Diffuse gliomas in patients aged 55 years or over: A suggestion for IDH mutation testing

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.

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.

Cognitive functioning in untreated glioma patients: The limited predictive value of clinical variables

BACKGROUND

Previous research identified many clinical variables that are significantly related to cognitive functioning before surgery. It is not clear whether such variables enable accurate prediction for individual patients' cognitive functioning because statistical significance does not guarantee predictive value. Previous studies did not test how well cognitive functioning can be predicted for (yet) untested patients. Furthermore, previous research is limited in that only linear or rank-based methods with small numbers of variables were used.

METHODS

We used various machine learning models to predict preoperative cognitive functioning for 340 patients with glioma across 18 outcome measures. Predictions were made using a comprehensive set of clinical variables as identified from the literature. Model performances and optimized hyperparameters were interpreted. Moreover, Shapley additive explanations were calculated to determine variable importance and explore interaction effects.

RESULTS

Best-performing models generally demonstrated above-random performance. Performance, however, was unreliable for 14 out of 18 outcome measures with predictions worse than baseline models for a substantial number of train-test splits. Best-performing models were relatively simple and used most variables for prediction while not relying strongly on any variable.

CONCLUSIONS

Preoperative cognitive functioning could not be reliably predicted across cognitive tests using the comprehensive set of clinical variables included in the current study. Our results show that a holistic view of an individual patient likely is necessary to explain differences in cognitive functioning. Moreover, they emphasize the need to collect larger cross-center and multimodal data sets.

Treatment outcome of IDH1/2 wildtype CNS WHO grade 4 glioma histologically diagnosed as WHO grade II or III astrocytomas

BACKGROUND

Isocitrate dehydrogenase (IDH)1/2 wildtype (wt) astrocytomas formerly classified as WHO grade II or III have significantly shorter PFS and OS than IDH mutated WHO grade 2 and 3 gliomas leading to a classification as CNS WHO grade 4. It is the aim of this study to evaluate differences in the treatment-related clinical course of these tumors as they are largely unknown.

METHODS

Patients undergoing surgery (between 2016-2019 in six neurosurgical departments) for a histologically diagnosed WHO grade 2-3 IDH1/2-wt astrocytoma were retrospectively reviewed to assess progression free survival (PFS), overall survival (OS), and prognostic factors.

RESULTS

This multi-center study included 157 patients (mean age 58 years (20-87 years); with 36.9% females). The predominant histology was anaplastic astrocytoma WHO grade 3 (78.3%), followed by diffuse astrocytoma WHO grade 2 (21.7%). Gross total resection (GTR) was achieved in 37.6%, subtotal resection (STR) in 28.7%, and biopsy was performed in 33.8%. The median PFS (12.5 months) and OS (27.0 months) did not differ between WHO grades. Both, GTR and STR significantly increased PFS (P < 0.01) and OS (P < 0.001) compared to biopsy. Treatment according to Stupp protocol was not associated with longer OS or PFS compared to chemotherapy or radiotherapy alone. EGFR amplification (P = 0.014) and TERT-promotor mutation (P = 0.042) were associated with shortened OS. MGMT-promoter methylation had no influence on treatment response.

CONCLUSIONS

WHO grade 2 and 3 IDH1/2 wt astrocytomas, treated according to the same treatment protocols, have a similar OS. Age, extent of resection, and strong EGFR expression were the most important treatment related prognostic factors.

Adult-type and Pediatric-type Diffuse Gliomas : What the Neuroradiologist Should Know

The classification of diffuse gliomas into the adult type and the pediatric type is the new basis for the diagnosis and clinical evaluation. The knowledge for the neuroradiologist should not remain limited to radiological aspects but should be based additionally on the current edition of the World Health Organization (WHO) classification of tumors of the central nervous system (CNS). This classification defines the 11 entities of diffuse gliomas, which are included in the 3 large groups of adult-type diffuse gliomas, pediatric-type diffuse low-grade gliomas, and pediatric-type diffuse high-grade gliomas. This article provides a detailed overview of important molecular, morphological, and clinical aspects for all 11 entities, such as typical genetic alterations, age distribution, variability of the tumor localization, variability of histopathological and radiological findings within each entity, as well as currently available statistical information on prognosis and outcome. Important differential diagnoses are also discussed.

