Neuroimaging of pediatric brain tumors: from basic to advanced magnetic resonance imaging (MRI)

Applications of machine learning to MR imaging of pediatric low-grade gliomas

INTRODUCTION

Machine learning (ML) shows promise for the automation of routine tasks related to the treatment of pediatric low-grade gliomas (pLGG) such as tumor grading, typing, and segmentation. Moreover, it has been shown that ML can identify crucial information from medical images that is otherwise currently unattainable. For example, ML appears to be capable of preoperatively identifying the underlying genetic status of pLGG.

METHODS

In this chapter, we reviewed, to the best of our knowledge, all published works that have used ML techniques for the imaging-based evaluation of pLGGs. Additionally, we aimed to provide some context on what it will take to go from the exploratory studies we reviewed to clinically deployed models.

RESULTS

Multiple studies have demonstrated that ML can accurately grade, type, and segment and detect the genetic status of pLGGs. We compared the approaches used between the different studies and observed a high degree of variability throughout the methodologies. Standardization and cooperation between the numerous groups working on these approaches will be key to accelerating the clinical deployment of these models.

CONCLUSION

The studies reviewed in this chapter detail the potential for ML techniques to transform the treatment of pLGG. However, there are still challenges that need to be overcome prior to clinical deployment.

Advanced MRI imaging techniques in pediatric brain tumors

There is a diverse array of pediatric brain tumors with considerable associated morbidity. Like adult brain tumors, MRI serves as the primary imaging modality for pediatric brain tumors. In addition to standard sequences, more advanced MRI techniques can enhance the precision of diagnosis and assist in prognostication, and treatment planning. This paper discusses these various advanced techniques categorizing them into those that assist in identifying tissue characteristics, and those that evaluate the functional impact of tumors to aid in treatment planning.

Radiomics and artificial intelligence applications in pediatric brain tumors

BACKGROUND

The study of central nervous system (CNS) tumors is particularly relevant in the pediatric population because of their relatively high frequency in this demographic and the significant impact on disease- and treatment-related morbidity and mortality. While both morphological and non-morphological magnetic resonance imaging techniques can give important information concerning tumor characterization, grading, and patient prognosis, increasing evidence in recent years has highlighted the need for personalized treatment and the development of quantitative imaging parameters that can predict the nature of the lesion and its possible evolution. For this purpose, radiomics and the use of artificial intelligence software, aimed at obtaining valuable data from images beyond mere visual observation, are gaining increasing importance. This brief review illustrates the current state of the art of this new imaging approach and its contributions to understanding CNS tumors in children.

DATA SOURCES

We searched the PubMed, Scopus, and Web of Science databases using the following key search terms: ("radiomics" AND/OR "artificial intelligence") AND ("pediatric AND brain tumors"). Basic and clinical research literature related to the above key research terms, i.e., studies assessing the key factors, challenges, or problems of using radiomics and artificial intelligence in pediatric brain tumors management, was collected.

RESULTS

A total of 63 articles were included. The included ones were published between 2008 and 2024. Central nervous tumors are crucial in pediatrics due to their high frequency and impact on disease and treatment. MRI serves as the cornerstone of neuroimaging, providing cellular, vascular, and functional information in addition to morphological features for brain malignancies. Radiomics can provide a quantitative approach to medical imaging analysis, aimed at increasing the information obtainable from the pixels/voxel grey-level values and their interrelationships. The "radiomic workflow" involves a series of iterative steps for reproducible and consistent extraction of imaging data. These steps include image acquisition for tumor segmentation, feature extraction, and feature selection. Finally, the selected features, via training predictive model (CNN), are used to test the final model.

CONCLUSIONS

In the field of personalized medicine, the application of radiomics and artificial intelligence (AI) algorithms brings up new and significant possibilities. Neuroimaging yields enormous amounts of data that are significantly more than what can be gained from visual studies that radiologists can undertake on their own. Thus, new partnerships with other specialized experts, such as big data analysts and AI specialists, are desperately needed. We believe that radiomics and AI algorithms have the potential to move beyond their restricted use in research to clinical applications in the diagnosis, treatment, and follow-up of pediatric patients with brain tumors, despite the limitations set out.

Characterisation of paediatric brain tumours by their MRS metabolite profiles

1H-magnetic resonance spectroscopy (MRS) has the potential to improve the noninvasive diagnostic accuracy for paediatric brain tumours. However, studies analysing large, comprehensive, multicentre datasets are lacking, hindering translation to widespread clinical practice. Single-voxel MRS (point-resolved single-voxel spectroscopy sequence, 1.5 T: echo time [TE] 23-37 ms/135-144 ms, repetition time [TR] 1500 ms; 3 T: TE 37-41 ms/135-144 ms, TR 2000 ms) was performed from 2003 to 2012 during routine magnetic resonance imaging for a suspected brain tumour on 340 children from five hospitals with 464 spectra being available for analysis and 281 meeting quality control. Mean spectra were generated for 13 tumour types. Mann-Whitney U-tests and Kruskal-Wallis tests were used to compare mean metabolite concentrations. Receiver operator characteristic curves were used to determine the potential for individual metabolites to discriminate between specific tumour types. Principal component analysis followed by linear discriminant analysis was used to construct a classifier to discriminate the three main central nervous system tumour types in paediatrics. Mean concentrations of metabolites were shown to differ significantly between tumour types. Large variability existed across each tumour type, but individual metabolites were able to aid discrimination between some tumour types of importance. Complete metabolite profiles were found to be strongly characteristic of tumour type and, when combined with the machine learning methods, demonstrated a diagnostic accuracy of 93% for distinguishing between the three main tumour groups (medulloblastoma, pilocytic astrocytoma and ependymoma). The accuracy of this approach was similar even when data of marginal quality were included, greatly reducing the proportion of MRS excluded for poor quality. Children's brain tumours are strongly characterised by MRS metabolite profiles readily acquired during routine clinical practice, and this information can be used to support noninvasive diagnosis. This study provides both key evidence and an important resource for the future use of MRS in the diagnosis of children's brain tumours.

Social cognition in adult survivors of brain tumors: studying the relationship between theory of mind and quality of life

OBJECTIVE

The present study is the first to examine theory of mind (ToM) sequelae in a sample of adult survivors of primary brain tumors, and to investigate the assumed relationship between ToM and health-related quality of life (HRQoL).

METHOD

Participants were 40 long-term adult survivors of primary brain tumors and 40 matched healthy controls. They completed ToM tests (Faux-Pas test and Advanced ToM task) and two questionnaires assessing HRQoL (36-Item Short-Form Health Survey and EORTC QLQ-C30/QLQ-BN20). Their relatives also completed an observer-rated version of the SF-36 questionnaire.

RESULTS

Survivors performed worse than controls only on the Advanced ToM task. Overall, patients and caregivers reported more problems than healthy controls and their relatives regarding both global HRQoL and its social/emotional aspects. No relationship was found between ToM and HRQoL scores.

CONCLUSION

Adult survivors of primary brain tumors may exhibit ToM deficits several years after treatment and report more problems on social/emotional HRQoL components. Our findings highlight the need to consider these late effects in survivors' long-term follow-up, even if the clinical involvement of ToM deficits still needs to be elucidated. The assessment of ToM deficits and their potential impact on survivors' everyday life is thoroughly discussed.

Recent Advances in Pediatric Medulloblastoma

PURPOSE OF REVIEW

Review recent advances in the understanding of pediatric medulloblastoma including etiology, biology, radiology, and management of pediatric medulloblastoma.

RECENT FINDINGS

The classic four subgroups have been reclassified and further subdivided based on new molecular findings. Research is revealing the cell origins of the different subtypes of medulloblastoma. There has been continued personalization of management based on molecular parameters. While many advances have been made in the knowledge base of this most common malignant pediatric brain tumor, there has not yet been translation into more effective therapies to prolong survival in all subgroups with the possible exception of children with group 3 disease. Quality of life remains a major challenge for long-term survivors.

