Two-headed UNetEfficientNets for parallel execution of segmentation and classification of brain tumors: incorporating postprocessing techniques with connected component labelling.

PURPOSE: The purpose of this study is to develop accurate and automated detection and segmentation methods for brain tumors, given their significant fatality rates, with aggressive malignant tumors like Glioblastoma Multiforme (GBM) having a five-year survival rate as low as 5 to 10%. This underscores the urgent need to improve diagnosis and treatment outcomes through innovative approaches in medical imaging and deep learning techniques. METHODS: In this work, we propose a novel approach utilizing the two-headed UNetEfficientNets model for simultaneous segmentation and classification of brain tumors from Magnetic Resonance Imaging (MRI) images. The model combines the strengths of EfficientNets and a modified two-headed Unet model. We utilized a publicly available dataset consisting of 3064 brain MR images classified into three tumor classes: Meningioma, Glioma, and Pituitary. To enhance the training process, we performed 12 types of data augmentation on the training dataset. We evaluated the methodology using six deep learning models, ranging from UNetEfficientNet-B0 to UNetEfficientNet-B5, optimizing the segmentation and classification heads using binary cross entropy (BCE) loss with Dice and BCE with focal loss, respectively. Post-processing techniques such as connected component labeling (CCL) and ensemble models were applied to improve segmentation outcomes. RESULTS: The proposed UNetEfficientNet-B4 model achieved outstanding results, with an accuracy of 99.4% after postprocessing. Additionally, it obtained high scores for DICE (94.03%), precision (98.67%), and recall (99.00%) after post-processing. The ensemble technique further improved segmentation performance, with a global DICE score of 95.70% and Jaccard index of 91.20%. CONCLUSION: Our study demonstrates the high efficiency and accuracy of the proposed UNetEfficientNet-B4 model in the automatic and parallel detection and segmentation of brain tumors from MRI images. This approach holds promise for improving diagnosis and treatment planning for patients with brain tumors, potentially leading to better outcomes and prognosis.

Identification and classification of glioma subtypes based on RNA-binding proteins.

BACKGROUND: Glioma is a common and aggressive primary malignant cancer known for its high morbidity, mortality, and recurrence rates. Despite this, treatment options for glioma are currently restricted. The dysregulation of RBPs has been linked to the advancement of several types of cancer, but their precise role in glioma evolution is still not fully understood. This study sought to investigate how RBPs may impact the development and prognosis of glioma, with potential implications for prognosis and therapy. METHODS: RNA-seq profiles of glioma and corresponding clinical data from the CGGA database were initially collected for analysis. Unsupervised clustering was utilized to identify crucial tumor subtypes in glioma development. Subsequent time-series analysis and MS model were employed to track the progression of these identified subtypes. RBPs playing a significant role in glioma progression were then pinpointed using WGCNA and Lasso Cox regression models. Functional analysis of these key RBP-related genes was conducted through GSEA. Additionally, the CIBERSORT algorithm was utilized to estimate immune infiltrating cells, while the STRING database was consulted to uncover potential mechanisms of the identified biomarkers. RESULTS: Six tumor subgroups were identified and found to be highly homogeneous within each subgroup. The progression stages of these tumor subgroups were determined using time-series analysis and a MS model. Through WGCNA, Lasso Cox, and multivariate Cox regression analysis, it was confirmed that BCLAF1 is correlated with survival in glioma patients and is closely linked to glioma progression. Functional annotation suggests that BCLAF1 may impact glioma progression by influencing RNA splicing, which in turn affects the cell cycle, Wnt signaling pathway, and other cancer development pathways. CONCLUSIONS: The study initially identified six subtypes of glioma progression and assessed their malignancy ranking. Furthermore, it was determined that BCLAF1 could serve as an RBP-related prognostic marker, offering significant implications for the clinical diagnosis and personalized treatment of glioma.

Major Changes in 2021 World Health Organization Classification of Central Nervous System Tumors.

