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Prediction and Visualization of Non-Enhancing Tumor in Glioblastoma via T1w/T2w-Ratio Map

Authors :
Shota Yamamoto
Takahiro Sanada
Mio Sakai
Atsuko Arisawa
Naoki Kagawa
Eku Shimosegawa
Katsuyuki Nakanishi
Yonehiro Kanemura
Manabu Kinoshita
Haruhiko Kishima
Source :
Brain Sciences, Vol 12, Iss 1, p 99 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

Abstract

One of the challenges in glioblastoma (GBM) imaging is to visualize non-enhancing tumor (NET) lesions. The ratio of T1- and T2-weighted images (rT1/T2) is reported as a helpful imaging surrogate of microstructures of the brain. This research study investigated the possibility of using rT1/T2 as a surrogate for the T1- and T2-relaxation time of GBM to visualize NET effectively. The data of thirty-four histologically confirmed GBM patients whose T1-, T2- and contrast-enhanced T1-weighted MRI and 11C-methionine positron emission tomography (Met-PET) were available were collected for analysis. Two of them also underwent MR relaxometry with rT1/T2 reconstructed for all cases. Met-PET was used as ground truth with T2-FLAIR hyperintense lesion, with >1.5 in tumor-to-normal tissue ratio being NET. rT1/T2 values were compared with MR relaxometry and Met-PET. rT1/T2 values significantly correlated with both T1- and T2-relaxation times in a logarithmic manner (p < 0.05 for both cases). The distributions of rT1/T2 from Met-PET high and low T2-FLAIR hyperintense lesions were different and a novel metric named Likeliness of Methionine PET high (LMPH) deriving from rT1/T2 was statistically significant for detecting Met-PET high T2-FLAIR hyperintense lesions (mean AUC = 0.556 ± 0.117; p = 0.01). In conclusion, this research study supported the hypothesis that rT1/T2 could be a promising imaging marker for NET identification.

Details

Language :
English
ISSN :
20763425
Volume :
12
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Brain Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.ba0a8d134e344fb977c5c7733d29e58
Document Type :
article
Full Text :
https://doi.org/10.3390/brainsci12010099