Pediatric Imaging Using PET/MR Imaging

PET/MR imaging is a one-stop shop technique for pediatric diseases allowing not only an accurate clinical assessment of tumors at staging and restaging but also the diagnosis of neurologic, inflammatory, and infectious diseases in complex cases. Moreover, applying PET kinetic analyses and sequences such as diffusion-weighted imaging as well as quantitative analysis investigating the relationship between disease metabolic activity and cellularity can be applied. Complex radiomics analysis can also be performed.

Deep learning based clinico-radiological model for paediatric brain tumor detection and subtype prediction

Aim

Early diagnosis of paediatric brain tumors significantly improves the outcome. The aim is to study magnetic resonance imaging (MRI) features of paediatric brain tumors and to develop an automated segmentation (AS) tool which could segment and classify tumors using deep learning methods and compare with radiologist assessment.

Methods

This study included 94 cases, of which 75 were diagnosed cases of ependymoma, medulloblastoma, brainstem glioma, and pilocytic astrocytoma and 19 were normal MRI brain cases. The data was randomized into training data, 64 cases; test data, 21 cases and validation data, 9 cases to devise a deep learning algorithm to segment the paediatric brain tumor. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of the deep learning model were compared with radiologist's findings. Performance evaluation of AS was done based on Dice score and Hausdorff95 distance.

Results

Analysis of MRI semantic features was done with necrosis and haemorrhage as predicting features for ependymoma, diffusion restriction and cystic changes were predictors for medulloblastoma. The accuracy of detecting abnormalities was 90%, with a specificity of 100%. Further segmentation of the tumor into enhancing and non-enhancing components was done. The segmentation results for whole tumor (WT), enhancing tumor (ET), and non-enhancing tumor (NET) have been analyzed by Dice score and Hausdorff95 distance. The accuracy of prediction of all MRI features was compared with experienced radiologist's findings. Substantial agreement observed between the classification by model and the radiologist's given classification [K-0.695 (K is Cohen's kappa score for interrater reliability)].

Conclusions

The deep learning model had very high accuracy and specificity for predicting the magnetic resonance (MR) characteristics and close to 80% accuracy in predicting tumor type. This model can serve as a potential tool to make a timely and accurate diagnosis for radiologists not trained in neuroradiology.

Imaging of pediatric brain tumors: A COG Diagnostic Imaging Committee/SPR Oncology Committee/ASPNR White Paper

Tumors of the central nervous system are the most common solid malignancies in children and the most common cause of pediatric cancer-related mortality. Imaging plays a central role in diagnosis, staging, treatment planning, and response assessment of pediatric brain tumors. However, the substantial variability in brain tumor imaging protocols across institutions leads to variability in patient risk stratification and treatment decisions, and complicates comparisons of clinical trial results. This White Paper provides consensus-based imaging recommendations for evaluating pediatric patients with primary brain tumors. The proposed brain magnetic resonance imaging protocol recommendations balance advancements in imaging techniques with the practicality of deployment across most imaging centers.

Apparent Diffusion Coefficient in the Differentiation of Common Pediatric Brain Tumors in the Posterior Fossa: Different Region-of-Interest Selection Methods for Time Efficiency, Measurement Reproducibility, and Diagnostic Utility

OBJECTIVES

This study aimed to explore the diagnostic ability of apparent diffusion coefficient (ADC) values obtained from different region of interest (ROI) measurements in tumor parenchyma for differentiating posterior fossa tumors (PFTs) and the correlations between ADC values and Ki-67.

METHODS

Seventy-three pediatric patients with PFTs who underwent conventional diffusion-weighted imaging were recruited in this study. Five different ROIs were manually drawn by 2 radiologists (ROI-polygon, ROI-3 sections, ROI-3-5 ovals, ROI-more ovals, and ROI-whole). The interreader/intrareader repeatability, time required, diagnostic ability, and Ki-67 correlation analysis of the ADC values based on these ROI strategies were calculated.

RESULTS

Both interreader and intrareader reliabilities were excellent for ADC values among the different ROI strategies (intraclass correlation coefficient, 0.899-0.992). There were statistically significant differences in time consumption among the 5 ROI selection methods ( P < 0.001). The time required for the ROI-3-5 ovals was the shortest (32.23 ± 5.14 seconds), whereas the time required for the ROI-whole was the longest (204.52 ± 92.34 seconds). The diagnostic efficiency of the ADC values showed no significant differences among the different ROI measurements ( P > 0.05). The ADC value was negatively correlated with Ki-67 ( r = -0.745 to -0.798, all P < 0.0001).

CONCLUSIONS

The ROI-3-5 ovals method has the best interobserver repeatability, the shortest amount of time spent, and the best diagnostic ability. Thus, it is considered an effective measurement to produce ADC values in the evaluation of pediatric PFTs.

The Diagnostic Efficiency of Quantitative Diffusion Weighted Imaging in Differentiating Medulloblastoma from Posterior Fossa Tumors: A Systematic Review and Meta-Analysis

Medulloblastoma (MB) is considered the most common and highly malignant posterior fossa tumor (PFT) in children. The accurate preoperative diagnosis of MB is beneficial in choosing the appropriate surgical methods and treatment strategies. Diffusion-weighted imaging (DWI) has improved the accuracy of differential diagnosis of posterior fossa tumors. Nonetheless, further studies are needed to confirm its value for clinical application. This study aimed to evaluate the performance of DWI in differentiating MB from other PFT. A literature search was conducted using databases PubMed, Embase, and Web of Science for studies reporting the diagnostic performance of DWI for PFT from January 2000 to January 2022. A bivariate random-effects model was employed to evaluate the pooled sensitivities and specificities. A univariable meta-regression analysis was used to assess relevant factors for heterogeneity, and subgroup analyses were performed. A total of 15 studies with 823 patients were eligible for data extraction. Overall pooled sensitivity and specificity of DWI were 0.94 (95% confident interval [CI]: 0.89-0.97) and 0.94 (95% CI: 0.90-0.96) respectively. The area under the curve (AUC) of DWI was 0.98 (95% CI: 0.96-0.99). Heterogeneity was found in the sensitivity (I² = 62.59%) and the specificity (I² = 35.94%). Magnetic field intensity, region of interest definition and DWI diagnostic parameters are the factors that affect the diagnostic performance of DWI. DWI has excellent diagnostic accuracy for differentiating MB from other PFT. Hence, it is necessary to set DWI as a routine examination sequence for posterior fossa tumors.

MR Imaging of Pediatric Brain Tumors

Primary brain tumors are the most common solid neoplasms in children and a leading cause of mortality in this population. MRI plays a central role in the diagnosis, characterization, treatment planning, and disease surveillance of intracranial tumors. The purpose of this review is to provide an overview of imaging methodology, including conventional and advanced MRI techniques, and illustrate the MRI appearances of common pediatric brain tumors.

Relationships between executive functioning and health-related quality of life in adult survivors of brain tumor and matched healthy controls

INTRODUCTION

Few studies have considered health-related quality of life (HRQOL) as a primary outcome measure in adult survivors of primary brain tumor (PBT), and fewer still have studied the cognitive factors that may influence it. Research suggests that executive functions (EFs) are associated with HRQOL, but there is scant evidence to support this. The present study was conducted to (1) extend prior findings about HRQOL limitations in a sample of stable, long-term adult survivors of PBT, (2) investigate the associations between objective/reported EFs and HRQOL, and (3) identify the EFs that contribute most to HRQOL.

