Neuroplasticity of Glioma Patients: Brain Structure and Topological Network

Abstract

Glioma is the most common primary malignant brain tumor in adults. It accounts for about 75% of such tumors and occurs more commonly in men. The incidence rate has been increasing in the past 30 years. Moreover, the 5-year overall survival rate of glioma patients is < 35%. Different locations, grades, and molecular characteristics of gliomas can lead to different behavioral deficits and prognosis, which are closely related to patients' quality of life and associated with neuroplasticity. Some advanced magnetic resonance imaging (MRI) technologies can explore the neuroplasticity of structural, topological, biochemical metabolism, and related mechanisms, which may contribute to the improvement of prognosis and function in glioma patients. In this review, we summarized the studies conducted on structural and topological plasticity of glioma patients through different MRI technologies and discussed future research directions. Previous studies have found that glioma itself and related functional impairments can lead to structural and topological plasticity using multimodal MRI. However, neuroplasticity caused by highly heterogeneous gliomas is not fully understood, and should be further explored through multimodal MRI. In addition, the individualized prediction of functional prognosis of glioma patients from the functional level based on machine learning (ML) is promising. These approaches and the introduction of ML can further shed light on the neuroplasticity and related mechanism of the brain, which will be helpful for management of glioma patients.

Prediction of Survival of Glioblastoma Patients Using Local Spatial Relationships and Global Structure Awareness in FLAIR MRI Brain Images

“…This means that the brain's global structure correlates with survival prediction in glioblastoma patients. Finally, neuroplasticity of structural, topological, biochemical metabolism, and related mechanisms of the brain come through multimodal MRI [13], which may contribute to the improvement of prognosis and function in glioma patients.…”

“…We believe that local spatial relationships in MRI brain images can assist in the understanding of brain structure and lead to improved prediction of survival times. Additionally, many papers [9,10,11,12,13] about the global structure of the brain has proven its correlation with survival prediction in glioblastoma patients. Firstly, the disruptions in the normal-appearing brain beyond the lesion could mediate the topological alteration of the connectome associated with worse patient survival [9].…”

“…The impact of glioblastoma on global brain function, including functional communication between brain regions far from the tumor, has been carefully investigated in previous research [12]. Finally, neuroplasticity of structural, topological, biochemical metabolism, and related mechanisms of the brain come through multimodal MRI [13], which may contribute to the improvement of prognosis and function in glioma patients. Based on the valuable global structure information with prognosis in glioblastoma patients, as we mentioned, we therefore integrated knowledge about the global structure as an embedding feature vector in our survival prediction network.…”

Intraoperative Stimulation Mapping in Neurosurgery for Anesthesiologists—Part 1: The Technical Nuances

“…97 Brain tumor progression also leads to functional reorganization over time, which may complicate resection guided by imaging only. [98][99][100][101][102] Thus, ISM combined with preoperative functional neuroimaging increases the precision of identifying critical cortical and subcortical structures for preservation during surgery. 88, [103][104][105][106][107]…”

Voxel based morphometry-detected white matter volume loss after multi-modality treatment in high grade glioma patients

“…Voxel Based Morphometry (VBM) analysis allows for voxel-wise comparison of tissue volume changes between different MRI timepoints for a population [ 12 , 13 ]. VBM analysis has previously shown to be very useful in detecting longitudinal volume changes in glioma patients [ 14 – 16 ]. However if, and to what extent treatment affects healthy contralateral brain tissue during treatment, remains largely unknown.…”