Association Between Pretreatment 11C-Methionine Positron Emission Tomography Metrics, Histology, and Prognosis in 125 Newly Diagnosed Patients with Adult-Type Diffuse Glioma Based on the World Health Organization 2021Classification

OBJECTIVE

To clarify the relationships between 11C-methionine (MET) positron emission tomography (PET) metrics and the histology, genetics, and prognosis of adult-type diffuse glioma (ADG) based on the World Health Organization (WHO) 2021 classification.

METHODS

A total of 125 newly diagnosed patients with ADG were enrolled. We compared the maximum standardized uptake value (SUVmax), tumor-to-normal background ratio (TNR), metabolic tumor volume (MTV), and total lesion methionine uptake (TLMU) to the histology and genetics of the patients with ADG. We also evaluated the prognoses of the 93 surgically treated patients.

RESULTS

The patients with isocitrate dehydrogenase wild ADG showed significantly higher MET-PET metrics (P < 0.05 for all parameters), significantly shorter overall survival and progression-free survival (P < 0.0001 for both) than those of the patients with isocitrate dehydrogenase mutant (IDHm) ADG. In the IDHm ADG group, the SUVmax, MTV, and TLMU values were significantly higher in patients with IDHm grade (G) 4 astrocytoma than patients with IDHm G2/3 astrocytoma (P < 0.05 for all), but not than patients with G2-3 oligodendroglioma. The progression-free survival was significantly shorter in the patients with G4 astrocytoma versus the patients with G2/3 astrocytoma and G3 oligodendroglioma (P < 0.05 for both). The SUVmax and TNR values were significantly higher in recurrent patients than nonrecurrent patients (P < 0.01 for both), but no significant differences were found in MTV or TLMU values.

CONCLUSIONS

MET-PET metrics well reflect the histological subtype, WHO grade and prognosis of ADG based on the 2021 WHO classification, with the exception of oligodendroglial tumors. Volumetric parameters were not significantly associated with recurrence, unlike the SUVmax and TNR.

Review on neuroimaging in pediatric-type diffuse low-grade gliomas

The fifth edition of the World Health Organization Classification of Tumors of the Central Nervous System (WHO CNS5) has identified a new classification system for tumors of the brain and spinal cord, highlighting the pivotal role of molecular diagnosis in accurately categorizing neoplasms. In addition to previous classifications, one of the key distinctions lies in categorizing pediatric-type diffuse low-grade gliomas (pDLGGs) and pediatric-type diffuse high-grade gliomas (pDHGGs) as distinct tumor types. Although similar in histology and morphology, pediatric diffuse gliomas are completely different from the adult type with respect to the molecular genetic characteristics, prognosis, and treatment strategies. pDLGG includes four tumor types, namely, diffuse astrocytoma, MYB- or MYBL1-altered; angiocentric glioma; polymorphous low-grade neuroepithelial tumor of the young (PLNTY); and diffuse low-grade glioma, MAPK pathway-altered, three types of which are newly recognized tumor types. Herein, we review the clinical characteristics, histopathological and molecular genetic characteristics, neuroimaging features, and prognosis of pDLGG and summarize the neuroimaging key points in diagnosing different tumor types. This review aims to evaluate and update the relevant pDLGG features and advances in neuroimaging that may assist in differential diagnosis, surgery planning, and prognostic determination of these tumor types and provide accurate diagnostic information for clinical colleagues.

Cytopathology of glioneuronal and neuronal tumours with histological correlations

Glioneuronal and neuronal tumours constitute a diverse group of tumours that feature neuronal differentiation. In mixed glioneuronal tumours, a glial component is present in addition to the neuronal component. With a few exceptions (eg diffuse leptomeningeal glioneuronal tumour) they are well-circumscribed and slow-growing tumours, which is why their prognosis is intrinsically favourable after gross total resection. Rendering an intraoperative diagnosis of glioneuronal/neuronal tumour is therefore important-neurosurgeons should remove them to prevent the persistence of clinical symptoms and/or recurrence. In this context, cytopathological examination can be especially useful for assessing cellular details when frozen section artefacts render poor-quality preparations, as is the case for this group of tumours, which are frequently mistaken for infiltrating gliomas (eg diffuse astrocytoma infiltrating grey matter, oligodendroglioma) on frozen section slides. The aim of this article is to review the cytomorphological features of glioneuronal and neuronal tumours according to the 2021 World Health Organization classification of central nervous system tumours, 5th edition. Additionally, since interpretation in intraoperative cytology relies on intuiting tissue patterns from cytology preparations, representative histological figures of all discussed entities have been included. Clues for specific diagnoses and the primary diagnostic problems encountered during intraoperative procedures are also discussed.