The World Health Organization (WHO) published the fifth edition of the WHO Classification of Tumors of the Central Nervous System (WHO CNS5) in 2021, as an update of the WHO central nervous system (CNS) classification system published in 2016. WHO CNS5 was drafted on the basis of recommendations from the Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy (cIMPACT-NOW) and expounds the classification scheme of the previous edition, which emphasized the importance of genetic and molecular changes in the characteristics of CNS tumors. Multiple newly recognized tumor types, including those for which there is limited knowledge regarding neuroimaging features, are detailed in WHO CNS5. The authors describe the major changes introduced in WHO CNS5, including revisions to tumor nomenclature. For example, WHO grade IV tumors in the fourth edition are equivalent to CNS WHO grade 4 tumors in the fifth edition, and diffuse midline glioma, H3 K27M-mutant, is equivalent to midline glioma, H3 K27-altered. With regard to tumor typing, isocitrate dehydrogenase (IDH)-mutant glioblastoma has been modified to IDH-mutant astrocytoma. In tumor grading, IDH-mutant astrocytomas are now graded according to the presence or absence of homozygous CDKN2A/B deletion. Moreover, the molecular mechanisms of tumorigenesis, as well as the clinical characteristics and imaging features of the tumor types newly recognized in WHO CNS5, are summarized. Given that WHO CNS5 has become the foundation for daily practice, radiologists need to be familiar with this new edition of the WHO CNS tumor classification system. Online supplemental material and the slide presentation from the RSNA Annual Meeting are available for this article. ©RSNA, 2022.

Analysis of the Prognosis of High-Grade gliomas in the View of New Immunohistochemistry Markers and 2016 WHO Classification.

AIM: To evaluate isocitrate dehydrogenase (IDH) mutation status and Ki67 percentages of tumors that were treated in our institution to determine whether these markers affected the initial diagnosis and survival rates. MATERIAL AND METHODS: High-grade glioma patients, who were operated in our department between 2013 and 2018, were enrolled in the study and retrospectively reviewed. New immunohistochemistry staining studies were conducted and survival analyses were performed. RESULTS: Of 135 patients and 136 tumors, 117 were glioblastoma multiforme (GBM), 8 were grade III-IV glioma, 4 were anaplastic astrocytoma and 7 were anaplastic oligodendroglioma. One patient had two different lesions, which were GBM and anaplastic astrocytoma respectively. Mean age was 55 (7-85) years, and 88 (65%) were male and 47 (35%) were female. The most common complaint was motor deficit (56%). Fourteen patients underwent reoperation due to recurrent disease. Tumors were most commonly found in the frontal lobe (53, 39%). Magnetic resonance imaging (MRI) features showed that existence of necrosis is strongly related to GBM (p < 0.01). Approximately 126 patients were found to be IDH-wildtype, which changed 6 patients? diagnosis to GBM, IDH wildtype from grade III-IV glioma. Five patients, who were diagnosed with anaplastic astrocytoma and anaplastic oligodendroglioma initially were found to be IDH wildtype. IDH mutation status, extend of resection, and age were found to affect survival. CONCLUSION: IDH mutation status is important in classifying high-grade gliomas, as well as its effects on prognosis. This mutation is related to several radiological features of tumors. Extent of resection and patient age are also profoundly affect survival. Detailing the diagnosis with molecular features will help physicians to shape targeted adjuvant therapies, which would better outcomes.

Identification of Four Metabolic Subtypes of Glioma Based on Glycolysis-Cholesterol Synthesis Genes.

Based on alterations in gene expression associated with the production of glycolysis and cholesterol, this research classified glioma into prognostic metabolic subgroups. In this study, data from the CGGA325 and The Cancer Genome Atlas (TCGA) datasets were utilized to extract single nucleotide variants (SNVs), RNA-seq expression data, copy number variation data, short insertions and deletions (InDel) mutation data, and clinical follow-up information from glioma patients. Glioma metabolic subtypes were classified using the ConsensusClusterPlus algorithm. This study determined four metabolic subgroups (glycolytic, cholesterogenic, quiescent, and mixed). Cholesterogenic patients had a higher survival chance. Genome-wide investigation revealed that inappropriate amplification of MYC and TERT was associated with improper cholesterol anabolic metabolism. In glioma metabolic subtypes, the mRNA levels of mitochondrial pyruvate carriers 1 and 2 (MPC1/2) presented deletion and amplification, respectively. Differentially upregulated genes in the glycolysis group were related to pathways, including IL-17, HIF-1, and TNF signaling pathways and carbon metabolism. Downregulated genes in the glycolysis group were enriched in terpenoid backbone biosynthesis, nitrogen metabolism, butanoate metabolism, and fatty acid metabolism pathway. Cox analysis of univariate and multivariate survival showed that risks of glycolysis subtypes were significantly higher than other subtypes. Those results were validated in the CGGA325 dataset. The current findings greatly contribute to a comprehensive understanding of glioma and personalized treatment.

