomas in teenagers and adults (median age 19, range, 14-64) with confirmed H3 K27M histone-mutant genotype were analysed at a national referral centre. Morphological characteristics including tumour epicentre(s), T2/FLAIR and Gadolinium enhancement patterns, calcification, haemorrhage and cyst formation were recorded. Multiple apparent diffusion coefficient (ADC_min, ADC_mean) regions of interest were sited in solid tumour and normal appearing white matter (ADC_NAWM) using post-processing software (Olea Sphere v2.3, Olea Medical). ADC histogram data (2^nd, 5^th, 10^th percentile, median, mean, kurtosis, skewness) were calculated from volumetric tumour segmentations and tested against the regions of interest (ROI) data (Wilcoxon signed rank test).

Results

The median interval from imaging to tissue diagnosis was 9 (range, 0-74) days. The structural MR imaging findings varied between individuals and within tumours, often featuring signal heterogeneity on all MR sequences. All gliomas demonstrated contact with the brain midline, and 67% exhibited rim-enhancing necrosis. The mean ROI ADC_min value was 0.84 (±0.15 standard deviation, SD) ×10^-3 mm²/s. In the largest tumour cross-section (excluding necrosis), an average ADC_mean value of 1.12 (±0.25)×10^-3 mm²/s was observed. The mean ADC_min/NAWM ratio was 1.097 (±0.149), and the mean ADC_mean/NAWM ratio measured 1.466 (±0.299). With the exception of the 2^nd centile, no statistical difference was observed between the regional and histogram derived ADC results.

Conclusions

H3 K27M-mutant gliomas demonstrate variable morphology and diffusivity, commonly featuring moderately low ADC values in solid tumour. Regional ADC measurements appeared representative of volumetric histogram data in this study.

Dual PET Imaging of an H3K27M-Mutant Glioma With 18F-GE-180 and 18F-FET PET

A 25-year-old man presented with headache and intracranial pressure symptoms. On MRI, an intracranial lesion was detected in the right thalamus with exophytic growth into the third ventricle and inhomogeneous contrast enhancement without necrosis. Dual amino acid (F-FET) and TSPO (F-GE-180) PET imaging showed high tumor-to-background ratios in both scans and a short time-to-peak in F-FET uptake dynamics. Biopsy revealed a diffuse midline glioma, H3K27M-mutant (WHO grade IV), a novel entity in the 2016 WHO classification with poor clinical outcome. Our case shows that the highly aggressive features of this tumor entity can be visualized in vivo by both PET modalities.

H3K27M-mutant diffuse midline glioma presenting as synchronous lesions involving pineal and suprasellar region: A case report and literature review

INTRODUCTION

The differential diagnoses for multifocal lesions with pineal and suprasellar involvement in a young adult include germ cell tumour and intracranial metastasis. Other differentials include atypical teratoid/rhabdoid tumour and pineoblastoma. We present the first known case of multicentric H3K27M mutant diffuse midline glioma, which is typically defined by its diffuse nature, midline location, and H3K27M mutation.

CASE REPORT

A young Chinese female presented subacutely with giddiness, right abducens nerve palsy and unsteady gait. Magnetic resonance imaging (MRI) of the brain with contrast revealed a moderately sized pineal region tumour, extending into the third ventricle, associated with hydrocephalus. There were two other synchronous lesions noted in the suprasellar and left occipital region. Serum and cerebrospinal fluid tumour markers, along with a computed tomography scan of her thorax and abdomen and were unremarkable. She underwent an endoscopic third ventriculostomy and biopsy of pineal and suprasellar lesions. Histology demonstrated a poor prognosis variant multifocal glioblastoma multiforme that was IDH wildtype, H3K27M positive, and MGMT unmethylated. MRI of the whole spine did not reveal any drop metastasis. The patient subsequently underwent adjuvant chemotherapy and radiotherapy after she was deemed to be unsuitable for surgical resection.