From Theory to Practice: Implementing the WHO 2021 Classification of Adult Diffuse Gliomas in Neuropathology Diagnosis

Diffuse gliomas are the most common type of primary central nervous system (CNS) neoplasm to affect the adult population. The diagnosis of adult diffuse gliomas is dependent upon the integration of morphological features of the tumour with its underlying molecular alterations, and the integrative diagnosis has become of increased importance in the fifth edition of the WHO classification of CNS neoplasms (WHO CNS5). The three major diagnostic entities of adult diffuse gliomas are as follows: (1) astrocytoma, IDH-mutant; (2) oligodendroglioma, IDH-mutant and 1p/19q-codeleted; and (3) glioblastoma, IDH-wildtype. The aim of this review is to summarize the pathophysiology, pathology, molecular characteristics, and major diagnostic updates encountered in WHO CNS5 of adult diffuse gliomas. Finally, the application of implementing the necessary molecular tests for diagnostic workup of these entities in the pathology laboratory setting is discussed.

Imaging Recommendations for the Diagnosis, Staging, and Management of Adult Brain Tumors

Neuroimaging plays a pivotal role in the clinical practice of brain tumors aiding in the diagnosis, genotype prediction, preoperative planning, and prognostication. The brain tumors most commonly seen in adults are extra-axial lesions like meningioma, intra-axial lesions like gliomas and lesions of the pituitary gland. Clinical features may be localizing like partial seizures, weakness, and sensory disturbances or nonspecific like a headache. On clinical suspicion of a brain tumor, the primary investigative workup should focus on imaging. Other investigations like fundoscopy and electroencephalography may be performed depending on the clinical presentation. Obtaining a tissue sample after identifying a brain tumor on imaging is crucial for confirming the diagnosis and planning further treatment. Tissue sample may be obtained by techniques such as stereotactic biopsy or upfront surgery. The magnetic resonance (MR) imaging protocol needs to be standardized and includes conventional sequences like T1-weighted (T1W) imaging with and without contrast, T2w imaging, fluid-attenuated axial inversion recovery, diffusion-weighted imaging (DWI), susceptibility-weighted imaging, and advanced imaging sequences like MR perfusion and MR spectroscopy. Various tumor characteristics in each of these sequences can help us narrow down the differential diagnosis and also predict the grade of the tumor. Multidisciplinary co-ordination is needed for proper management and care of brain tumor patients. Treatment protocols need to be adapted and individualized for each patient depending on the age, general condition of the patient, histopathological characteristics, and genotype of the tumor. Treatment options include surgery, radiotherapy, and chemotherapy. Imaging also plays a vital role in post-treatment follow-up. Sequences like DWI, MR perfusion, and MR spectroscopy are useful to distinguish post-treatment effects like radiation necrosis and pseudoprogression from true recurrence. Radiological reporting of brain tumor images should follow a structured format to include all the elements that could have an impact on the treatment decisions in patients.

Prognostic significance of HIF1-α immunohistochemical expression in gliomas and it's relation to IDH1 mutation status

Background

Gliomas are the commonest primary adults’ brain tumors. Hypoxia performs an essential role in gliomas’ initiation as well as progression through hypoxia inducible factor (HIF-1α) activation, which could serve as a promising target in treatment of gliomas. Our study aimed to evaluate types and grades of glioma cases and detect isocitrate dehydrogenase 1 (IDH1) mutation status and expression of HIF-1α in all included cases and its correlation with clinical data and pathological parameters.

Results

Samples from 71 patients who were diagnosed with glioma were studied immunohistochemically for IDH1-R132H (if indicated) and HIF-1α expression. Expression of HIF-1α was detected in 73.2% of the included 71 gliomas. HIF-1α expression significantly increased in older patients, in high-grade gliomas and in tumors positive for necrosis. We studied IDH1 mutation in the histologically diagnosed grade 2, 3and 4 astrocytic and oligodendroglial tumors (51 cases out of the included 71 gliomas). IDH1-R132H immunohistochemical expression was positive in 62.7% of cases. IDH1 mutation was significantly higher with younger age. IDH1 mutation was noted also with lower tumor grade. A statistically significant relation was detected between negative IDH1-R132H expression and high level of HIF-1α immunohistochemical expression.