T2-FLAIR mismatch sign: a roadmap of pearls and pitfalls.

T2-FLAIR mismatch sign has been advocated to be 100% specific for IDH-mutant 1p/19q non-codeleted gliomas (diffuse astrocytomas). However, false positives have been reported in recent works. Loose application of the criteria may lead to erroneous classification, especially by non-trained neuroradiologists. In this pictorial essay, we aim to bring attention to the need for strict criteria for the application of T2-FLAIR mismatch sign and to discuss the potential pitfalls in the application of these criteria. For that, a series of adult brain tumour cases are presented to demonstrate how to apply this radiological sign in the clinical practice.

Glioma-related epilepsy in patients with diffuse high-grade glioma after the 2016 WHO update: seizure characteristics, risk factors, and clinical outcomes.

OBJECTIVE: The aim of this study was to investigate the epidemiological characteristics, associated risk factors, and prognostic value of glioma-related epilepsy in patients with diffuse high-grade gliomas (DHGGs) that were diagnosed after the 2016 updated WHO classification was released. METHODS: Data from 449 patients with DHGGs were retrospectively collected. Definitive diagnosis was reaffirmed according to the 2016 WHO classification. Seizure outcome was assessed using the Engel classification at 12 months after surgery. Univariate and multivariate analyses were performed to identify risk factors associated with preoperative and postoperative glioma-related epilepsy. Lastly, the prognostic value of glioma-related epilepsy was evaluated by Kaplan-Meier and Cox analysis. RESULTS: The incidence of glioma-related epilepsy decreased gradually as the malignancy of the tumor increased. Age < 45 years (OR 2.601, p < 0.001), normal neurological function (OR 3.024, p < 0.001), and lower WHO grade (OR 2.028, p = 0.010) were independently associated with preoperative glioma-related epilepsy, while preoperative glioma-related epilepsy (OR 7.554, p < 0.001), temporal lobe involvement (OR 1.954, p = 0.033), non-gross-total resection (OR 2.286, p = 0.012), and lower WHO grade (OR 2.130, p = 0.021) were identified as independent predictors of poor seizure outcome. Furthermore, postoperative glioma-related epilepsy, rather than preoperative glioma-related epilepsy, was demonstrated as an independent prognostic factor for overall survival (OR 0.610, p = 0.010). CONCLUSIONS: The updated WHO classification seems conducive to reveal the distribution of glioma-related epilepsy in DHGG patients. For DHGG patients with high-risk predictors of poor seizure control, timely antiepileptic interventions could be beneficial. Moreover, glioma-related epilepsy (especially postoperative glioma-related epilepsy) is associated with favorable overall survival.

Application of multiplex ligation-dependent probe amplification (MLPA) and low pass whole genome sequencing (LP-WGS) to the classification / characterisation of low grade glioneuronal tumours.

AIMS: Glioneuronal tumours, although rare, are an important cause of treatment-resistant epilepsy. Differential diagnosis of glioneuronal tumour subtypes is complicated by their variable histological appearance and the lack of pathognomonic histological or molecular biomarkers. In this study we have applied techniques available in a diagnostic laboratory setting to characterise molecular and cytogenetic abnormalities in a single institution cohort of glioneuronal tumours. METHODS: A cohort of 29 glioneuronal tumours that included 21 gangliogliomas and 5 dysembryoplastic neuroepithelial tumours (DNETs) was analysed using low pass whole genome sequencing (WGS) and 2 multiplex ligation-dependent probe amplification (MLPA) central nervous system (CNS) tumour probesets. RESULTS: Low pass WGS identified chromosomal or subchromosomal alterations in 15 specimens. The most common chromosomal alterations were gains of chromosome 7 (n = 8) and chromosome 16 (n = 3). The BRAFV600E mutation was detected by MLPA in 9/21 (42.9%) gangliogliomas and 2/2 pleomorphic xanthoastrocytomas (PXAs). Chromosome 7 gains detected by WGS were reflected in MLPAs by overall gains of chromosome 7 gene probes, including those for BRAF, KIAA1549 and EGFR, while an internal BRAF/MKRN1 duplication was detected in a single ganglioglioma. Homozygous CDKN2A/B loss was detected by MLPA in 3 gangliogliomas, with p16 immunohistochemistry supporting these results. CONCLUSIONS: The combination of low pass WGS and MLPA identifies multiple, diverse genetic and chromosomal alterations in glioneuronal tumours, irrespective of histological tumour grade.

