Neurite orientation dispersion and density imaging and diffusion tensor imaging to facilitate distinction between infiltrating tumors and edemas in glioblastoma

Yoshiko Okita; Koji Takano; Soichiro Tateishi; Motohisa Hayashi; Mio Sakai; Manabu Kinoshita; Haruhiko Kishima; Katsuyuki Nakanishi

doi:10.1016/j.mri.2023.03.001

Neurite orientation dispersion and density imaging and diffusion tensor imaging to facilitate distinction between infiltrating tumors and edemas in glioblastoma

Magn Reson Imaging. 2023 Jul:100:18-25. doi: 10.1016/j.mri.2023.03.001. Epub 2023 Mar 15.

Authors

Yoshiko Okita¹, Koji Takano², Soichiro Tateishi³, Motohisa Hayashi², Mio Sakai³, Manabu Kinoshita⁴, Haruhiko Kishima⁵, Katsuyuki Nakanishi³

Affiliations

¹ Department of Neurosurgery, Osaka International Cancer Institute, 3-1-69 Otemae, Chuo-ku, Osaka 541-8567, Japan; Department of Neurosurgery, Graduate School of Medicine, Osaka University, 2-2 Yamadaoka, Suita, Osaka 565-0871, Japan. Electronic address: y-okita@nsurg.med.osaka-u.ac.jp.
² Department of Neurosurgery, Osaka International Cancer Institute, 3-1-69 Otemae, Chuo-ku, Osaka 541-8567, Japan.
³ Department of Diagnostic and Interventional Radiology, Osaka International Cancer Institute, 3-1-69 Otemae, Chuo-ku, Osaka 541-8567, Japan.
⁴ Department of Neurosurgery, Osaka International Cancer Institute, 3-1-69 Otemae, Chuo-ku, Osaka 541-8567, Japan; Department of Neurosurgery, Asahikawa Medical University, Midorigaoka-higashi 2-1-1-1, Asahikawa, Hokkaido 078-8510, Japan.
⁵ Department of Neurosurgery, Graduate School of Medicine, Osaka University, 2-2 Yamadaoka, Suita, Osaka 565-0871, Japan.

PMID: 36924806
DOI: 10.1016/j.mri.2023.03.001

Abstract

Background: Glioblastomas are highly infiltrative tumors, and differentiating between non-enhancing tumors (NETs) and vasogenic edema (Edemas) occurring in the non-enhancing T2-weighted hyperintense area is challenging. Here, we differentiated between NETs and Edemas in glioblastomas using neurite orientation dispersion and density imaging (NODDI) and diffusion tensor imaging (DTI).

Materials and methods: Data were collected retrospectively from 21 patients with primary glioblastomas, three with metastasis, and two with meningioma as controls. MRI data included T2 weighted images and contrast enhanced T1 weighted images, NODDI, and DTI. Three neurosurgeons manually assigned volumes of interest (VOIs) to the NETs and Edemas. The DTI and NODDI-derived parameters calculated for each VOI were fractional anisotropy (FA), apparent diffusion coefficient (ADC), intracellular volume fraction (ICVF), isotropic volume fraction (ISOVF), and orientation dispersion index.

Results: Sixteen and 14 VOIs were placed on NETs and Edemas, respectively. The ICVF, ISOVF, FA, and ADC values of NETs and Edemas differed significantly (p < 0.01). Receiver operating characteristic curve analysis revealed that using all parameters allowed for improved differentiation of NETs from Edemas (area under the curve = 0.918) from the use of NODDI parameters (0.910) or DTI parameters (0.899). Multiple logistic regression was performed with all parameters, and a predictive formula to differentiate between NETs and Edemas could be created and applied to the edematous regions of the negative control-group images; the tumor prediction degree was well below 0.5, confirming differentiation as edema.

Conclusions: Using NODDI and DTI may prove useful in differentiating NETs from Edemas in the non-contrast T2 hyperintensity region of glioblastomas.

Keywords: Glioblastoma; Neurite orientation dispersion and density imaging; Non-enhancing tumors; Vasogenic edema.

MeSH terms

Diffusion Magnetic Resonance Imaging / methods
Diffusion Tensor Imaging / methods
Edema
Glioblastoma* / diagnostic imaging
Humans
Meningeal Neoplasms*
Neurites
Retrospective Studies