Conclusion

Absence of IDH1 mutation with increased HIF-1α expression among high-grade gliomas suggesting both as predicting indicators for poor prognosis.

A Radiologist's Guide to the 2021 WHO Central Nervous System Tumor Classification: Part I-Key Concepts and the Spectrum of Diffuse Gliomas

The fifth edition of the World Health Organization (WHO) classification of tumors of the central nervous system, published in 2021, contains substantial updates in the classification of tumor types. Many of these changes are relevant to radiologists, including "big picture" changes to tumor diagnosis methods, nomenclature, and grading, which apply broadly to many or all central nervous system tumor types, as well as the addition, elimination, and renaming of multiple specific tumor types. Radiologists are integral in interpreting brain tumor imaging studies and have a considerable impact on patient care. Thus, radiologists must be aware of pertinent changes in the field. Staying updated with the most current guidelines allows radiologists to be informed and effective at multidisciplinary tumor boards and in interactions with colleagues in neuro-oncology, neurosurgery, radiation oncology, and neuropathology. This review represents the first of a two-installment review series on the most recent changes to the WHO brain tumor classification system. This first installment focuses on the changes to the classification of adult and pediatric gliomas of greatest relevance for radiologists.

Simple approach for the histomolecular diagnosis of central nervous system gliomas based on 2021 World Health Organization Classification

The classification of central nervous system (CNS) glioma went through a sequence of developments, between 2006 and 2021, started with only histological approach then has been aided with a major emphasis on molecular signatures in the 4th and 5th editions of the World Health Organization (WHO). The recent reformation in the 5th edition of the WHO classification has focused more on the molecularly defined entities with better characterized natural histories as well as new tumor types and subtypes in the adult and pediatric populations. These new subclassified entities have been incorporated in the 5^th edition after the continuous exploration of new genomic, epigenomic and transcriptomic discovery. Indeed, the current guidelines of 2021 WHO classification of CNS tumors and European Association of Neuro-Oncology (EANO) exploited the molecular signatures in the diagnostic approach of CNS gliomas. Our current review presents a practical diagnostic approach for diffuse CNS gliomas and circumscribed astrocytomas using histomolecular criteria adopted by the recent WHO classification. We also describe the treatment strategies for these tumors based on EANO guidelines.

Integrated CT Radiomics Features Could Enhance the Efficacy of 18F-FET PET for Non-Invasive Isocitrate Dehydrogenase Genotype Prediction in Adult Untreated Gliomas: A Retrospective Cohort Study

Purpose

We aimed to investigate the predictive models based on O-[2-(¹⁸F)fluoroethyl]-l-tyrosine positron emission tomography/computed tomography (¹⁸F-FET PET/CT) radiomics features for the isocitrate dehydrogenase (IDH) genotype identification in adult gliomas.

Methods

Fifty-eight consecutive pathologically confirmed adult glioma patients with pretreatment ¹⁸F-FET PET/CT were retrospectively enrolled. One hundred and five radiomics features were extracted for analysis in each modality. Three independent radiomics models (PET-Rad Model, CT-Rad Model and PET/CT-Rad Model) predicting IDH mutation status were generated using the least absolute shrinkage and selection operator (LASSO) regression analysis based on machine learning algorithms. All-subsets regression and cross validation were applied for the filter and calibration of the predictive radiomics models. Besides, semi-quantitative parameters including maximum, peak and mean tumor to background ratio (TBRmax, TBRpeak, TBRmean), standard deviation of glioma lesion standardized uptake value (SUV_SD), metabolic tumor volume (MTV) and total lesion tracer uptake (TLU) were obtained and filtered for the simple model construction with clinical feature of brain midline involvement status. The area under the receiver operating characteristic curve (AUC) was applied for the evaluation of the predictive models.