Differential genes and scoring criteria among immunogenomic clusters of lower-grade gliomas.

High incidence of recurrency had been a significant threat among glioma patients. Moreover, the performance of traditional therapies among recurrent gliomas was far from satisfying. Advances in the tumor microenvironment (TME) and immune responses on the brain inspired immunotherapy researches. Nevertheless, verification of classic PD-1/PD-L1 inhibitors failed in phase III clinical trials. Additional gene targets were required for future studies among glioma patients. Immune cell infiltration (ICI) scores, defined based on multiple prognostic genes, were proved as the marker for the sensitivity of immunotherapies in many tumors. However, relevant results were not reported in gliomas. In the study, a retrospective cohort of 495 patients was classified into two ICI score subgroups. High ICI scores were closely related to high tumor mutation burden (TMB) values, indicating a high instability of genes. Furthermore, ICI scores were proved as reliable prognostic predictors. And a predictive model was built based on the ICI scores and multiple clinical features. The model showed its superiority through both internal validation and external validation. The ICI scores and the predictive model showed significant clinical values through decision curve analysis (DCA) since high ICI scores were related to high sensitivity for treatment. The prognostic immune-related gene list provided targets for immunotherapy researches.

TMEM2 Combined with IDH and 1p19q in Refining Molecular Subtypes for Predicting Survival of Patients with Glioma.

Gliomas are common intracranial tumors with high morbidity and mortality in adults. Transmembrane protein 2 (TMEM2) is involved in the malignant behavior of solid tumors. TMEM2 regulates cell adhesion and metastasis as well as intercellular communication by degrading nonprotein components of the extracellular matrix. This study aimed to evaluate the relationship between TMEM2 expression levels and glioma subtypes or patient prognosis. Our findings revealed that TMEM2 expression was abnormally upregulated in high-grade glioma. Moreover, combining TMEM2, the status of isocitrate dehydrogenase (IDH) and 1p19q, we subdivided molecular subtypes with significant differences in survival. Patients in the MT-codel-low subgroup had better prognosis than those in the WT-no-codel-high subgroup, who fared the worst. Additionally, correlation analysis of TMEM2 and immune cell infiltration indicated an altered tumor microenvironment (TME) and cell redistribution in the TMEM2 high-expression subtype. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that focal adhesion and PI3K-Akt signaling pathways were enriched in the TMEM2-expressing group. In conclusion, aberrant TMEM2 expression can be used as an independent prognostic marker for refining glioma molecular subtyping and accurate prognosis. These findings will improve rational decision making to provide individualized therapy for patients with glioma.

Molecular subtype impacts surgical resection in low-grade gliomas: A Chinese Glioma Genome Atlas database analysis.

Surgeons have considered extending the resection margins for better outcomes in gliomas, but have not considered molecular pathology. We investigated the impact of molecular pathology on the surgical benefit in gliomas. Herein, we collected the clinical and pathological information of 449 patients with glioma from the Chinese Glioma Genome Atlas database, and enrolled those who underwent surgical resection. We measured the impact of the extent of resection on survival time in subgroups classified by clinical characteristics. We found that gross total resection (GTR) was associated with longer survival times in the entire cohort, and each of the three molecular subtypes. Even after age stratification, there was no survival benefit from GTR in those with a Karnofsky performance score (KPS) ≤ 80. In patients aged >45 years with a KPS >80, extensive resection resulted in longer survival times in isocitrate dehydrogenase-mutated astrocytomas. Additionally, GTR was associated with longer overall survival times in patients aged ≤45 years with a KPS >80. In conclusion, extensive resection does not always prolong survival in patients with glioma. Along with clinical characteristics, molecular pathology positively impacts survival in gliomas. Neurosurgeons may consider our findings when planning surgery in the future.

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 4th 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.

The impact of the molecular classification of glioblastoma on the interpretation of therapeutic clinical trial results.

