Morphologic Features on MR Imaging Classify Multifocal Glioblastomas in Different Prognostic Groups

Artificial intelligence-based MRI radiomics and radiogenomics in glioma

The specific genetic subtypes that gliomas exhibit result in variable clinical courses and the need to involve multidisciplinary teams of neurologists, epileptologists, neurooncologists and neurosurgeons. Currently, the diagnosis of gliomas pivots mainly around the preliminary radiological findings and the subsequent definitive surgical diagnosis (via surgical sampling). Radiomics and radiogenomics present a potential to precisely diagnose and predict survival and treatment responses, via morphological, textural, and functional features derived from MRI data, as well as genomic data. In spite of their advantages, it is still lacking standardized processes of feature extraction and analysis methodology among different research groups, which have made external validations infeasible. Radiomics and radiogenomics can be used to better understand the genomic basis of gliomas, such as tumor spatial heterogeneity, treatment response, molecular classifications and tumor microenvironment immune infiltration. These novel techniques have also been used to predict histological features, grade or even overall survival in gliomas. In this review, workflows of radiomics and radiogenomics are elucidated, with recent research on machine learning or artificial intelligence in glioma.

RETROSPECTIVE EVALUATION OF MRI PATTERN OF GLIOBLASTOMA IN A TERTIARY HOSPITAL IN NIGERIA

Introduction

Malignant gliomas, especially glioblastomas, are among the most aggressive and devastating of cancers, commonly producing profound progressive disability and leading to death in most cases. Conventional magnetic resonance (MR) imaging with gadolinium-based contrast agents is the most widely established and most useful tool in the characterization of cerebral tumors including Glioblastomas. This study aims to describe the imaging characteristics of Glioblastoma in African patients using conventional MR imaging.

Methodology

This was a retrospective cross-sectional study carried out at a Nigerian tertiary hospital. The demographic data, MR images and reports of patients with imaging and histological diagnosis of Glioblastoma between January 2003 and September 2017 were retrieved and reviewed. All the recorded data were analyzed using simple proportion and descriptive statistics with the Statistical Package for Social Sciences (SPSS) version 20.0 software for Windows.

Results

One hundred and twenty-two (122) patients had brain tumors during the review period, out of which 14 (11.5%) had histologically confirmed glioblastoma. The male- to -female ratio was 2.5 to 1.0. The age ranged between 14 and 72 years with a mean age of 49.6 years SD ±16.3. Twelve (85.7%) patients had solitary tumors and 2 (14.3%) had multiple tumors. Six (42.9%) were found on the right hemisphere only, 5 (35.7%) were found on the left hemisphere while 3 (21.4%) traversed both hemispheres. All tumors showed inhomogeneous enhancement and significant midline shift to the contra-lateral side of greater than 3mm. Only 1 (7.1%) tumor showed evidence of intra-tumoral bleed detected on T2* sequence.

Conclusion

Glioblastoma is a known aggressive brain tumor with unique MR imaging characteristics. While midline shift is typical, intra-tumoral bleeding may be an uncommon finding at presentation in our center.

Prognostic factors affecting outcome of multifocal or multicentric glioblastoma: A scoping review

It has been reported that patients with multiple lesions have shorter overall survival compared to single lesion in glioblastoma (GBM). Number of lesions can profoundly impact the prognosis and treatment outcome in GBM. In view of the advancement of imaging, multiple GBM (mGBM) lesions are increasingly recognized and reported. The scoping review was conducted and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension statement for systematic review. Database was searched to collect relevant articles based on predefined eligibility criteria. Our observations suggest that multifocal/multicentric GBM has poorer outcome compared to GBM with singular lesion (sGBM). As the factors influencing the prognosis and outcome is poorly understood and there is no consensus in the existing literature, this review is clinically relevant. As patients with single lesion are more likely to undergo gross total excision, it is likely that further adjuvant treatment may be decided by extent of resection. This review will be helpful for design of further prospective randomized studies for optimal management of mGBM.

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.

Radiomics and radiogenomics in gliomas: a contemporary update

The natural history and treatment landscape of primary brain tumours are complicated by the varied tumour behaviour of primary or secondary gliomas (high-grade transformation of low-grade lesions), as well as the dilemmas with identification of radiation necrosis, tumour progression, and pseudoprogression on MRI. Radiomics and radiogenomics promise to offer precise diagnosis, predict prognosis, and assess tumour response to modern chemotherapy/immunotherapy and radiation therapy. This is achieved by a triumvirate of morphological, textural, and functional signatures, derived from a high-throughput extraction of quantitative voxel-level MR image metrics. However, the lack of standardisation of acquisition parameters and inconsistent methodology between working groups have made validations unreliable, hence multi-centre studies involving heterogenous study populations are warranted. We elucidate novel radiomic and radiogenomic workflow concepts and state-of-the-art descriptors in sub-visual MR image processing, with relevant literature on applications of such machine learning techniques in glioma management.

On the Prognosis of Multifocal Glioblastoma: An Evaluation Incorporating Volumetric MRI

Primary glioblastoma (GBM), IDH-wildtype, especially with multifocal appearance/growth (mGBM), is associated with very poor prognosis. Several clinical parameters have been identified to provide prognostic value in both unifocal GBM (uGBM) and mGBM, but information about the influence of radiological parameters on survival for mGBM cohorts is scarce. This study evaluated the prognostic value of several volumetric parameters derived from magnetic resonance imaging (MRI). Data from the Department of Neurosurgery, Leipzig University Hospital, were retrospectively analyzed. Patients treated between 2014 and 2019, aged older than 18 years and with adequate peri-operative MRI were included. Volumetric assessment was performed manually. One hundred and eighty-three patients were included. Survival of patients with mGBM was significantly shorter (p < 0.0001). Univariate analysis revealed extent of resection, adjuvant therapy regimen, residual tumor volume, tumor necrosis volume and ratio of tumor necrosis to initial volume as statistically significant for overall survival. In multivariate Cox regression, however, only EOR (for uGBM and the entire cohort) and adjuvant therapy were independently significant for survival. Decreased ratio of tumor necrosis to initial tumor volume and extent of resection were associated with prolonged survival in mGBM but failed to achieve statistical significance in multivariate analysis.