Results

The AUC of the simple predictive model consists of semi-quantitative parameter SUV_SD and dichotomized brain midline involvement status was 0.786 (95% CI 0.659-0.883). The AUC of PET-Rad Model building with three ¹⁸F-FET PET radiomics parameters was 0.812 (95% CI 0.688-0.902). The AUC of CT-Rad Model building with three co-registered CT radiomics parameters was 0.883 (95% CI 0.771-0.952). While the AUC of the combined ¹⁸F-FET PET/CT-Rad Model building with three CT and one PET radiomics features was 0.912 (95% CI 0.808-0.970). DeLong test results indicated the PET/CT-Rad Model outperformed the PET-Rad Model (p = 0.048) and simple predictive model (p = 0.034). Further combination of the PET/CT-Rad Model with the clinical feature of dichotomized tumor location status could slightly enhance the AUC to 0.917 (95% CI 0.814-0.973).

Conclusion

The predictive model combining ¹⁸F-FET PET and integrated CT radiomics features could significantly enhance and well balance the non-invasive IDH genotype prediction in untreated gliomas, which is important in clinical decision making for personalized treatment.

Controversies in appendiceal pathology: Mucinous and goblet cell neoplasms

Appendiceal goblet cell adenocarcinomas and mucinous neoplasms are uncommon compared with other epithelial tumours of the gastrointestinal tract. Both tumour types have been subjected to terminology that belies their biological risk and leads to confusion. Goblet cell adenocarcinomas display patchy staining for endocrine markers and, thus, were previously classified as goblet cell carcinoids. Unlike well-differentiated endocrine neoplasms, however, they often contain high-grade glandular elements and pursue an aggressive course akin to that of conventional adenocarcinoma. Although several authors have recently proposed grading schemes to predict behaviour among goblet cell neoplasms, most that contain high-grade components have already spread beyond the appendix at the time of diagnosis, whereas those confined to the appendix almost always have low-grade features; the added value of grading these tumours is limited. Contradictions also surround the nomenclature of mucinous neoplasms. The World Health Organization and others promote non-malignant terminology to describe metastatic mucinous neoplasms of the peritoneum and eliminate a benign category entirely, even though virtually all neoplasms confined to the appendix pose no recurrence risk following appendectomy. 'Low-grade appendiceal mucinous neoplasm' now encompasses a spectrum of benign tumours and malignant neoplasms in the appendix and peritoneum. Although using an umbrella term in this fashion simplifies the roles of pathologists, it provides essentially no actionable information beyond that which is already clinically apparent. Broad strokes nomenclature also ensures that many patients with no risk of recurrence will receive unnecessary surveillance while others will undergo inappropriate surgical procedures due to lapses in communication. Moreover, a surprising number of non-neoplastic mucinous lesions are misclassified as low-grade appendiceal mucinous neoplasms, which can result in unwarranted patient concern or even mismanagement. The purpose of this review is to critically evaluate the literature and describe an approach to appendiceal neoplasms that more clearly denotes their biologic risk.

H3K27me3 immunostaining is diagnostic and prognostic in diffuse gliomas with oligodendroglial or mixed oligoastrocytic morphology

Oligodendroglioma is defined by IDH mutation and 1p/19q codeletion. The latter is mutually exclusive to ATRX immunohistochemical loss and has been recently associated with the loss of H3K27me3 immunostaining. We aimed to assess the diagnostic and prognostic value of H3K27me3 immuno-expression in diffuse gliomas with oligodendroglial or mixed oligoastrocytic morphology. H3K27me3 immunostaining was performed in 69 diffuse gliomas with oligodendroglial (n = 62) or oligoastrocytic (n = 7) morphology. The integration with routinely assessed IDH mutations, ATRX immunostaining, and 1p/19q codeletion classified these cases as 60 oligodendroglial and 9 astrocytic. H3K27me3 was lost in 58/60 oligodendrogliomas with retained (n = 47) or non-conclusive (n = 11) ATRX staining, 3/6 IDH-mutant astrocytomas with ATRX loss, and 3/3 IDH-wt astrocytomas. H3K27me3 was retained in 2/60 oligodendrogliomas with retained ATRX, and in 3/6 IDH-mutant astrocytomas, two of which had lost and one retained ATRX. The combination of H3K27me3 and ATRX immunostainings with IDH mutational status correctly classified 55/69 (80%) cases. In IDH-mutant gliomas, ATRX loss indicates astrocytic phenotype, while ATRX retention and H3K27me3 loss identify oligodendroglial phenotype. Only 14 (20%) IDH-mutant cases with retained ATRX and H3K27me3 or inconclusive ATRX immunostaining would have requested 1p/19q codeletion testing to be classified. Furthermore, H3K27me3 retention was associated with significantly shorter relapse-free survival (P < 0.0001), independently from IDH mutation or 1p/19q codeletion (P < 0.005). Our data suggest that adding H3K27me3 immunostaining to the diagnostic workflow of diffuse gliomas with oligodendroglial or mixed morphology is useful for drastically reducing the number of cases requiring 1p/19q codeletion testing and providing relevant prognostic information.

