Whole-Tumor Histogram Analysis of Multiple Diffusion Metrics for Glioma Genotyping

Histogram Analysis Based on Neurite Orientation Dispersion and Density MR Imaging for Differentiation Between Glioblastoma Multiforme and Solitary Brain Metastasis and Comparison of the Diagnostic Performance of Two ROI Placements

“…This also will reduce the complexity of the microstructure to some extent, resulting in higher skewness in GBM than in SBM. Recent studies have reported that NODDI technology can identify more different tissue components within tumors than conventional imaging, and the cell density may play an important role here because ICVF shows similar performance to other non‐Gaussian metrics 29,31,37 . The ICVF max in GBM may reflect the dense region of cell structure and relate to tumor parenchymal regions.…”

“…30 However, when applied to tumors, the elevated ICVF can be explained by the presence of restrictive structures with restrictions in all direction, which is similar to the evaluation of ODI. 31 The higher ICVF min of GBM may be related to infiltrating tumor cells of the edema around GBM, which raises the lower limit of ICVF to some extent.…”

“…Recent studies have reported that NODDI technology can identify more different tissue components within tumors than conventional imaging, and the cell density may play an important role here because ICVF shows similar performance to other non-Gaussian metrics. 29,31,37 The ICVF max in GBM may reflect the dense region of cell structure and relate to tumor parenchymal regions. This is consistent with the internal structure and pathological characteristics of GBM and SBM.…”