Decoding and Systematization of Medical Imaging Features of Multiple Human Malignancies

Purpose

To summarize the data of previously reported medical imaging features on human malignancies to provide a scientific basis for more credible imaging feature selection for future studies.

Materials and Methods

A search was performed in PubMed from database inception through March 23, 2018, for studies clearly stating the decoding of medical imaging features for malignancy-related objectives and/or hypotheses. The Newcastle-Ottawa scale was used for quality assessment of the included studies. Unsupervised hierarchical clustering was performed on the manually extracted features from each included study to identify the application rules of medical imaging features across human malignancies. CT images of 1000 retrospective patients with non–small cell lung cancer were used to reveal a pattern for the value distribution of complex texture features.

Results

A total of 5026 imaging features of malignancies affecting 20 parts of the human body from 930 original articles were collated and assessed in this study. A meta-feature construct was proposed to facilitate the investigation of details of any high-dimensional complex imaging features of malignancy. A correlation atlas was constructed to clarify the general rules of applying medical imaging features to the analysis of human malignancy. Assessment of this data revealed a pattern of value distributions of the most commonly reported texture features across human malignancies. Furthermore, the significant expression of the gene mutational signature 1B across human cancer was highly consistent with the presence of the run length imaging feature across different human malignancy types.

Conclusion

The results of this study may facilitate more credible imaging feature selection in all oncology tasks across a wide spectrum of human malignancies and help to reduce bias and redundancies in future medical imaging studies.

Keywords: Computer Aided Diagnosis (CAD), Computer Applications-General (Informatics), Evidence Based Medicine, Informatics, Research Design, Statistics, Technology Assessment

Supplemental material is available for this article.

Published under a CC BY 4.0 license.

Molecular characteristics and clinical features of multifocal glioblastoma

INTRODUCTION

Glioblastomas (GBMs) usually occur as a solitary lesion; however, about 0.5-35% present with multiple lesions (M-GBM). The genetic landscape of GBMs have been thoroughly investigated; nevertheless, differences between M-GBM and single-foci GBM (S-GBM) remains unclear. The present study aimed to determine differences in clinical and molecular characteristics between M-GBM and S-GBM.

METHODS

A retrospective review of multifocal/multicentric infiltrative gliomas (M-IG) from our institutional database was performed. Demographics, clinical, radiological, and genetic features were obtained and compared between M-GBM IDH-wild type (IDH-WT) vs 193 S-GBM IDH-WT. Mutations were examined by a targeted next-generation sequencing assay interrogating 315 genes.

RESULTS

33M-IG were identified from which 94% were diagnosed as M-GBM IDH-WT, the remaining 6% were diagnosed as astrocytomas IDH-mutant. M-GBM and S-GBM comparison revealed that EGFR alterations were more frequent in M-GBM (65% vs 42% p = 0.019). Furthermore, concomitant EGFR/PTEN alterations were more common in M-GBM vs. S-GBM (36% vs 19%) as well as compared to TCGA (21%). No statistically significant differences in overall survival were observed between M-GBM and S-GBM; however, within the M-GBM cohort, patients harboring KDR alterations had a worse survival (KDR-altered 6.7 vs KDR-WT 16.6 months, p = 0.038).

CONCLUSIONS

The results of the present study demonstrate that M-GBM genetically resembles S-GBM, however, M-GBM harbor higher frequency of EGFR alterations and co-occurrence of EGFR/PTEN alterations, which may account for their highly malignant and invasive phenotype. Further study of genetic alterations including differences between multifocal and multicentric GBMs are warranted, which may identify potential targets for this aggressive tumor.

Resection versus biopsy in the treatment of multifocal glioblastoma: a weighted survival analysis

OBJECT

Diffuse tumor invasion in multifocal/multicentric GBM (mGBM) often foreshadows poor survival outcome. The correlation between extent of resection in gliomas and patient outcome is well described. The objective of this study was to assess the effect of gross total resection compared to biopsy for mGBM on patient overall survival and progression free survival.

METHODS

Thirty-four patients with mGBM received either biopsy or resection of their largest enhancing lesion from 2011 to 2019. Relevant demographic, peri-operative, and radiographic data were collected. Tumor burden and extent of resection was assessed through measurement of pre-operative and post-operative contrast-enhancing volume. An adjusted Kaplan-Meier survival analysis was conducted using inverse probability of treatment weighting (IPTW) to account for the covariates of age, number of lesions, satellite tumor volume, total pre-operative tumor volume, degree of spread, and location.

RESULTS

Thirty-four patients were identified with sixteen (47.1%) and eighteen (52.9%) patients receiving resection and biopsy respectively. Patients receiving resection exhibited greater median overall survival but not progression free survival compared to biopsy on IPTW analysis (p = 0.026, p = 0.411). Greater than or equal to 85% extent of resection was significantly associated with increased median overall survival (p = 0.016).

CONCLUSION

Overall, our study suggests that resection of the largest contrast-enhancing lesion may provide a survival benefit. Our volumetric analysis suggests that a greater degree of resection results in improved survival. Employing IPTW analysis, we sought to control for selection bias in our retrospective analysis. Thus, aggressive surgical treatment of mGBM may offer improved outcomes. Further clinical trials are needed.