State-of-the-art techniques using pre-operative brain MRI scans for survival prediction of glioblastoma multiforme patients and future research directions

Abstract

Objective Glioblastoma multiforme (GBM) is a grade IV brain tumour with very low life expectancy. Physicians and oncologists urgently require automated techniques in clinics for brain tumour segmentation (BTS) and survival prediction (SP) of GBM patients to perform precise surgery followed by chemotherapy treatment. Methods This study aims at examining the recent methodologies developed using automated learning and radiomics to automate the process of SP. Automated techniques use pre-operative raw magnetic resonance imaging (MRI) scans and clinical data related to GBM patients. All SP methods submitted for the multimodal brain tumour segmentation (BraTS) challenge are examined to extract the generic workflow for SP. ResultsThe maximum accuracies achieved by 21 state-of-the-art different SP techniques reviewed in this study are 65.5 and 61.7% using the validation and testing subsets of the BraTS dataset, respectively. The comparisons based on segmentation architectures, SP models, training parameters and hardware configurations have been made. ConclusionThe limited accuracies achieved in the literature led us to review the various automated methodologies and evaluation metrics to find out the research gaps and other findings related to the survival prognosis of GBM patients so that these accuracies can be improved in future. Finally, the paper provides the most promising future research directions to improve the performance of automated SP techniques and increase their clinical relevance.

Brain tumor detection and segmentation: Interactive framework with a visual interface and feedback facility for dynamically improved accuracy and trust

“…The different tissues of the brain is shown with various contrasts in different modalities of MRIs according to the imaging parameters like echo time, repetition time, flip angel etc. The four most common modalities for brain MRIs are T1-weighted (T1), T1-weighted contrast-enhanced (T1ce), T2-weighted (T2), and fluid attenuated inversion recovery (FLAIR) [12]. Generally, there are three anatomical positions for MRIs-axial, coronal and sagittal [13,14] due to three different plane cross sections.…”

Radiomics in the diagnosis of glioblastoma

“…Malignant regions of tumour may be divided into sub compartments [3]. Enhancing tumours (ET) are represent ed on CET1WI.…”

“…I. Contrastenhanced, T1weighted images. Intravenous administration of contrast media enables delineation of the tumour core [3]. Combined with data obtained from T1WI, radiomic features can precisely describe the type of lesion enhancement.…”

Treatment-wise glioblastoma survival Inference with multi-parametric preoperative MRI

“…Despite significant advances in medical treatments for brain tumors, the median survival duration for GBM patients remains limited. 1 The prognosis of GBM can vary widely depending on the patient's individual status and treatment approach.…”