MRI features as a helpful tool to predict the molecular subgroups of medulloblastoma: state of the art

Posterior fossa tumors in children: current insights

While in adults most intracranial tumors develop around the cerebral hemispheres, 45 to 60% of pediatric lesions are found in the posterior fossa, although this anatomical region represents only 10% of the intracranial volume. The latest edition of the WHO classification for CNS tumors presented some fundamental paradigm shifts that particularly affected the classification of pediatric tumors, also influencing those that affect posterior fossa. Molecular biomarkers play an important role in the diagnosis, prognosis, and treatment of childhood posterior fossa tumors and can be used to predict patient outcomes and response to treatment and monitor its effectiveness. Although genetic studies have identified several posterior fossa tumor types, differing in terms of their location, cell of origin, genetic mechanisms, and clinical behavior, recent management strategies still depend on uniform approaches, mainly based on the extent of resection. However, significant progress has been made in guiding therapy decisions with biological or molecular stratification criteria and utilizing molecularly targeted treatments that address specific tumor biological characteristics. The primary focus of this review is on the latest advances in the diagnosis and treatment of common subtypes of posterior fossa tumors in children, as well as potential therapeutic approaches in the future.   Conclusion: Molecular biomarkers play a central role, not only in the diagnosis and prognosis of posterior fossa tumors in children but also in customizing treatment plans. They anticipate patient outcomes, measure treatment responses, and assess therapeutic effectiveness. Advances in neuroimaging and treatment have significantly enhanced outcomes for children with these tumors. What is Known: • Central nervous system tumors are the most common solid neoplasms in children and adolescents, with approximately 45 to 60% of them located in the posterior fossa. • Multimodal approaches that include neurosurgery, radiation therapy, and chemotherapy are typically used to manage childhood posterior fossa tumors What is New: • Notable progress has been achieved in the diagnosis, categorization and management of posterior fossa tumors in children, leading to improvement in survival and quality of life.

Prognostic significance of molecular subgroups in survival outcome for children with medulloblastoma in Malaysia

Introduction

Advancements in genomic profiling led to the discovery of four major molecular subgroups in medulloblastoma (MB), which have now been incorporated into the World Health Organization classification of central nervous system tumors. The current study aimed to determine the prognostic significance of the MB molecular subgroups among children in Malaysia.

Methods

We assembled MB samples from children <18 years between January 2003 and June 2017 from four pediatric oncology centers in Malaysia. MB was sub-grouped using 850k DNA methylation testing at German Cancer Research Centre, Heidelberg, Germany.

Results

Fifty samples from patients diagnosed and treated as MB were identified. Two (4%) of the 50 patients' tumor DNA samples were insufficient for analysis. Of the remaining 48 patients, 41 (85%) samples were confirmed as MB, while for 7 (15%) patients, DNA methylation classification results were discrepant with the histopathological diagnosis of MB, with various other diagnoses. Of the 41 MB patients, 15 patients were stratified as standard-risk (SR), 16 patients as high-risk (HR), and ten as infants (age <3 years old). Molecular subgrouping of the whole cohort revealed four (14%) WNT, 11 (27%) SHH, 10 (24%) Group 3, and 16 (39%) Group 4. Treatment abandonment rates for older children and infants were 22.5% and 10%, respectively. After censoring treatment abandonment, for SR patients, the 5-year event-free survival (EFS) and overall survival (OS) were 43.1% ± 14.7% and 46.9 ± 15.6%, respectively, while in HR, 5-year EFS and OS were both 63.6% ± 14.5%. Infants had a 5-year EFS and OS of 55.6% ± 16.6% and 66.7% ± 15.7%, respectively. WNT tumors had the best 5y-OS, followed by Group 3, Group 4, and SHH in children ≥3 years old. In younger children, SHH MB patients showed favorable outcomes.

Conclusion

The study highlights the importance of DNA methylation profiling for diagnostic accuracy. Most infants had SHH MB, and their EFS and OS were comparable to those reported in high-income countries. Due to the relatively small cohort and the high treatment abandonment rate, definite conclusions cannot be made regarding the prognostic significance of molecular subgroups of MB. Implementing this high-technology investigation would assist pathologists in improving the diagnosis and provide molecular subgrouping of MB, permitting subgroup-specific therapies.

Preoperative prediction of sonic hedgehog and group 4 molecular subtypes of pediatric medulloblastoma based on radiomics of multiparametric MRI combined with clinical parameters

Purpose

To construct a machine learning model based on radiomics of multiparametric magnetic resonance imaging (MRI) combined with clinical parameters for predicting Sonic Hedgehog (SHH) and Group 4 (G4) molecular subtypes of pediatric medulloblastoma (MB).