In 2016, the World Health Organization (WHO) released the most recent update to the classification of central nervous system tumors. This update has led to the reshaping of tumor identification and subsequently changed current understanding of treatment options for patients. Moreover, the restructuring of the classification of central nervous system tumors to include molecular markers has led to the need to re-evaluate how to interpret pivotal trials. These trials originally enrolled patients purely based upon histologic diagnoses without the use of adjunctive, and frequently diagnostic molecular testing. With this new paradigm also comes the need to assess how one should incorporate molecular markers into current trials as well as shape future trials. First, we will discuss updates on the molecular classification of glioblastoma (GBM) (and its histologic mimics). This will be followed by a review of key pivotal trials which have defined our standard of care for glioblastoma within the context of molecular classification of their study populations. This will be followed by preliminary results of ongoing phase 3 cooperative group trials for high-grade gliomas that were initiated prior to routine molecular classification of tumors and how one could interpret these results in light of advances in molecular classification. Finally, we will end with suggestions for future clinical trial design with a focus on enrollment based upon molecular diagnostics.

Evidence-based recommendations on categories for extent of resection in diffuse glioma.

Surgical resection represents the standard of care in diffuse glioma, and more extensive tumour resection appears to be associated with favourable outcome. Up to now, terminology to describe extent of resection has been inconsistently applied across clinical trials which hampers comparative analysis of cohorts between different studies. Based on a comprehensive literature review, we developed evidence-based expert recommendations on categories for extent of resection. Recommendations are formulated for the categories 'biopsy', 'partial resection', 'subtotal resection', 'near total resection', 'complete resection' and 'supramaximal resection'. Definitions rest on reduction of contrast- and non-contrast-enhancing tumour in glioblastoma, and on reduction of T2/FLAIR-hyperintense tumour in gliomas WHO grade 2 or 3. Both relative reduction of tumour volume (in percentage) as a measurement of surgical efficacy and absolute residual tumour volume (in cm3) as a measurement of remaining tumour burden are incorporated into the categories for extent of resection. Class of evidence for the proposed categories ranges from class IIB to IV. Limitations of the suggested categories are discussed. The proposed categories on extent of resection offer a framework to standardize nomenclature based on previous studies, and will need to be evaluated in prospective, molecularly well-defined cohorts. Our categories may eventually help as a stratification factor for future clinical trials.

Pituicytoma: Case report of a rare suprasellar tumor.

Pituicytoma is a distinct sellar or supracellar tumor which originates from specialized glial cells of neurohypophyses and infundibulum known as pituicytes. Because of its sellar location patients present with headache, visual disturbance, and endocrine abnormalities. Pituicytoma is difficult to diagnose on neuroimaging as radiological features overlap with other more common tumors of this region. Thus, diagnosis is established by histopathology and immunohistochemistry of resected tumor only. Pituicytomas are composed of bipolar spindle cells arranged as fascicles and are immunoreactive for TTF-1, S100p, and vimentin. These tumors are extremely rare and only around 70 published cases are known in literature. We report a case of suprasellar SOL in a 58-year-old male who presented with headache and gradual visual deterioration in both eyes. He was diagnosed as a case of pituicytoma based on light microscopy findings and immunohistochemical expression of TTF-1, vimentin, S100p, and bcl-2.

Characterization of primary glioma cell lines derived from the patients according to 2016 CNS tumour WHO classification and comparison with their parental tumours.

BACKGROUND: Gliomas represent about 80% of primary brain tumours and about 30% of malignant ones, which today don't have a resolution therapy because of their variability. A valid model for the study of new personalized therapies can be represented by primary cultures from patient's tumour biopsies. METHODS: In this study we consider 12 novel cell lines established from patients' gliomas and immunohistochemically and molecularly characterized according to the newly updated 2016 CNS Tumour WHO classification. RESULTS: Eight of these lines were glioblastoma cells, two grade III glioma cells (anaplastic astrocytoma and oligo astrocytoma) and two low grade glioma cells (grade II astrocytoma and oligodendroglioma). All cell lines were analysed by immunohistochemistry for specific glioma markers, respectively VIMENTIN, GFAP, IDH1R132, and ATRX. The methylation status of the MGMT gene promoter was also determined in all lines. The comparison of the immunohistochemical characteristics and of the MGMT methylation status of the lines with the tissues of origin shows that the cells in culture maintain the same characteristics. CONCLUSIONS: Human cancer cell lines represent a support in the knowledge of tumour biology and in drug discovery through its facile experimental manipulation. TRIAL REGISTRATION: NCT04180046.