METHOD

We recruited 40 survivors of PBT (> 2 years post-treatment) and 40 matched healthy controls. Participants completed an objective EF assessment (inhibition, working memory, shifting, and rule detection) and two self-report questionnaires probing EFs (Behavior Rating Inventory of Executive Function-Adult) and HRQOL (Medical Outcomes Study Short-Form 36). Participants' relatives completed observer-rated versions of these questionnaires.

RESULTS

Patients' objective EF performances were relatively intact. However, patients and caregivers reported significantly more problems than healthy controls and their relatives, for both EFs and HRQOL. There were only negligible links between objective EFs and HRQOL, whereas numerous associations were found between reported EFs and HRQOL components. ANCOVA models revealed that specific reported EF processes contributed to both the physical and mental components of HRQOL, regardless of group.

CONCLUSIONS

From a clinical point of view, this study demonstrates that even several years after end of treatment, adult PBT survivors experience substantial problems across different HRQOL domains. HRQOL assessment should therefore be part of the long-term follow-up of PBT survivors, and clinicians should consider EF limitations when designing appropriate survivorship care plans. These findings indicate that cognitive interventions targeting EFs could improve HRQOL.

Compressed SENSE in Pediatric Brain Tumor MR Imaging : Assessment of Image Quality, Examination Time and Energy Release

Purpose

To compare the image quality, examination time, and total energy release of a standardized pediatric brain tumor magnetic resonance imaging (MRI) protocol performed with and without compressed sensitivity encoding (C-SENSE). Recently introduced as an acceleration technique in MRI, we hypothesized that C‑SENSE would improve image quality, reduce the examination time and radiofrequency-induced energy release compared with conventional examination in a pediatric brain tumor protocol.

Methods

This retrospective study included 22 patients aged 2.33–18.83 years with different brain tumor types who had previously undergone conventional MRI examination and underwent follow-up C‑SENSE examination. Both examinations were conducted with a 3.0-Tesla device and included pre-contrast and post-contrast T1-weighted turbo-field-echo, T2-weighted turbo-spin-echo, and fluid-attenuated inversion recovery sequences. Image quality was assessed in four anatomical regions of interest (tumor area, cerebral cortex, basal ganglia, and posterior fossa) using a 5-point scale. Reader preference between the standard and C‑SENSE images was evaluated. The total examination duration and energy deposit were compared based on scanner log file analysis.

Results

Relative to standard examinations, C‑SENSE examinations were characterized by shorter total examination times (26.1 ± 3.93 vs. 22.18 ± 2.31 min; P = 0.001), reduced total energy deposit (206.0 ± 19.7 vs. 92.3 ± 18.2 J/kg; P < 0.001), and higher image quality (overall P < 0.001).

Conclusion

C‑SENSE contributes to the improvement of image quality, reduction of scan times and radiofrequency-induced energy release relative to the standard protocol in pediatric brain tumor MRI.

Supplementary Information

The online version of this article (10.1007/s00062-021-01112-3) contains supplementary material, which is available to authorized users.

Advanced Magnetic Resonance Imaging in Pediatric Glioblastomas

The shortly upcoming 5th edition of the World Health Organization Classification of Tumors of the Central Nervous System is bringing extensive changes in the terminology of diffuse high-grade gliomas (DHGGs). Previously "glioblastoma," as a descriptive entity, could have been applied to classify some tumors from the family of pediatric or adult DHGGs. However, now the term "glioblastoma" has been divested and is no longer applied to tumors in the family of pediatric types of DHGGs. As an entity, glioblastoma remains, however, in the family of adult types of diffuse gliomas under the insignia of "glioblastoma, IDH-wildtype." Of note, glioblastomas still can be detected in children when glioblastoma, IDH-wildtype is found in this population, despite being much more common in adults. Despite the separation from the family of pediatric types of DHGGs, what was previously labeled as "pediatric glioblastomas" still remains with novel labels and as new entities. As a result of advances in molecular biology, most of the previously called "pediatric glioblastomas" are now classified in one of the four family members of pediatric types of DHGGs. In this review, the term glioblastoma is still apocryphally employed mainly due to its historical relevance and the paucity of recent literature dealing with the recently described new entities. Therefore, "glioblastoma" is used here as an umbrella term in the attempt to encompass multiple entities such as astrocytoma, IDH-mutant (grade 4); glioblastoma, IDH-wildtype; diffuse hemispheric glioma, H3 G34-mutant; diffuse pediatric-type high-grade glioma, H3-wildtype and IDH-wildtype; and high grade infant-type hemispheric glioma. Glioblastomas are highly aggressive neoplasms. They may arise anywhere in the developing central nervous system, including the spinal cord. Signs and symptoms are non-specific, typically of short duration, and usually derived from increased intracranial pressure or seizure. Localized symptoms may also occur. The standard of care of "pediatric glioblastomas" is not well-established, typically composed of surgery with maximal safe tumor resection. Subsequent chemoradiation is recommended if the patient is older than 3 years. If younger than 3 years, surgery is followed by chemotherapy. In general, "pediatric glioblastomas" also have a poor prognosis despite surgery and adjuvant therapy. Magnetic resonance imaging (MRI) is the imaging modality of choice for the evaluation of glioblastomas. In addition to the typical conventional MRI features, i.e., highly heterogeneous invasive masses with indistinct borders, mass effect on surrounding structures, and a variable degree of enhancement, the lesions may show restricted diffusion in the solid components, hemorrhage, and increased perfusion, reflecting increased vascularity and angiogenesis. In addition, magnetic resonance spectroscopy has proven helpful in pre- and postsurgical evaluation. Lastly, we will refer to new MRI techniques, which have already been applied in evaluating adult glioblastomas, with promising results, yet not widely utilized in children.

Amide Proton Transfer-Weighted MR Imaging of Pediatric Central Nervous System Diseases

Amide proton transfer-weighted (APTw) imaging is a molecular MR imaging technique that can detect the concentration of the amide protons in mobile cellular proteins and peptides or a pH change in vivo. Previous studies have indicated that APTw MR imaging can be used to detect malignant brain tumors, stroke, and other neurologic diseases, although the clinical application in pediatric patients remains limited. The authors briefly introduce the basic principles of APTw imaging. Then, they review early clinical applications of this approach to pediatric central nervous system diseases, including pediatric brain development, hypoxic-ischemic encephalopathy, intracranial infection, and brain tumors.

Contrast Pediatric Brain Perfusion: Dynamic Susceptibility Contrast and Dynamic Contrast-Enhanced MR Imaging

Magnetic resonance (MR) perfusion is a robust imaging technique that assesses the passage of blood through the cerebral vascular network using a variety of techniques. The applications of MR perfusion have been expanded and is well suited to investigate cerebrovascular diseases and cerebral neoplastic processes in pediatric patients. Assessment of brain perfusion can augment the information obtained on conventional MR imaging and provides additional information on the biological and physiologic features of pediatric brain tumors. Similarly, MR perfusion can help guide the management of a variety of pediatric cerebrovascular diseases, including acute ischemic stroke and Moyamoya syndrome.

Supratentorial Extraventricular Ependymomas: Imaging Features and the Added Value of Apparent Diffusion Coefficient

OBJECTIVE

To improve the understanding and the diagnosis of intracranial ependymal tumors.

METHODS

The clinical, radiological and prognostic features of 48 supratentorial extraventricular ependymomas and 74 intraventricular ependymomas were summarized and compared.

RESULTS

Supratentorial extraventricular ependymomas, most often located in the frontal lobe (33.3%) and classified as grade III (75.0%), had relatively large eccentric cysts (3.07 ± 2.03 cm), significant enhancement (84.8%), low apparent diffusion coefficient (ADC) values, and associated with higher mortality (41.3%). The majority of intraventricular lesions occurred in the fourth ventricle (86.5%) and classified as grade II (78.4%), had relatively small and multiple cystic changes (1.04 ± 0.87 cm), slight or moderate enhancement (76.9%), high ADC values and associated with lower mortality (20.7%). There were few significant differences between grade II and grade III tumors in these 2 groups, respectively. Young age, high grade and low ADC values are worse prognostic indicators for patients with supratentorial extraventricular ependymomas, but not for those with intraventricular ependymomas.