Methods

The preoperative MRI images and clinical data of 95 patients with MB were retrospectively analyzed, including 47 cases of SHH subtype and 48 cases of G4 subtype. Radiomic features were extracted from T1-weighted imaging (T1), contrast-enhanced T1 weighted imaging (T1c), T2-weighted imaging (T2), T2 fluid-attenuated inversion recovery imaging (T2FLAIR), and apparent diffusion coefficient (ADC) maps, using variance thresholding, SelectKBest, and Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithms. The optimal features were filtered using LASSO regression, and a logistic regression (LR) algorithm was used to build a machine learning model. The receiver operator characteristic (ROC) curve was plotted to evaluate the prediction accuracy, and verified by its calibration, decision and nomogram. The Delong test was used to compare the differences between different models.

Results

A total of 17 optimal features, with non-redundancy and high correlation, were selected from 7,045 radiomics features, and used to build an LR model. The model showed a classification accuracy with an under the curve (AUC) of 0.960 (95% CI: 0.871-1.000) in the training cohort and 0.751 (95% CI: 0.587-0.915) in the testing cohort, respectively. The location of the tumor, pathological type, and hydrocephalus status of the two subtypes of patients differed significantly (p < 0.05). When combining radiomics features and clinical parameters to construct the combined prediction model, the AUC improved to 0.965 (95% CI: 0.898-1.000) in the training cohort and 0.849 (95% CI: 0.695-1.000) in the testing cohort, respectively. There was a significant difference in the prediction accuracy, as measured by AUC, between the testing cohorts of the two prediction models, which was confirmed by Delong's test (p = 0.0144). Decision curves and nomogram further validate that the combined model can achieve net benefits in clinical work.

Conclusion

The combined prediction model, constructed based on radiomics of multiparametric MRI and clinical parameters can potentially provide a non-invasive clinical approach to predict SHH and G4 molecular subtypes of MB preoperatively.

An Analysis of the Effects of In Vitro Photodynamic Therapy on Prostate Cancer Tissue by Histopathological Examination and Magnetic Resonance Imaging

Prostate cancer can significantly shorten the lifetime of a patient, even if he is diagnosed at an early stage. The development of minimally-invasive focal therapies such as photodynamic therapy to reduce the number of neoplastic cells while sparing delicate structures is extremely advantageous for treating prostate cancer. This study investigates the effect of photodynamic therapy performed in prostate tissue samples in vitro, using quantitative magnetic resonance imaging and histopathological analysis. Prostate tissue samples were treated with oxygenated solutions of Rose Bengal (RB) or protoporphyrin IX disodium salt (PpIX), illuminated with visible light, and then analyzed for changes in morphology by microscopy and by measurement of spin–lattice and spin–spin relaxation times at 1.5 Tesla. In the treated prostate tissue samples, histopathological images revealed chromatin condensation and swelling of the stroma, and in some cases, thrombotic necrosis and swelling of the stroma accompanied by pyknotic nuclei occurred. Several samples had protein fragments in the stroma. Magnetic resonance imaging of the treated prostate tissue samples revealed differences in the spin–lattice and spin–spin relaxation times prior to and post photodynamic action.

Advanced Neuroimaging Approaches to Pediatric Brain Tumors

Simple Summary

After leukemias, brain tumors are the most common cancers in children, and early, accurate diagnosis is critical to improve patient outcomes. Beyond the conventional imaging methods of computed tomography (CT) and magnetic resonance imaging (MRI), advanced neuroimaging techniques capable of both structural and functional imaging are moving to the forefront to improve the early detection and differential diagnosis of tumors of the central nervous system. Here, we review recent developments in neuroimaging techniques for pediatric brain tumors.

Abstract

Central nervous system tumors are the most common pediatric solid tumors; they are also the most lethal. Unlike adults, childhood brain tumors are mostly primary in origin and differ in type, location and molecular signature. Tumor characteristics (incidence, location, and type) vary with age. Children present with a variety of symptoms, making early accurate diagnosis challenging. Neuroimaging is key in the initial diagnosis and monitoring of pediatric brain tumors. Conventional anatomic imaging approaches (computed tomography (CT) and magnetic resonance imaging (MRI)) are useful for tumor detection but have limited utility differentiating tumor types and grades. Advanced MRI techniques (diffusion-weighed imaging, diffusion tensor imaging, functional MRI, arterial spin labeling perfusion imaging, MR spectroscopy, and MR elastography) provide additional and improved structural and functional information. Combined with positron emission tomography (PET) and single-photon emission CT (SPECT), advanced techniques provide functional information on tumor metabolism and physiology through the use of radiotracer probes. Radiomics and radiogenomics offer promising insight into the prediction of tumor subtype, post-treatment response to treatment, and prognostication. In this paper, a brief review of pediatric brain cancers, by type, is provided with a comprehensive description of advanced imaging techniques including clinical applications that are currently utilized for the assessment and evaluation of pediatric brain tumors.