CONCLUSION

Although rare, multicentric H3K27M mutant diffuse midline glioma should be included in the list of differential diagnoses for multifocal enhancing lesions with involvement of the pineal and suprasellar regions, especially if the lesions demonstrate imaging features atypical for more common diagnosis such as germ cell tumours.

Variations in attitudes towards stereotactic biopsy of adult diffuse midline glioma patients: a survey of members of the AANS/CNS Tumor Section

Purpose

Diffuse midline gliomas are rare midline CNS malignancies that primarily affect children but can also affect adults. While radiation is standard treatment, prognosis remains fatal. Furthermore, due to its sensitive anatomic location, many physicians have been reluctant to perform biopsies without potential for improved prognosis. However, recent advancements in molecular-targeted therapeutics have encouraged greater tissue sampling. While the literature reflects this progress, the landscape of how clinicians actually manage these patients remains unclear. Our goal was to assess the attitudes of current practicing neurosurgical oncologists towards management of adult diffuse midline gliomas, reasons behind their practices, and factors that might influence these practices.

Methods

We created and distributed a survey with 16 multiple choice and open-ended questions to members of the Tumor Section of the Congress of Neurological Surgeons.

Results

A total of 81 physicians responded to the survey. Although time since training and volume of glioma patients did not significantly affect the decision to consider clinical trials or to offer biopsy, those that operated on fewer gliomas (< 25/year) were more likely to cite surgical morbidity as the primary reason not to biopsy these midline locations. Further, surgeons with access to more advanced molecular testing were significantly more likely to consider clinical trial eligibility when offering biopsies.

Conclusion

Factors that affect the management of diffuse midline gliomas and the role of biopsy are relatively uniform across the field, however, there were a few notable differences that reflect the changes within the neuro-oncology field in response to clinical trials.

Electronic supplementary material

The online version of this article (10.1007/s11060-020-03585-7) contains supplementary material, which is available to authorized users.

MR Imaging Correlates for Molecular and Mutational Analyses in Children with Diffuse Intrinsic Pontine Glioma

BACKGROUND AND PURPOSE

Recent advances in molecular techniques have characterized distinct subtypes of diffuse intrinsic pontine gliomas. Our aim was the identification of MR imaging correlates of these subtypes.

MATERIALS AND METHODS

Initial MRIs from subjects with diffuse intrinsic pontine gliomas recruited for a prospective clinical trial before treatment were analyzed. Retrospective imaging analyses included FLAIR/T2 tumor volume, tumor volume enhancing, the presence of cyst and/or necrosis, median, mean, mode, skewness, kurtosis of ADC tumor volume based on FLAIR, and enhancement at baseline. Molecular subgroups based on EGFR and MGMT mutations were established. Histone mutations were also determined (H3F3A, HIST1H3B, HIST1H3C). Univariate Cox proportional hazards regression was used to test the association of imaging predictors with overall and progression-free survival. Wilcoxon rank sum, Kruskal-Wallis, and Fisher exact tests were used to compare imaging measures among groups.

RESULTS

Fifty patients had biopsy and MR imaging. The median age at trial registration was 6 years (range, 3.3-17.5 years); 52% were female. On the basis of immunohistochemical results, 48 patients were assigned to 1 of 4 subgroups: 28 in MGMT-/epidermal growth factor receptor (EGFR)-, 14 in MGMT-/EGFR+, 3 in MGMT+/EGFR-, and 3 in MGMT+/EGFR+. Twenty-three patients had histone mutations in H3F3A, 8 in HIST1H3B, and 3 in HIST1H3C. Enhancing tumor volume was near-significantly different across molecular subgroups (P = .04), after accounting for the false discovery rate. Tumor volume enhancing, median, mode, skewness, and kurtosis ADC T2-FLAIR/T2 were significantly different (P ≤ .048) between patients with H3F3A and HIST1H3B/C mutations.

CONCLUSIONS

MR imaging features including enhancement and ADC histogram parameters are correlated with molecular subgroups and mutations in children with diffuse intrinsic pontine gliomas.