CONCLUSIONS

Conventional radiological features, combined with clinical manifestations and quantitative information provided by diffusion-weighted imaging, may not only enhance the diagnosis and assist in determining prognosis but also provide a better pathophysiological understanding of intracranial ependymal tumors.

[Combination of tumors of different histogenesis in pediatric neurosurgery]

Multiple gliomas are determined by synchronous two or more tumors located in different brain regions. It is important to distinguish multiple primary tumors and metastatic brain lesion. In the first case, tumor spread can`t be explained by dissemination along the cerebrospinal fluid pathways, commissural fibers or local metastases. Multiple primary tumors with different histological structures are called bidermal neoplasms. Surgery is preferred in these patients with severe symptoms. The purpose of surgery is maximum resection of tumor. Follow-up may be advisable for small tumors without clinical manifestations. Treatment of multiple gliomas includes surgery, radiotherapy and chemotherapy. Multiple tumor process in children is much more severe compared to a single neoplasia that requires neurological and neuroimaging control and determines treatment strategy. The authors report 3 children with multicentric gliomas, discuss the various aspects of diagnosis and treatment of multiple gliomas and formulate the recommendations for the treatment based on own clinical experience and literature data.

Edema-mass Ratio Based On Magnetic Resonance Imaging As A Preoperative Diagnostic Factor For Posterior Fossa Metastasis

BACKGROUND

Peritumoral edema of primary brain tumors is an important cause of morbidity and mortality. The number of studies currently available on the prognostic role of peritumoral brain edema in the posterior fossa is extremely limited.

OBJECTIVE

Based on the known importance of magnetic resonance imaging in diagnosing supratentorial metastases, this study aimed to investigate the effects of peritumoral edema on survival of patients with posterior fossa metastases and the preoperative diagnostic value of MRI.

METHODS

Edema and mass volumes of 49 patients with posterior fossa metastasis, who underwent surgery during 2012-2016, were measured using magnetic resonance imaging. The edema/mass indices were retrospectively calculated and interpreted by evaluating the demographic, clinical, and survival data.

RESULTS

The study consisted of 32 (65.3%) male and 17 (34.7%) female participants, with the mean age ± standard deviation of 47.25±29.25 (17-81) years. Among the 49 patients with posterior fossa metastases, 34 (69.4%) had carcinoma, while 15 (30.6%) had non-carcinoma metastases. The edema/mass indices of patients with carcinoma and non-carcinoma metastases were found to be 14.55±9.64 and 1.34±1.08, respectively, and the difference was statistically significant (p<0.001). The mean survival of patients with carcinoma and non-carcinoma metastases was found to be 642±11.52 days and 726±9.32 days, respectively; however, this difference was not statistically significant (p=0.787).

CONCLUSION

The edema/mass ratio was found to be a significant diagnostic factor for the prediction of posterior fossa metastases. Further detailed studies are warranted to investigate the effect of edema/mass ratio on survival rate.

Diffusion histology imaging differentiates distinct pediatric brain tumor histology

High-grade pediatric brain tumors exhibit the highest cancer mortality rates in children. While conventional MRI has been widely adopted for examining pediatric high-grade brain tumors clinically, accurate neuroimaging detection and differentiation of tumor histopathology for improved diagnosis, surgical planning, and treatment evaluation, remains an unmet need in their clinical management. We employed a novel Diffusion Histology Imaging (DHI) approach employing diffusion basis spectrum imaging (DBSI) derived metrics as the input classifiers for deep neural network analysis. DHI aims to detect, differentiate, and quantify heterogeneous areas in pediatric high-grade brain tumors, which include normal white matter (WM), densely cellular tumor, less densely cellular tumor, infiltrating edge, necrosis, and hemorrhage. Distinct diffusion metric combination would thus indicate the unique distributions of each distinct tumor histology features. DHI, by incorporating DBSI metrics and the deep neural network algorithm, classified pediatric tumor histology with an overall accuracy of 85.8%. Receiver operating analysis (ROC) analysis suggested DHI’s great capability in distinguishing individual tumor histology with AUC values (95% CI) of 0.984 (0.982–0.986), 0.960 (0.956–0.963), 0.991 (0.990–0.993), 0.950 (0.944–0.956), 0.977 (0.973–0.981) and 0.976 (0.972–0.979) for normal WM, densely cellular tumor, less densely cellular tumor, infiltrating edge, necrosis and hemorrhage, respectively. Our results suggest that DBSI-DNN, or DHI, accurately characterized and classified multiple tumor histologic features in pediatric high-grade brain tumors. If these results could be further validated in patients, the novel DHI might emerge as a favorable alternative to the current neuroimaging techniques to better guide biopsy and resection as well as monitor therapeutic response in patients with high-grade brain tumors.

Predictors of cognitive function in pediatric brain tumor patients: Pre-surgery through 24-month follow-up

The aim of this study was to examine the feasibility of cognitive assessment from pre-surgery through 2-year follow-up in a sample of pediatric brain tumor (BT) patients. We sought to investigate cognitive function over the course of diagnosis and treatment, and as a function of presenting problems, tumor location, treatment type, and tumor severity. Using a prospective, longitudinal design, standardized IQ measures were administered to pediatric BT patients (ages 6-16) prior to surgery (n = 25), 6 months post-diagnosis (n = 24), and 24 months post-diagnosis (n = 23). Group differences emerged based on tumor severity and treatment type at multiple time points, including prior to surgical intervention; children with high grade tumors performed more poorly than children with low grade tumors, and children receiving surgery plus adjuvant therapy performed more poorly than children who received surgery only. When considered together, an analysis of covariance demonstrated that tumor grade significantly accounted for variability in cognitive functioning, while treatment type did not. Although there is overlap clinically between tumor severity and treatment received, results suggest that tumor severity is an important factor contributing to variability in cognitive functioning and should also be considered when monitoring risk for cognitive deficits in children diagnosed with BT.

Role of diffusion-weighted imaging in differentiation between posterior fossa brain tumors

Background

Diffusion-weighted imaging (DWI) is an imaging modality using multi-section single-shot spin echo planar imaging (EPI) sequence which is extremely sensitive for detection of water motion within intra, extra, and transcellular regions. This character is important to differentiate between brain tumors either low (benign) or highly (malignant) cellular tumors.

Objective

To evaluate the role of DWI and apparent diffusion coefficient (ADC) in evaluation and differentiation between different brain posterior fossa tumors in children and adults.

Patients and methods

The study included 34 patients with different brain posterior fossa tumors for evaluation by conventional MRI (using 1.5 T MRI PHILIPS Achieva 2.1 Best Netherland) and DWI.

Results

Our study showed that mean ADC values were significantly different between the four groups of posterior fossa tumors in children: juvenile pilocytic astrocytoma (JPA), medulloblastoma, ependymoma, and brain stem glioma while mean ADC values were not significantly different between posterior fossa tumors in the adult group. Regions of interest were manually positioned, and all values were automatically calculated and expressed in 10−3 mm2/s.

Conclusion

DWI is an ideal additional imaging technique, which is a rapid, easy, non-invasive imaging modality, with no contrast injection needed. It has been widely applied in the differentiation between posterior fossa brain tumors and in the diagnosis of various intracranial diseases.

Pediatric hemispheric high-grade glioma: targeting the future

Pediatric high-grade gliomas (pHGGs) are a group of tumors affecting approximately 0.85 children per 100,000 annually. The general outcome for these tumors is poor with 5-year survival rates of less than 20%. It is now recognized that these tumors represent a heterogeneous group of tumors rather than one entity. Large-scale genomic analyses have led to a greater understanding of the molecular drivers of different subtypes of these tumors and have also aided in the development of subtype-specific therapies. For example, for pHGG with NTRK fusions, promising new targeted therapies are actively being explored. Herein, we review the clinico-pathologic and molecular classification of these tumors, historical treatments, current management strategies, and therapies currently under investigation.