New Developments in the Pathogenesis, Therapeutic Targeting, and Treatment of Pediatric Medulloblastoma

Pediatric medulloblastoma (MB) is the most common pediatric brain tumor with varying prognoses depending on the distinct molecular subtype. The four consensus subgroups are WNT, Sonic hedgehog (SHH), Group 3, and Group 4, which underpin the current 2021 WHO classification of MB. While the field of knowledge for treating this disease has significantly advanced over the past decade, a deeper understanding is still required to improve the clinical outcomes for pediatric patients, who are often vulnerable in ways that adult patients are not. Here, we discuss how recent insights into the pathogenesis of pediatric medulloblastoma have directed current and future research. This review highlights new developments in understanding the four molecular subtypes’ pathophysiology, epigenetics, and therapeutic targeting. In addition, we provide a focused discussion of recent developments in imaging, and in the surgery, chemotherapy, and radiotherapy of pediatric medulloblastoma. The article includes a brief explanation of healthcare costs associated with medulloblastoma treatment.

Embryonal and non-meningothelial mesenchymal tumors of the central nervous system - Advances in diagnosis and prognostication

The 5th edition of the WHO Classification of Tumours of the Central Nervous System introduces new entities, and provides updated guidance regarding the diagnostic criteria for tumors of the central nervous system (CNS). CNS embryonal tumors and CNS non‐meningothelial mesenchymal tumors can be challenging for practicing pathologists, as the histologic features are not always specific to a particular entity, and integration of microscopic and molecular findings is necessary. This review on CNS embryonal and non‐meningothelial mesenchymal tumors is meant to provide an update with a focus on WHO changes and additions and on recent discoveries with diagnostic, prognostic, and therapeutic implications.

Case Report: Primary Leptomeningeal Medulloblastoma in a Child: Clinical Case Report and Literature Review

Medulloblastoma is one of the most common pediatric central nervous system malignancies worldwide, and it is characterized by frequent leptomeningeal metastasizing. We report a rare case of primary leptomeningeal medulloblastoma of an 11-year-old Caucasian girl with a long-term disease history, non-specific clinical course, and challenges in the diagnosis verification. To date, 4 cases of pediatric primary leptomeningeal medulloblastoma are reported, and all of them are associated with unfavorable outcomes. The approaches of neuroimaging and diagnosis verification are analyzed in the article to provide opportunities for effective diagnosis of this disease in clinical practice. The reported clinical case of the primary leptomeningeal medulloblastoma is characterized by MR images with non-specific changes in the brain and spinal cord and by 18FDG-PET/CT images with diffuse heterogeneous hyperfixation of the radiopharmaceutical along the whole spinal cord. The immunohistochemistry and next-generation sequencing analyses of tumor samples were performed for comprehensive characterization of the reported clinical case.

Magnetic Resonance Imaging in the Contemporary Management of Medulloblastoma: Current and Emerging Applications

Medulloblastoma, the most common malignant primary brain tumor in children, is now considered to comprise of four distinct molecular subgroups-wingless (WNT), sonic hedgehog (SHH), Group 3, and Group 4 medulloblastoma, each associated with distinct developmental origins, unique transcriptional profiles, diverse phenotypes, and variable clinical behavior. Due to its exquisite anatomic resolution, multiparametric nature, and ability to image the entire craniospinal axis, magnetic resonance imaging (MRI) is the preferred and recommended first-line imaging modality for suspected brain tumors including medulloblastoma. Preoperative MRI can reliably differentiate medulloblastoma from other common childhood posterior fossa masses such as ependymoma, pilocytic astrocytoma, and brainstem glioma. On T1-weighted images, medulloblastoma is generally iso- to hypointense, while on T2-weighted images, the densely packed cellular component of the tumor is significantly hypointense and displays restricted diffusion on diffusion-weighted imaging. Following intravenous gadolinium, medulloblastoma shows significant but variable and heterogeneous contrast enhancement. Given the propensity of neuraxial spread in medulloblastoma, sagittal fat-suppressed T1-postcontrast spinal MRI is recommended to rule out leptomeningeal metastases for accurate staging. Following neurosurgical excision, postoperative MRI done within 24-48 h confirms the extent of resection, accurately quantifying residual tumor burden imperative for risk assignment. Post-treatment MRI is needed to assess response and effectiveness of adjuvant radiotherapy and systemic chemotherapy. After completion of planned therapy, surveillance MRI is recommended periodically on follow-up for early detection of recurrence for timely institution of salvage therapy, as well as for monitoring treatment-related late complications. Recent studies suggest that preoperative MRI can reliably identify SHH and Group 4 medulloblastoma but has suboptimal predictive accuracy for WNT and Group 3 tumors. In this review, we focus on the role of MRI in the diagnosis, staging, and quantifying residual disease; post-treatment response assessment; and periodic surveillance, and provide a brief summary on radiogenomics in the contemporary management of medulloblastoma.

