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

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.

Correlation of T1- to T2-weighted signal intensity ratio with T1- and T2-relaxation time and IDH mutation status in glioma

“…T1WI and T2WI in Digital Imaging and COmmunication in Medicine (DICOM) format were converted into Neuroimaging Informatics Technology Initiative (NIfTI) format using Mango software (version 4.0.1; University of Texas Health Science Center, https://ric.uthscsa.edu/mango/mango.html , accessed on March 6, 2022). We used an in-house imaging software incorporating an algorithm for reconstructing rT1/T2 images from T1WI and T2WI 24 . The algorithm and MATLAB codes for calculating rT1/T2 can be obtained as an open-source toolbox for SPM12 developed by Ganzetti et al ( https://www.nitrc.org/projects/mrtool/ , accessed on March 6, 2022) 18 .…”

Intensity scaling of conventional brain magnetic resonance images avoiding cerebral reference regions: A systematic review

“…Negative correlations of scaled T1w/T2w-ratios with T1- and T2-relaxation times were found within lower-grade glioma (T1-ralaxation: R 2 = 0.64; T2-relaxation: R 2 = 0.59) [ 30 ] and within non-contrast-enhancing glioblastoma lesions (T1-relaxation: R 2 = 0.002; T2-relaxation: R 2 = 0.07) [ 35 ].…”

“…Relation to quantitative imaging and MRI measures related to tissue microstructure. Twenty studies investigated relationships between scaled images and quantitative imaging[14,[18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37]. In total, scaled images were compared to 16 quantitative imaging methods (Fig3).…”

Qualitative MR features to identify non-enhancing tumors within glioblastoma’s T2-FLAIR hyperintense lesions

“…This observation is consistent with our result showing a lower Met-PET T/N ratio in the area with a positive "Around-rim" feature. We also included a new image feature named the "HighT1LowT2", deriving from our previous observation that brain tissues with high tumor burden show a more similar MRI intensity than those mainly composed of edematous change [23,24]. Here, it is noteworthy that each feature correlated signi cantly with the Met-PET T/N ratio, and combining these features improved the prediction accuracy of T2/FLAIR high-intensity lesions with high tumor burden.…”