Simplified approach for pathological diagnosis of diffuse gliomas in adult patients

The most recent WHO classification (2016) for gliomas introduced integrated diagnoses requiring both phenotypic and genotypic data. This approach presents difficulties for countries with limited resources for laboratory testing. The present study describes a series of 118 adult Thai patients with diffuse gliomas, classified by the WHO 2016 classification. The purpose was to demonstrate how a diagnosis can still be achieved using a simplified approach that combines clinical, morphological, immunohistochemical, and fewer molecular assays than typically performed. This algorithm starts with tumor location (midline vs. non-midline) with diffuse midline glioma identified by H3 K27M immunostaining. All other tumors are placed into one of 6 categories, based on morphologic features rather than specific diagnoses. Molecular testing is limited to IDH1/IDH2 mutations, plus co-deletion of 1p/19q for cases with oligodendroglial features and TERT promoter mutation for cases without such features. Additional testing for co-deletion of 1p/19q, TERT promoter mutation and BRAF mutations are only used in selected cases to refine diagnosis and prognosis. With this approach, we were able to reach the integrated diagnosis in 117/118 cases, saving 50 % of the costs of a more inclusive testing panel. The demographic data and tumor subtypes were found to be similar to series from other regions of the world. To the best of our knowledge, this is to the first reported series of diffuse gliomas in South-East Asia categorized by the WHO 2016 classification system.

A Nomogram Modeling 11C-MET PET/CT and Clinical Features in Glioma Helps Predict IDH Mutation

Purpose: We developed a ¹¹C-Methionine positron emission tomography/computed tomography (¹¹C-MET PET/CT)-based nomogram model that uses easy-accessible imaging and clinical features to achieve reliable non-invasive isocitrate dehydrogenase (IDH)-mutant prediction with strong clinical translational capability.

Methods: One hundred and ten patients with pathologically proven glioma who underwent pretreatment ¹¹C-MET PET/CT were retrospectively reviewed. IDH genotype was determined by IDH1 R132H immunohistochemistry staining. Maximum, mean and peak tumor-to-normal brain tissue (TNRmax, TNRmean, TNRpeak), metabolic tumor volume (MTV), total lesion methionine uptake (TLMU), and standard deviation of SUV (SUV_SD) of the lesions on MET PET images were obtained via a dedicated workstation (Siemens. syngo.via). Univariate and multivariate logistic regression models were used to identify the predictive factors for IDH mutation. Nomogram and calibration plots were further performed.

Results: In the entire population, TNRmean, TNRmax, TNRpeak, and SUV_SD of IDH-mutant glioma patients were significantly lower than these values of IDH wildtype. Receiver operating characteristic (ROC) analysis suggested SUV_SD had the best performance for IDH-mutant discrimination (AUC = 0.731, cut-off ≤ 0.29, p < 0.001). All pairs of the ¹¹C-MET PET metrics showed linear associations by Pearson correlation coefficients between 0.228 and 0.986. Multivariate analyses demonstrated that SUV_SD (>0.29 vs. ≤ 0.29 OR: 0.053, p = 0.010), dichotomized brain midline structure involvement (no vs. yes OR: 26.52, p = 0.000) and age (≤ 45 vs. >45 years OR: 3.23, p = 0.023), were associated with a higher incidence of IDH mutation. The nomogram modeling showed good discrimination, with a C-statistics of 0.866 (95% CI: 0.796–0.937) and was well-calibrated.

Conclusions:¹¹C-Methionine PET/CT imaging features (SUV_SD and the involvement of brain midline structure) can be conveniently used to facilitate the pre-operative prediction of IDH genotype. The nomogram model based on ¹¹C-Methionine PET/CT and clinical age features might be clinically useful in non-invasive IDH mutation status prediction for untreated glioma patients.