Medulloblastoma Associated with Down Syndrome: From a Rare Event Leading to a Pathogenic Hypothesis

Down syndrome (DS) is the most common chromosome abnormality with a unique cancer predisposition syndrome pattern: a higher risk to develop acute leukemia and a lower incidence of solid tumors. In particular, brain tumors are rarely reported in the DS population, and biological behavior and natural history are not well described and identified. We report a case of a 10-year-old child with DS who presented with a medulloblastoma (MB). Histological examination revealed a classic MB with focal anaplasia and the molecular profile showed the presence of a CTNNB1 variant associated with the wingless (WNT) molecular subgroup with a good prognosis in contrast to our case report that has shown an early metastatic relapse. The nearly seven-fold decreased risk of MB in children with DS suggests the presence of protective biological mechanisms. The cerebellum hypoplasia and the reduced volume of cerebellar granule neuron progenitor cells seem to be a possible favorable condition to prevent MB development via inhibition of neuroectodermal differentiation. Moreover, the NOTCH/WNT dysregulation in DS, which is probably associated with an increased risk of leukemia, suggests a pivotal role of this pathway alteration in the pathogenesis of MB; therefore, this condition should be further investigated in future studies by molecular characterizations.

Medulloblastoma in adults - reviewing the literature from a surgeon's point of view

Medulloblastoma is a common primary brain tumor in children but it is a rare cancer in adult patients. We reviewed the literature, searching PubMed for articles on this rare tumor entity, with a focus on tumor biology, advanced neurosurgical opportunities for safe tumor resection, and multimodal treatment options. Adult medulloblastoma occurs at a rate of 0.6 per one million people per year. There is a slight disparity between male and female patients, and patients with a fair skin tone are more likely to have a medulloblastoma. Patients present with cerebellar signs and signs of elevated intracranial pressure. Diagnostic efforts should consist of cerebral MRI and MRI of the spinal axis. Cerebrospinal fluid should be investigated to look for tumor dissemination. Medulloblastoma tumors can be classified as classic, desmoplastic, anaplastic, and large cell, according to the WHO tumor classification. Molecular subgroups include WNT, SHH, group 3, and group 4 tumors. Further molecular analyses suggest that there are several subgroups within the four existing subgroups, with significant differences in patient age, frequency of metastatic spread, and patient survival. As molecular markers have started to play an increasing role in determining treatment strategies and prognosis, their importance has increased rapidly. Treatment options include microsurgical tumor resection and radiotherapy and, in addition, chemotherapy that respects the tumor biology of individual patients offers targeted therapeutic approaches. For neurosurgeons, intraoperative imaging and tumor fluorescence may improve resection rates. Disseminated disease, residual tumor after surgery, lower radiation dose, and low Karnofsky performance status are all suggestive of a poor outcome. Extraneural spread occurs only in very few cases. The reported 5-year-survival rates range between 60% and 80% for all adult medulloblastoma patients.

Construction and Validation of a 13-Gene Signature for Prognosis Prediction in Medulloblastoma

Background: Recent studies have identified several molecular subgroups of medulloblastoma associated with distinct clinical outcomes; however, no robust gene signature has been established for prognosis prediction. Our objective was to construct a robust gene signature-based model to predict the prognosis of patients with medulloblastoma.

Methods: Expression data of medulloblastomas were acquired from the Gene Expression Omnibus (GSE85217, n = 763; GSE37418, n = 76). To identify genes associated with overall survival (OS), we performed univariate survival analysis and least absolute shrinkage and selection operator (LASSO) Cox regression. A risk score model was constructed based on selected genes and was validated using multiple datasets. Differentially expressed genes (DEGs) between the risk groups were identified. Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and protein–protein interaction (PPI) analyses were performed. Network modules and hub genes were identified using Cytoscape. Furthermore, tumor microenvironment (TME) was evaluated using ESTIMATE algorithm. Tumor-infiltrating immune cells (TIICs) were inferred using CIBERSORTx.