Response assessment in paediatric low-grade glioma: recommendations from the Response Assessment in Pediatric Neuro-Oncology (RAPNO) working group

Paediatric low-grade gliomas (also known as pLGG) are the most common type of CNS tumours in children. In general, paediatric low-grade gliomas show clinical and biological features that are distinct from adult low-grade gliomas, and the developing paediatric brain is more susceptible to toxic late effects of the tumour and its treatment. Therefore, response assessment in children requires additional considerations compared with the adult Response Assessment in Neuro-Oncology criteria. There are no standardised response criteria in paediatric clinical trials, which makes it more difficult to compare responses across studies. The Response Assessment in Pediatric Neuro-Oncology working group, consisting of an international panel of paediatric and adult neuro-oncologists, clinicians, radiologists, radiation oncologists, and neurosurgeons, was established to address issues and unique challenges in assessing response in children with CNS tumours. We established a subcommittee to develop consensus recommendations for response assessment in paediatric low-grade gliomas. Final recommendations were based on literature review, current practice, and expert opinion of working group members. Consensus recommendations include imaging response assessments, with additional guidelines for visual functional outcomes in patients with optic pathway tumours. As with previous consensus recommendations, these recommendations will need to be validated in prospective clinical trials.

Diagnostic accuracy of apparent diffusion coefficient ratio in distinguishing common pediatric CNS posterior fossa tumors

Background

Pilocytic astrocytoma, medulloblastoma, and ependymoma are the most common pediatric CNS tumors seen at posterior cranial fossa and final diagnosis obtained by histopathology after surgical excision. Routine MRI study gives an idea about site and extension of the tumors but provide a little information about type and grade of tumors. ADC ratio had high sensitivity and specificity in differentiation between these tumors as regard type and grade according to tumor cellularity.

Patients and methods

Prospective study conducted on thirty pediatric patients (11 males and 19 females) with CNS posterior fossa masses, their ages ranged from 2 to 17 years (mean age of 8.7 years), conventional MRI, DWI, ADC value, and ADC ratio were done for all patients.

Results

ADC values were significantly different between pilocytic astrocytomas (1.43 ± 0.28 × 10−3) and medulloblastomas (0.71 ± 0. 21 × 10−3) with a P value < 0.001, also there was a significant difference when comparing medulloblastomas (0.71 ± 0.21 × 10−3) with ependymomas (1.04 × 10−3 ± 0.21) with a P value < 0.001. ADC ratio at a cutoff > 1.7 showed significant good power of discrimination of astrocytoma (AUC = 0.85) from ependymoma with 87.5% sensitivity and 93.3% specificity. Similarly, at cutoff ≤ 1.6-> 1.2 was a significant good predictor of ependymoma (AUC = 0.85) with 87.8% sensitivity and 99.5% specificity. While, ADC ratio ≤ 1.2 was significant excellent discriminator of medulloblastoma (AUC = 0.99) with 100% sensitivity and 90% specificity.

Conclusion

ADC ratio is a simple way used in distinguishing juvenile pilocytic astrocytoma, ependymoma, and medulloblastoma, which are the most frequent pediatric posterior fossa tumors. Cutoff ADC ratio of more than 1.7 characteristic of JPA with 87.5% sensitivity and 93.3% specificity, ADC ratio less than 1.1 characteristic of medulloblastoma with 100% sensitivity and 90% specificity. ADC ratios more than 1.1 and less than 1.7 characteristic of ependymoma with 87.8% sensitivity and 99.5% specificity. We recommended ADC ratio as a routine study in evaluation of pediatric CNS posterior fossa tumors.

Radiological Evaluation of Newly Diagnosed Non-Brainstem Pediatric High-Grade Glioma in the HERBY Phase II Trial

PURPOSE

The HERBY trial evaluated the benefit of the addition of the antiangiogenic agent Bevacizumab (BEV) to radiotherapy/temozolomide (RT/TMZ) in pediatric patients with newly diagnosed non-brainstem high-grade glioma (HGG). The work presented here aims to correlate imaging characteristics and outcome measures with pathologic and molecular data.

EXPERIMENTAL DESIGN

Radiological, pathologic, and molecular data were correlated with trial clinical information to retrospectively re-evaluate event-free survival (EFS) and overall survival (OS).

RESULTS

One-hundred thirteen patients were randomized to the RT/TMZ arm (n = 54) or the RT/TMZ+BEV (BEV arm; n = 59). The tumor arose in the cerebral hemispheres in 68 patients (Cerebral group) and a midline location in 45 cases (Midline group). Pathologic diagnosis was available in all cases and molecular data in 86 of 113. H3 K27M histone mutations were present in 23 of 32 Midline cases and H3 G34R/V mutations in 7 of 54 Cerebral cases. Total/near-total resection occurred in 44 of 68 (65%) Cerebral cases but in only 5 of 45 (11%) Midline cases (P < 0.05). Leptomeningeal metastases (27 cases, 13 with subependymal spread) at relapse were more frequent in Midline (17/45) than in Cerebral tumors (10/68, P < 0.05). Mean OS (14.1 months) and EFS (9.0 months) in Midline tumors were significantly lower than mean OS (20.7 months) and EFS (14.9 months) in Cerebral tumors (P < 0.05). Pseudoprogression occurred in 8 of 111 (6.2%) cases.

CONCLUSIONS

This study has shown that the poor outcome of midline tumors (compared with cerebral) may be related to (1) lesser surgical resection, (2) H3 K27M histone mutations, and (3) higher leptomeningeal dissemination.

Incidence of high grade gliomas presenting as radiographically non-enhancing lesions: experience in 111 surgically treated non-enhancing gliomas with tissue diagnosis

PURPOSE

Although non-enhancing lesions suspicious for glioma are usually assumed to be low grade glioma (LGG), some high grade glioma (HGG) do not enhance, which may lead to a delay in biopsy and/or resection, diagnosis, and treatment initiation. Thus, there is a clear need for a large-sample study that quantifies the rate of malignant, non-enhancing gliomas.

METHODS

We retrospectively reviewed our series of 561 consecutive surgically treated gliomas with tissue diagnosis, 111 of which were non-enhancing, to determine the prevalence of high-grade histology in radiographically presumed LGG. Relative expression of tumor markers were also reported for non-enhancing lesions to investigate genetic correlates.

RESULTS

We identified 561 surgically treated gliomas with tissue diagnosis from August 2012 to July 2018 and found that 111 patients (19.8%) demonstrated non-enhancing lesions suspicious for glioma on preoperative MRI. Thirty-one (27.9%) of the non-enhancing lesions were classified as HGGs (WHO Grade III or IV). Non-enhancing lesions were four times more likely to be HGG in patients older than 60 years than patients younger than 35 years (41.2% vs. 11.4%, Pearson Chi² p < 0.001). Binomial logistic regression showed a significant inverse effect of age on the presence of IDH mutation in non-enhancing HGGs (p = 0.007).

CONCLUSION

A clinically significant proportion (27.9%) of non-enhancing lesions were found to be HGG on final pathologic diagnosis. Thus, in patients with good functional and health status, especially those older than 60 years, we recommend obtaining tissue diagnosis of all lesions suspected to be glioma, even those that are non-enhancing, to guide diagnosis as well as early initiation of chemotherapy and radiation therapy.

Accuracy of apparent diffusion coefficient values and magnetic resonance imaging in differentiating suprasellar germinomas from chiasmatic/hypothalamic gliomas

OBJECTIVE

The aim of this study was to differentiate suprasellar germinomas from chiasmatic/hypothalamic gliomas (CHGs) using apparent diffusion coefficient (ADC) values and magnetic resonance imaging (MRI) characteristics.

