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

Abstract

The current study aimed to test whether the ratio of T1-weighted to T2-weighted signal intensity (T1W/T2W ratio: rT1/T2) derived from conventional MRI could act as a surrogate relaxation time predictive of IDH mutation status in histologically lower-grade gliomas. Strong exponential correlations were found between rT1/T2 and each of T1- and T2-relaxation times in eight subjects (rT1/T2 = 1.63exp−0.0005T1-relax + 0.30 and rT1/T2 = 1.27exp−0.0081T2-relax + 0.48; R2 = 0.64 and 0.59, respectively). In a test cohort of 25 patients, mean rT1/T2 (mrT1/T2) was significantly higher in IDHwt tumors than in IDHmt tumors (p < 0.05) and the optimal cut-off of mrT1/T2 for discriminating IDHmt was 0.666–0.677, (AUC = 0.75, p < 0.05), which was validated in an external domestic cohort of 29 patients (AUC = 0.75, p = 0.02). However, this result was not validated in an external international cohort derived from TCIA/TCGA (AUC = 0.63, p = 0.08). The t-Distributed Stochastic Neighbor Embedding analysis revealed a greater diversity in image characteristics within the TCIA/TCGA cohort than in the two domestic cohorts. The failure of external validation in the TCIA/TCGA cohort could be attributed to its wider variety of original imaging characteristics.

Radiomic profiling for insular diffuse glioma stratification with distinct biologic pathway activities

“…The 3D multiparametric characterization of the entire tumor by this RRS yielded a high C‐index of 0.726 in the validation set. These findings corroborate previous studies indicating the efficacy of intensities and textural features in capturing intratumoral heterogeneity and conveying potent prognostic insights for glioma patients 23,24,26,27 …”

“…These findings corroborate previous studies indicating the efficacy of intensities and textural features in capturing intratumoral heterogeneity and conveying potent prognostic insights for glioma patients. 23,24,26,27 In previous transcriptome studies, two analytical methods with different emphases, GSEA and WGCNA, [28][29][30] have been used to explore the specific biological pathways and biomarkers associated with glioma prognosis. WGCNA by Sun et al 12 established links between biological processes, such as immune, proliferative, treatment-responsive, and cellular functions, and radiomic phenotypes predictive of OS in GBM.…”

“…These findings corroborate previous studies indicating the efficacy of intensities and textural features in capturing intratumoral heterogeneity and conveying potent prognostic insights for glioma patients. 23 , 24 , 26 , 27 …”

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).…”