Results: A 13-gene model was constructed and validated. Patients classified as high-risk group had significantly worse OS than those as low-risk group (Training set: p < 0.0001; Validation set 1: p < 0.0001; Validation set 2: p = 0.00052). The area under the curve (AUC) of the receiver operating characteristic (ROC) analysis indicated a good performance in predicting 1-, 3-, and 5-year OS in all datasets. Multivariate analysis integrating clinical factors demonstrated that the risk score was an independent predictor for the OS (validation set 1: p = 0.001, validation set 2: p = 0.004). We then identified 265 DEGs between risk groups and PPI analysis predicted modules that were highly related to central nervous system and embryonic development. The risk score was significantly correlated with programmed death-ligand 1 (PD-L1) expression (p < 0.001), as well as immune score (p = 0.035), stromal score (p = 0.010), and tumor purity (p = 0.010) in Group 4 medulloblastomas. Correlations between the 13-gene signature and the TIICs in Sonic hedgehog and Group 4 medulloblastomas were revealed.

Conclusion: Our study constructed and validated a robust 13-gene signature model estimating the prognosis of medulloblastoma patients. We also revealed genes and pathways that may be related to the development and prognosis of medulloblastoma, which might provide candidate targets for future investigation.

Embryonal Tumors of the Central Nervous System: An Update

Embryonal tumors of the central nervous system (CNS) are rare, high-grade neoplasms predominantly affecting the pediatric population. Well-defined embryonal tumors include medulloblastoma, atypical teratoid/rhabdoid tumor, embryonal tumor with multilayered rosettes, C19MC-altered and embryonal tumor with multilayered rosettes, not otherwise specified, pineoblastoma, pituitary blastoma, CNS neuroblastoma, and ganglioneuroblastoma. Although their prognosis is nearly uniformly poor, the rapidly evolving understanding of their molecular biology contributes to diagnosis, prognosis, treatment, and clinical trial participation. Knowledge of current tumor stratification and diagnostic techniques will help pathologists guide care and preserve tissue for necessary or desired additional testing.

Texture Analysis of T1-Weighted Contrast-Enhanced Magnetic Resonance Imaging Potentially Predicts Outcomes of Patients with Non-Wingless-Type/Non-Sonic Hedgehog Medulloblastoma

OBJECTIVE

To investigate whether tumor texture features derived from preoperative T1-weighted magnetic resonance imaging (MRI) are associated with overall survival (OS) of patients with non-wingless-type (WNT)/non-sonic hedgehog (SHH) medulloblastoma.

METHODS

We retrospectively reviewed 38 patients with non-WNT/non-SHH (encompassing group 3 and group 4) medulloblastoma treated with surgery in our institution from 2013 to 2016. All patients were followed-up for at least 2 years or until death. Primary tumor traditional parameters were evaluated, and texture features were extracted from preoperative T1-weighted MRI, including 4 features from the histogram matrix and 6 textures from the gray-level co-occurrence matrix (GLCM). Texture features were dichotomized into 2 subgroups based on their optimal cutoff values obtained from receiver operating characteristics curve analysis. Two-year OS was compared between the dichotomized subgroups using the Kaplan-Meier analysis and log-rank test. Multivariate Cox regression analysis was performed to determine independent prognostic factors.

RESULTS

The therapy regimen was the only basic characteristic significantly related to 2-year OS (P = 0.015). Two features of the GLCM were shown to be significantly associated with 24-month OS. Multivariate Cox regression analysis revealed that GLCM homogeneity (adjusted hazard ratio, 0.145; P = 0.013) was an independent prognostic predictor for patients.

CONCLUSIONS

Texture analysis on T1-weighted contrast-enhanced MRI potentially serves as a prognostic predictor of survival for patients with non-WNT/non-SHH medulloblastoma.

Pediatric Central Nervous System Tumors: State-of-the-Art and Debated Aspects

Pediatric neuro-oncology surgery continues to progress in sophistication, largely driven by advances in technology used to aid the following aspects of surgery: operative planning (advanced MRI techniques including fMRI and DTI), intraoperative navigation [preoperative MRI, intra-operative MRI (ioMRI) and intra-operative ultrasound (ioUS)], tumor visualization (microscopy, endoscopy, fluorescence), tumor resection techniques (ultrasonic aspirator, micro-instruments, micro-endoscopic instruments), delineation of the resection extent (ioMRI, ioUS, and fluorescence), and intraoperative safety (neurophysiological monitoring, ioMRI). This article discusses the aforementioned technological advances, and their multimodal use to optimize safe pediatric neuro-oncology surgery.