MATERIALS AND METHODS

A cross-sectional study was conducted on 11 patients with suprasellar germinomas and 11 patients with CHGs who underwent pretreatment MRI. The ADC values (minimum and average ADC values) of the tumors were measured and the MRI characteristics were evaluated.

RESULTS

The average and minimum ADC values of suprasellar germinomas were significantly lower than those of CHGs (p = 0.016 and 0.004 respectively). The selection of 941.15 × 10^-6 mm²/s as a cutoff value of the minimum ADC value was used to differentiate suprasellar germinomas and CHGs; the best results were obtained with area under the curve of 0.889, sensitivity of 87.5%, specificity of 77.8% and accuracy of 82.4%. MRI characteristics suggested the diagnosis of suprasellar germinomas were T2W hypointensity and involvement of pituitary gland and/or stalk. MRI characteristics suggested the diagnosis of CHGs was higher degree of contrast enhancement and presence of macrocysts.

CONCLUSION

ADC values have a role in differentiating suprasellar germinomas and CHGs, especially when imaging findings on conventional MRI are inconclusive. Furthermore, some MRI features are in favor of differentiation between these tumor entities including tumor location, cyst pattern, T2W hypointensity, degree of contrast enhancement, stalk and pituitary gland involvement.

Diagnostic accuracy and added value of qualitative radiological review of 1H-magnetic resonance spectroscopy in evaluation of childhood brain tumors

Background

¹H-magnetic resonance spectroscopy (MRS) facilitates noninvasive diagnosis of pediatric brain tumors by providing metabolite profiles. Prospective studies of diagnostic accuracy and comparisons with conventional MRI are lacking. We aimed to evaluate diagnostic accuracy of MRS for childhood brain tumors and determine added clinical value compared with conventional MRI.

Methods

Children presenting to a tertiary pediatric center with brain lesions from December 2015 through 2017 were included. MRI and single-voxel MRS were acquired on 52 tumors and sequentially interpreted by 3 radiologists, blinded to histopathology. Proportions of correct diagnoses and interrater agreement at each stage were compared. Cases were reviewed to determine added value of qualitative radiological review of MRS through increased certainty of correct diagnosis, reduced number of differentials, or diagnosis following spectroscopist evaluation. Final diagnosis was agreed by the tumor board at study end.

Results

Radiologists' principal MRI diagnosis was correct in 69%, increasing to 77% with MRS. MRI + MRS resulted in significantly more additional correct diagnoses than MRI alone (P = .035). There was a significant increase in interrater agreement when correct with MRS (P = .046). Added value following radiologist interpretation of MRS occurred in 73% of cases, increasing to 83% with additional spectroscopist review. First histopathological diagnosis was available a median of 9.5 days following imaging, with 25% of all patients managed without conclusive histopathology.

Conclusions

MRS can improve the accuracy of noninvasive diagnosis of pediatric brain tumors and add value in the diagnostic pathway. Incorporation into practice has the potential to facilitate early diagnosis, guide treatment planning, and improve patient care.

[Brain tumors in children: about 136 cases]

Les tumeurs cérébrales sont les tumeurs solides les plus diagnostiquées chez les enfants de moins de 15 ans dans le monde. Toutefois, peu de publications ont rapporté le profil épidémiologique et anatomopathologique de ces tumeurs en Afrique et particulièrement au Maroc. Les auteurs rapportent les particularités épidémiologiques et anatomopathologiques des tumeurs cérébrales primitives de l'enfant dans la région de Marrakech (Sud du Maroc). C'est une étude rétrospective réalisée au service d'anatomie pathologique du CHU Mohammed VI de Marrakech de 2004 à 2016. Cent trente-six cas de tumeurs cérébrales primitives étaient diagnostiqués avec une moyenne de 11,33 cas par an. L'âge moyen était de 8,28 ans. Le sex-ratio (H/F) était de 1,6 avec une légère prédominance masculine. Ces tumeurs étaient infra-tentorielles dans 61,53% des cas et siégeaient en supra-tentoriel dans 38,47% des cas. A l'étage infra-tentoriel, les tumeurs des hémisphères cérebelleux occupaient le premier rang (61,4%). Parmi les dix-huit types histologiques diagnostiqués, l'astrocytome et le médulloblastome représentaient ensemble 46,32% (29,41% et 16,91% respectivement). Dans notre contexte, la majorité des tumeurs cérébrales de l'enfant prédominait dans les 2 groupes d'âge: 5-9 ans et 10-15 ans. Les résultats épidémiologiques de ces tumeurs au sud du Maroc concordent majoritairement avec ceux déjà publiés du Nord du pays et des autres pays non Africains.

High-Grade Gliomas in Children with Neurofibromatosis Type 1: Literature Review and Illustrative Cases

High-grade gliomas in patients with neurofibromatosis type 1 are rare and may therefore not be considered in the differential of brain lesions. Here, we describe 5 children with neurofibromatosis type 1; four of them developed various types of high-grade gliomas. The fifth patient had imaging features concerning for a high-grade lesion, but tissue diagnosis showed a low-grade glioma. The cases and literature summary provided here are to raise awareness for the occurrence of high-grade gliomas in children with neurofibromatosis type 1 and the limited ability of imaging features alone to predict a high-grade malignancy.

Pediatric Glioma at the Optic Pathway and Thalamus

Gliomas are the most common pediatric tumors of the central nervous system. In this review, we discuss the clinical features, treatment paradigms, and evolving concepts related to two types of pediatric gliomas affecting two main locations: the optic pathway and thalamus. In particular, we discuss recently revised pathologic classification, which adopting molecular parameter. We believe that our review contribute to the readers' better understanding of pediatric glioma because pediatric glioma differs in many ways from adult glioma according to the newest advances in molecular characterization of this tumor. A better understanding of current and evolving issues in pediatric glioma is needed to ensure effective management decision.

High-grade glioma in very young children: a rare and particular patient population

In the past years, pediatric high-grade gliomas (HGG) have been the focus of several research articles and reviews, given the recent discoveries on the genetic and molecular levels pointing out a clinico-biological uniqueness of the pediatric population compared to their adult counterparts with HGG. On the other hand, there are only scarce data about HGG in very young children (below 3 years of age at diagnosis) due to their relatively low incidence. However, the few available data suggest further distinction of this very rare subgroup from older children and adults at several levels including their molecular and biological characteristics, their treatment management, as well as their outcome. This review summarizes and discusses the current available knowledge on the epidemiological, neuropathological, genetic and molecular data of this subpopulation. We discuss these findings and differences compared to older patients suffering from the same histologic disease. In addition, we highlight the particular clinical and neuro-radiological findings in this specific subgroup of patients as well as their current management approaches and treatment outcomes.

Apparent diffusion coefficient in differentiation of pediatric posterior fossa tumors

PURPOSE

To investigate the contribution of preoperative apparent diffusion coefficient (ADC) values in the differential diagnosis of pediatric posterior fossa tumors.

METHODS

Forty-two pediatric patients (mean age 7.76 ± 4.58 years) with intra-axial tumors in the infra-tentorial region underwent magnetic resonance imaging. ADC measurement was performed using regions of interest, obtained from the solid component of the mass lesions. ADC ratios were calculated by dividing the ADC values from the mass lesions by the ADC values from normal cerebellar parenchyma. Lesions were categorized as juvenile pilocytic astrocytoma (JPA), ependymoma and medulloblastoma based on histopathological diagnosis. ADC values of the lesions and histopathological diagnoses were statistically correlated.

