Advanced imaging in adult diffusely infiltrating low-grade gliomas

Abstract

The adult diffusely infiltrating low-grade gliomas (LGGs) are typically IDH mutant and slow-growing gliomas having moderately increased cellularity generally without mitosis, necrosis, and microvascular proliferation. Supra-total resection of LGG significantly increases the overall survival by delaying malignant transformation compared with a simple debulking so accurate MR diagnosis is crucial for treatment planning. Data from meta-analysis support the addition of diffusion and perfusion-weighted MR imaging and MR spectroscopy in the diagnosis of suspected LGG. Typically, LGG has lower cellularity (ADCmin), angiogenesis (rCBVmax), capillary permeability (Ktrans), and mitotic activity (Cho/Cr ratio) compared to high-grade glioma. The identification of 2-hydroxyglutarate by MR spectroscopy can reflect the IDH status of the tumor. The initial low ADCmin, high rCBVmax, and Ktrans values are consistent with the poor prognosis. The gradual increase in intratumoral Cho/Cr ratio and rCBVmax values are well correlated with tumor progression. Besides MR-based technical artifacts, which are minimized by the voxel-based assessment of data obtained by histogram analysis, the problems derived from the diversity and the analysis of imaging data should be solved by using artificial intelligence techniques. The quantitative multiparametric MR imaging of LGG can either improve the diagnostic accuracy of their differential diagnosis or assess their prognosis.

Magnetic Resonance Imaging Derived Biomarkers of IDH Mutation Status and Overall Survival in Grade III Astrocytomas

“…These results are consistent with the recent literature [10,20]. Indeed, after the 2016 WHO brain tumor classification update, some studies investigated the role of MRI in the prediction of the IDH mutational status in gliomas [15][16][17][18][19][20][21]. However, most of them evaluated the imaging characteristics of IDH molecular subgroups of mixed patient's samples, from grade II to grade IV gliomas.…”

“…In particular, inverse significant correlations between ADC, cell count and ki67 have been reported [12,13]. Recently, some studies have shown that ADC maps may easily discriminate the IDH mutations status, but most of them did not consider a homogeneous group of gliomas in terms of grading and histology [14][15][16][17][18]. Indeed, ADC can be influenced by histology and grading [19][20][21][22].…”

A Multiparametric MRI-Based Radiomics Analysis to Efficiently Classify Tumor Subregions of Glioblastoma: A Pilot Study in Machine Learning

“…Diffusion-weighted MR imaging together with ADC maps reflect hindered and restricted diffusion pools within a voxel on diffusion-weighted MR images. This is always in the routine diagnostic protocol, but diffusion kurtosis imaging is usually reserved for research purposes [ 28 ]. Within a specific ROI, areas of necrosis and peritumoral edema can increase ADC values, which increase cellular density architecture due to the reduced ADC values [ 27 ].…”

“…The ADC threshold value of 1185 × 10 −6 mm 2 /s has a sensitivity of 97.6% and specificity of 53.1% in the discrimination of high-grade (grades III and IV) and low-grade (grade II) gliomas. Regarding tumor physical processes, MRS can be used to study tumor biomarkers such as IDH mutations, morphological image processing for quantitative analysis, and metabolism in noninvasive investigations of the link between the molecular basis of GBM and imaging attributes [ 27 , 28 ]. Most high-grade tumors have greater choline concentrations in astrocytoma.…”

Stratification by Tumor Grade Groups in a Holistic Evaluation of Machine Learning for Brain Tumor Segmentation

“…On the other hand, low grade tumors appear hyperintense on a FLAIR sequence with or without clear margins. On the pre-contrast T1-weighted sequences, the lesions tend to be hypointense and typically do not enhance following administration of gadolinium based agents (Forst et al, 2014;Bulakbaşı and Paksoy, 2019).…”