The Role of Advanced MRI Sequences in the Diagnosis and Follow-Up of Adult Brainstem Gliomas: A Neuroradiological Review

The 2021 WHO (World Health Organization) classification of brain tumors incorporated the rapid advances in the molecular, genetic, and pathogenesis understanding of brain tumor pathogenesis, behavior, and treatment response. It revolutionized brain tumor classification by placing great emphasis on molecular types and completely splitting adult-type and pediatric-type diffuse gliomas. Brainstem gliomas (BSGs) are the leading primary tumors of the brainstem, although they are quite uncommon in adults compared with the pediatric population, representing less than 2% of adult gliomas. Surgery is not always the treatment of choice since resection is rarely feasible and does not improve overall survival, and biopsies are not generally performed since the location is treacherous. Therefore, MRI (Magnetic Resonance Imaging) without and with gadolinium administration represents the optimal noninvasive radiological technique to suggest brainstem gliomas diagnosis, plan a multidisciplinary treatment and for follow-up evaluations. The MRI protocol encompasses morphological sequences as well as functional and advanced sequences, such as DWI/ADC (Diffusion-Weighted Imaging/Apparent Diffusion Coefficient), DTI (Diffusion Tensor Imaging), PWI (Perfusion-Weighted Imaging), and MRS (Magnetic Resonance Spectroscopy), which improve the accuracy of the diagnosis of BSGs by adding substantial information regarding the cellularity, the infiltrative behavior toward the v fiber tracts, the vascularity, and the molecular changes. Brainstem gliomas have been divided into four categories on the basis of their MRI radiological appearance, including diffuse intrinsic low-grade gliomas, enhancing malignant gliomas, localized tectal gliomas, and other forms. The aim of our review is to provide insight into the role of advanced MRI sequences in the diagnosis and follow-up of adult brainstem gliomas.

A CT-based nomogram for predicting the risk of adenocarcinomas in patients with subsolid nodule according to the 2021 WHO classification

Purpose

To establish a nomogram for predicting the risk of adenocarcinomas in patients with subsolid nodules (SSNs) according to the 2021 WHO classification.

Methods

A total of 656 patients who underwent SSNs resection were retrospectively enrolled. Among them, 407 patients were assigned to the derivation cohort and 249 patients were assigned to the validation cohort. Univariate and multi-variate logistic regression algorithms were utilized to identity independent risk factors of adenocarcinomas. A nomogram based on the risk factors was generated to predict the risk of adenocarcinomas. The discrimination ability of the nomogram was evaluated using the concordance index (C-index), its performance was calibrated using a calibration curve, and its clinical significance was evaluated using decision curves and clinical impact curves.

Results

Lesion size, mean CT value, vascular change and lobulation were identified as independent risk factors for adenocarcinomas. The C-index of the nomogram was 0.867 (95% CI, 0.833-0.901) in derivation cohort and 0.877 (95% CI, 0.836-0.917) in validation cohort. The calibration curve showed good agreement between the predicted and actual risks. Analysis of the decision curves and clinical impact curves revealed that the nomogram had a high standardized net benefit.

Conclusions

A nomogram for predicting the risk of adenocarcinomas in patients with SSNs was established in light of the 2021 WHO classification. The developed model can be adopted as a pre-operation tool to improve the surgical management of patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40644-022-00483-1.

[The 2021 WHO classification of tumours of the central nervous system]

Rapid technical advances in molecular biology allowed for the identification of key genetic alterations in central nervous system (CNS) tumors. Our ever-expanding knowledge of brain tumor genetics and the development of new technologies, such as DNA-methylation profiling, required an update of the 2016 fourth edition of the WHO classification of CNS tumors. Updates were regularly published by the Consortium to Inform Molecular Practical Approaches to CNS Tumor Taxonomy-Not Official WHO (c-IMPACT-NOW) until the publication of the fifth edition of the WHO classification of CNS tumors in 2021. In that edition, new types and subtypes are introduced and criteria for histo-molecular diagnostic and grading are refined, especially for diffuse gliomas. The definition of a broad category "diffuse glioma, pediatric subtype" (low or high grade) is a major improvement of the classification. Moreover, the nomenclature was simplified and aligned with that of other blue books. The 2021 edition truly advances the role of molecular diagnostics in CNS tumor classification. Methyloma profiling may become a cornerstone of CNS tumor diagnostic. The new WHO classification will lead to better management of brain tumor patients.