RESULTS

Histopathological diagnosis showed that 14 lesions were JPA, 10 were ependymoma; 18 were medulloblastoma. Both ADC values and ADC ratios were significantly correlated with tumor types (p <0.05). Astrocytoma was distinguished from ependymoma with sensitivity 85.7% and specificity 90% using an ADC ratio ≥1.7 and medulloblastoma was distinguished from ependymoma with sensitivity 100% and specificity 88.89% using an ADC ratio ≤1.18.

CONCLUSION

Preoperative ADC values could differentiate the main histological subtypes of pediatric posterior fossa tumors with high sensitivity and specificity.

Evaluation of the added value of 1H-magnetic resonance spectroscopy for the diagnosis of pediatric brain lesions in clinical practice

Background

Magnetic resonance spectroscopy (MRS) aids noninvasive diagnosis of pediatric brain tumors, but use in clinical practice is not well documented. We aimed to review clinical use of MRS, establish added value in noninvasive diagnosis, and investigate potential impact on patient care.

Methods

Sixty-nine children with lesions imaged using MRS and reviewed by the tumor board from 2014 to 2016 met inclusion criteria. Contemporaneous MRI diagnosis, spectroscopy analysis, histopathology, and clinical information were reviewed. Final diagnosis was agreed on by the tumor board at study end.

Results

Five cases were excluded for lack of documented MRI diagnosis. The principal MRI diagnosis by pediatric radiologists was correct in 59%, increasing to 73% with addition of MRS. Of the 73%, 19.1% (95% CI, 9.1%-33.3%) were incorrectly diagnosed with MRI alone. MRS led to a significant improvement in correct diagnosis over all tumor types (P = .012). Of diagnoses correctly made with MRI, confidence increased by 37% when adding MRS, with no patients incorrectly re-diagnosed. Indolent lesions were diagnosed noninvasively in 85% of cases, with MRS a major contributor to 91% of these diagnoses. Of all patients, 39% were managed without histopathological diagnosis. MRS contributed to diagnosis in 68% of this group, modifying it in 12%. MRS influenced management in 33% of cases, mainly through avoiding and guiding biopsy and aiding tumor characterization.

Conclusion

MRS can improve accuracy and confidence in noninvasive diagnosis of pediatric brain lesions in clinical practice. There is potential to improve outcomes through avoiding biopsy of indolent lesions, aiding tumor characterization, and facilitating earlier family discussions and treatment planning.

Creatine CEST MRI for Differentiating Gliomas with Different Degrees of Aggressiveness

PURPOSE

Creatine (Cr) is a major metabolite in the bioenergetic system. Measurement of Cr using conventional MR spectroscopy (MRS) suffers from low spatial resolution and relatively long acquisition times. Creatine chemical exchange saturation transfer (CrCEST) magnetic resonance imaging (MRI) is an emerging molecular imaging method for tissue Cr measurements. Our previous study showed that the CrCEST contrast, obtained through multicomponent Z-spectral fitting, was lower in tumors compared to normal brain, which further reduced with tumor progression. The current study was aimed to investigate if CrCEST MRI can also be useful for differentiating gliomas with different degrees of aggressiveness.

PROCEDURES

Intracranial 9L gliosarcoma and F98 glioma bearing rats with matched tumor size were scanned with a 9.4 T MRI scanner at two time points. CEST Z-spectra were collected using a customized sequence with a frequency-selective rectangular saturation pulse (B1 = 50 Hz, duration = 3 s) followed by a single-shot readout. Z spectral data were fitted pixel-wise with five Lorentzian functions, and maps of CrCEST peak amplitude, linewidth, and integral were produced. For comparison, single-voxel proton MR spectroscopy (1H-MRS) was performed to quantify and compare the total Cr concentration in the tumor.

RESULTS

CrCEST contrasts decreased with tumor progression from weeks 3 to 4 in both 9L and F98 phenotypes. More importantly, F98 tumors had significantly lower CrCEST integral compared to 9L tumors. On the other hand, integrals of other Z-spectral components were unable to differentiate both tumor progression and phenotype with limited sample size.

CONCLUSIONS

Given that F98 is a more aggressive tumor than 9L, this study suggests that CrCEST MRI may help differentiate gliomas with different aggressiveness.

Neuroimaging of Peptide-based Vaccine Therapy in Pediatric Brain Tumors: Initial Experience

The potential benefits of peptide-based immunotherapy for pediatric brain tumors are under investigation. Treatment-related heterogeneity has resulted in radiographic challenges, including pseudoprogression. Conventional MR imaging has limitations in assessment of different forms of treatment-related heterogeneity, particularly regarding distinguishing true tumor progression from efficacious treatment responses. Advanced neuroimaging techniques, including diffusion magnetic resonance (MR), perfusion MR, and MR spectroscopy, may add value in the assessment of treatment-related heterogeneity. Observations suggest that recent delineation of specific response criteria for immunotherapy of adult brain tumors is likely relevant to the pediatric population and further validation in multicenter pediatric brain tumor peptide-based vaccine studies is warranted.

Advanced MRI for Pediatric Brain Tumors with Emphasis on Clinical Benefits

Conventional anatomic brain MRI is often limited in evaluating pediatric brain tumors, the most common solid tumors and a leading cause of death in children. Advanced brain MRI techniques have great potential to improve diagnostic performance in children with brain tumors and overcome diagnostic pitfalls resulting from diverse tumor pathologies as well as nonspecific or overlapped imaging findings. Advanced MRI techniques used for evaluating pediatric brain tumors include diffusion-weighted imaging, diffusion tensor imaging, functional MRI, perfusion imaging, spectroscopy, susceptibility-weighted imaging, and chemical exchange saturation transfer imaging. Because pediatric brain tumors differ from adult counterparts in various aspects, MRI protocols should be designed to achieve maximal clinical benefits in pediatric brain tumors. In this study, we review advanced MRI techniques and interpretation algorithms for pediatric brain tumors.

Magnetic resonance imaging based functional imaging in paediatric oncology

Imaging is central to management of solid tumours in children. Conventional magnetic resonance imaging (MRI) is the standard imaging modality for tumours of the central nervous system (CNS) and limbs and is increasingly used in the abdomen. It provides excellent structural detail, but imparts limited information about tumour type, aggressiveness, metastatic potential or early treatment response. MRI based functional imaging techniques, such as magnetic resonance spectroscopy, diffusion and perfusion weighted imaging, probe tissue properties to provide clinically important information about metabolites, structure and blood flow. This review describes the role of and evidence behind these functional imaging techniques in paediatric oncology and implications for integrating them into routine clinical practice.

Accuracy of conventional MRI for preoperative diagnosis of intracranial tumors: A retrospective cohort study of 762 cases

BACKGROUND

Conventional magnetic resonance imaging (MRI) is considered a valuable tool for preoperative diagnosis of intracranial tumors. We assessed its accuracy in the diagnosis of intracranial tumors in usual clinical practice.

MATERIALS AND METHODS

MRI reports of 762 patients who had undergone conventional brain MRI prior to surgery were retrospectively reviewed. A 4-grade scoring system was devised to establish diagnostic agreement. Each tumor type was compared with the corresponding pathological diagnoses by dichotomization. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated for the overall patient population as well as for each tumor type.

RESULTS

664 cases (87.1%) were tumor-positive, and 98 cases (12.9%) were tumor-negative. The most common tumor types were meningiomas, gliomas, pituitary adenomas and schwannomas. These four types together comprised 74.5% of all cases reviewed. Sensitivity and PPV for the overall population were 72.0-90.7% and 91.9-95.4%, respectively. Diagnostic accuracy differed among tumor types. Meningiomas, pituitary adenomas, schwannomas and cholesteatomas were more likely to be diagnosed correctly (sensitivities were 82.6-96.9%, 86.1-96.7%, 88.9-98.2% and 91.3-100.0%, respectively); while some other types like solitary fibrous tumors (SFTs) seemed difficult to identify. Gliomas tended to be confused with metastases, meningiomas with SFTs, and pituitary adenomas with craniopharyngiomas.