Magnetic Resonance Features of Lower-grade Gliomas in Prediction of the Reverse Phase Protein A.

OBJECTIVES: The Cancer Genome Atlas Research Network identified 4 novel protein expression-defined subgroups in patients with lower-grade gliomas (LGGs). The RPPA3 subtype had high levels of Epidermal Growth Factor Receptor and Human epidermal growth factor receptor-2, further increasing the chances for targeted therapy. In this study, we aimed to explore the relationships between magnetic resonance features and reverse phase protein array (RPPA) subtypes (R1-R4). METHODS: Survival estimates for the Cancer Genome Atlas cohort were generated using the Kaplan-Meier method and time-dependent receiver operating characteristic curves. A total of 153 patients with LGG with brain magnetic resonance imaging from The Cancer Imaging Archive were retrospectively analyzed. Least absolute shrinkage and selection operator algorithm was used to reduce the feature dimensions of the RPPA3 subtype. RESULTS: A total of 51 (33.3%) RPPA1 subtype, 42 (27.4) RPPA2 subtype, 19 (12.4%) RPPA3 subtype, and 38 (24.8%) RPPA4 subtype were identified. On multivariate logistic regression analysis, subventricular zone involvement [odds ratio (OR), 0.370; P = 0.006; 95% confidence interval (CI), 0.181-0.757) was associated with RPPA1 subtype [area under the curve (AUC), 0.598]. Volume of 60 cm3 or greater (OR, 5.174; P < 0.001; 95% CI, 2.182-12.267) was associated with RPPA2 subtype (AUC, 0.684). Proportion contrast-enhanced tumor greater than 5% (OR, 4.722; P = 0.010; 95% CI, 1.456-15.317), extranodular growth (OR, 5.524; P = 0.010; 95% CI, 1.509-20.215), and L/CS ratio equal to or greater than median (OR, 0.132; P = 0.003; 95% CI, 0.035-0.500) were associated with RPPA3 subtype (AUC, 0.825). Proportion contrast-enhanced tumor greater than 5% (OR, 0.206; P = 0.005; 95% CI, 0.068-0.625) was associated with RPPA4 subtype (AUC, 0.638). For the prediction of RPPA3 subtype, the nomogram showed good discrimination, with an AUC of 0.825 (95% CI, 0.711-0.939) and was well calibrated. The RPPA3 subtype was associated with shortest mean overall survival (RPPA3 subtype vs other: 613 vs 873 days; P < 0.05). The time-dependent receiver operating characteristic curves for the RPPA3 subtype was 0.72 (95% CI, 0.60-0.84) for survival at 1 year. Decision curve analysis indicated that prediction for the RPPA3 model was clinically useful. CONCLUSIONS: The RPPA3 subtype is an unfavorable prognostic biomarker for overall survival in patients with LGG. Radiogenomics analysis of magnetic resonance features can predict the RPPA subtype preoperatively and may be of clinical value in tailoring the management strategies in patients with LGG.

IDH-Mutant Low-grade Glioma: Advances in Molecular Diagnosis, Management, and Future Directions.

PURPOSE OF REVIEW: IDH-mutant low-grade gliomas (LGG) have emerged as a distinct clinical and molecular entity with unique treatment considerations. Here, we review updates in IDH-mutant LGG diagnosis and classification, imaging biomarkers, therapies, and neurocognitive and patient-reported outcomes. RECENT FINDINGS: CDKN2A/B homozygous deletion in IDH-mutant astrocytoma is associated with shorter survival, similar to WHO grade 4. The T2-FLAIR mismatch, a highly specific but insensitive sign, is diagnostic of IDH-mutant astrocytoma. Maximal safe resection is currently indicated in all LGG cases. Radiotherapy with subsequent PCV (procarbazine, lomustine, vincristine) provides longer overall survival compared to radiotherapy alone. Temozolomide in place of PCV is reasonable, but high-level evidence is still lacking. LGG adjuvant treatment has important quality of life and neurocognitive side effects that should be considered. Although incurable, IDH-mutant LGG have a favorable survival compared to IDH-WT glioma. Recent advances in molecular-based classification, imaging, and targeted therapies will hopefully improve survival and quality of life.