CONCLUSION

The accuracy of conventional MRI for diagnosing intracranial tumors is generally satisfactory but should not be too heavily relied upon, especially for certain tumor types. In cases of discrepancy, neurosurgeons are encouraged to confer with the reporting neuroradiologists to achieve optimal preoperative diagnoses.

Advanced MR imaging in hemispheric low-grade gliomas before surgery; the indications and limits in the pediatric age

INTRODUCTION

Advanced magnetic resonance imaging (MRI) techniques is an umbrella term that includes diffusion (DWI) and diffusion tensor (DTI), perfusion (PWI), spectroscopy (MRS), and functional (fMRI) imaging. These advanced modalities have improved the imaging of brain tumors and provided valuable additional information for treatment planning. Despite abundant literature on advanced MRI techniques in adult brain tumors, few reports exist for pediatric brain ones, potentially because of technical challenges.

REVIEW OF THE LITERATURE

The authors review techniques and clinical applications of DWI, PWI, MRS, and fMRI, in the setting of pediatric hemispheric low-grade gliomas.

PERSONAL EXPERIENCE

The authors propose their personal experience to highlight benefits and limits of advanced MR imaging in diagnosis, grading, and presurgical planning of pediatric hemispheric low-grade gliomas.

DISCUSSION

Advanced techniques should be used as complementary tools to conventional MRI, and in theory, the combined use of the three techniques should ensure achieving the best results in the diagnosis of hemispheric low-grade glioma and in presurgical planning to maximize tumor resection and preserve brain function.

FUTURE PERSPECTIVES

In the setting of pediatric neurooncology, these techniques can be used to distinguish low-grade from high-grade tumor. However, these methods have to be applied on a large scale to understand their real potential and clinical relapse, and further technical development is required to reduce the excessive scan times and other technical limitations.

False-positive magnetic resonance imaging findings in follow-up of pediatric patients with tumors of the central nervous system

Management of patients with central nervous system tumors relies largely on magnetic resonance imaging scans to document disease progression or recurrence. The finding of new lesions always presents the challenge of differentiating between post-surgical changes, radiation necrosis, gliosis, and tumor, submitting these patients to more aggressive therapy and more toxicity. We reviewed the medical records of three patients with primary central nervous system tumors treated at the Children’s Hospital Los Angeles who had new false-positive magnetic resonance imaging findings suggestive of tumor recurrence. All of them had complete total resection of primary tumor, had received involved-field radiation therapy, had biopsies confirming absence of viable tumor, and all three patients are long-term survivors. These cases exemplify that not everything that enhances on brain or spine magnetic resonance imaging is viable tumor, and a biopsy should always be considered in the decision-making process in evaluation of potentially recurrent central nervous system tumors in pediatric patients. A step-wise approach for such challenging cases is presented in this article.

Prognostic and predictive values of diffusion and perfusion MRI in paediatric intracranial ependymomas in a large national study

OBJECTIVE

To assess the relative cerebral blood volume (rCBV) and apparent diffusion coefficient (ADC) derived, respectively, from perfusion and diffusion pre-operative MRI of intracranial ependymomas and their predictive and prognostic values.

METHODS

Pre-operative MRI and clinical data for intracranial ependymomas diagnosed between January 2000 and December 2013 were retrospectively retrieved from a web-based national database. MRI data included diffusion (62 patients) and perfusion (20 patients) MRI. Patient age, histopathological diagnosis, tumour location, ADC, relative ADC (rADC) and rCBV were considered as potential factors in a survival analysis. Survival rates were estimated using the Kaplan-Meier method. Univariate analyses were performed using the log-rank test to compare groups. We also performed a multivariate analysis, applying the Cox proportional hazards model.

RESULTS

ADC and rADC values within hypointense regions differed significantly between grades II and III (p = 0.01). The 75th percentile of ADC within hypointense regions and the 25th percentile of rCBV within non-enhancing lesions were prognostic of disease-free survival (p = 0.004, p = 0.05). A significant correlation was found between the 75th percentile of rCBV and the 25th percentile of rADC (p = 0.01) in enhancing regions of grade-III tumours.

CONCLUSION

Pre-operative rADC and rCBV could be used as prognostic factors for clinical outcome and to predict histological grade in paediatric ependymomas.

ADVANCES IN KNOWLEDGE

Prognostic value of diffusion and perfusion MRI in paediatric ependymoma was found and may play a role in the prognostic classification of patients in order to design more tailored treatment strategies.

Proton MRS imaging in pediatric brain tumors

Magnetic resonance (MR) techniques offer a noninvasive, non-irradiating yet sensitive approach to diagnosing and monitoring pediatric brain tumors. Proton MR spectroscopy (MRS), as an adjunct to MRI, is being more widely applied to monitor the metabolic aspects of brain cancer. In vivo MRS biomarkers represent a promising advance and may influence treatment choice at both initial diagnosis and follow-up, given the inherent difficulties of sequential biopsies to monitor therapeutic response. When combined with anatomical or other types of imaging, MRS provides unique information regarding biochemistry in inoperable brain tumors and can complement neuropathological data, guide biopsies and enhance insight into therapeutic options. The combination of noninvasively acquired prognostic information and the high-resolution anatomical imaging provided by conventional MRI is expected to surpass molecular analysis and DNA microarray gene profiling, both of which, although promising, depend on invasive biopsy. This review focuses on recent data in the field of MRS in children with brain tumors.

Low Grade Gliomas in Children

Gliomas represent the most common solid tumor of the nervous system, and can occur as both low and high-grade tumors. Current risk stratification and treatment approaches rely heavily on the morphological classification of gliomas whereby low-grade gliomas have an excellent prognosis, particularly pilocytic astrocytomas, while high-grade gliomas have a poor prognosis. The past decade has witnessed a dramatic increase in scholars' knowledge of the biology of pediatric low-grade gliomas particularly through the advent of integrated genomics and next generation sequencing. Indeed, many of these biological advances are changing treatment paradigms, particularly in low-grade gliomas, where rationale targeted therapies are currently being explored in clinical trials. In this review the authors summarize the current approach to pediatric low grade gliomas and outline the biological advances over the past 10 years, which will be driving the next generation of clinical trials.

Presurgical assessment of cognitive function in pediatric brain tumor patients: feasibility and initial findings

BACKGROUND

Establishing a presurgical baseline of neurocognitive functioning for pediatric brain tumor patients is a high priority to identify level of functioning prior to medical interventions. However, few studies have obtained adequate samples of presurgery assessments.

METHODS

This study examines the feasibility of completing tests to assess pre-surgical neurocognitive functioning in 59 identified pediatric brain tumor patients.

RESULTS

Eighty-five percent of patients (n = 50) were referred by the neurosurgery team before surgery and 83% of patients (n = 49) enrolled in the study. A full battery, including both performance-based and parent-report measures of neurocognitive function, was completed for 54% (n = 32) of patients. Rates of completion for either parent-report or performance-based measures were 68% (n = 40) and 69% (n = 41), respectively. While the performance-based assessment fell within the average range (M = 95.4, SD = 14.7, 95% CI, 90.7-100.0), 32% of participants had scores one or more standard deviations below the mean, or twice the expected rate. Parent-reports indicated higher level of concern than the general population (M = 55.4, SD = 11.3, 95% CI, 51.8-59.0) and found that 35% fell one or more standard deviations above the mean, or more than twice the expected rate.

CONCLUSIONS

Results suggest it is feasible to conduct pre-surgical assessments with a portion of pediatric brain tumor patients upon diagnosis and these results compare favorably with prior research. However, nearly half of identified patients did not receive a full test battery. Identifying barriers to enrollment and participation in research are discussed as well as recommendations for future research.