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

Thalamic Microstructural Alterations as Revealed by the T1/T2 Ratio in Chronic Pain Patients

Background/Objectives: Neuroimaging biomarkers could offer more objective measures of the pain experience. This study investigated rT1/T2 maps of the brain as a novel biomarker for chronic pain in patients with central post-stroke pain (PSP) and persistent spinal pain syndrome type 2 (PSPS-II). Methods: Patients with PSP and PSPS-II were retrospectively included alongside healthy controls. Bias correction and intensity normalization were applied to the T1-weighted and T2-weighted images to generate the rT1/T2 maps of the brain. Subsequently, rT1/T2 maps were spatially correlated with neurotransmitter atlases derived from molecular imaging. Results: In total, 15 PSPS-II patients, 11 PSP patients, and 18 healthy controls were included. No significant differences between patient and control demographics were found. Significant decreases in rT1/T2 signal intensity (p < 0.001) were observed in the dorsal and medial part of the thalamus, left caudate nucleus, cuneus, superior frontal gyrus, and dorsal cervicomedullary junction in PSP patients. No significant changes were found in rT1/T2 signal intensity in PSPS-II patients. Significant correlations were found with CB1-, 5HT2a-, and mGluR5-receptor maps (pFDR = 0.003, 0.030, and 0.030, respectively) for the PSP patients and with CB1-, 5HT1a-, 5HT2a-, KappaOp-, and mGluR5-receptor maps (pFDR = 0.003, 0.002, 0.002, 0.003, and 0.002, respectively) in PSPS-II patients. Conclusions: These findings suggest that microstructural alterations occur in the thalamus, cuneus, and dorsal cervicomedullary junction in patients with PSP. The lack of significant findings in rT1/T2 in PSPS-II patients combined with the significant correlations with multiple neurotransmitter maps suggests varying degrees of microstructural deterioration in both chronic pain syndromes, although further research is warranted.

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

Current literature emphasizes surgical complexities and customized resection for managing insular gliomas; however, radiogenomic investigations into prognostic radiomic traits remain limited. We aimed to develop and validate a radiomic model using multiparametric magnetic resonance imaging (MRI) for prognostic prediction and to reveal the underlying biological mechanisms. Radiomic features from preoperative MRI were utilized to develop and validate a radiomic risk signature (RRS) for insular gliomas, validated through paired MRI and RNA-seq data (N = 39), to identify core pathways underlying the RRS and individual prognostic radiomic features. An 18-feature-based RRS was established for overall survival (OS) prediction. Gene set enrichment analysis (GSEA) and weighted gene coexpression network analysis (WGCNA) were used to identify intersectional pathways. In total, 364 patients with insular gliomas (training set, N = 295; validation set, N = 69) were enrolled. RRS was significantly associated with insular glioma OS (log-rank p = 0.00058; HR = 3.595, 95% CI:1.636-7.898) in the validation set. The radiomic-pathological-clinical model (R-P-CM) displayed enhanced reliability and accuracy in prognostic prediction. The radiogenomic analysis revealed 322 intersectional pathways through GSEA and WGCNA fusion; 13 prognostic radiomic features were significantly correlated with these intersectional pathways. The RRS demonstrated independent predictive value for insular glioma prognosis compared with established clinical and pathological profiles. The biological basis for prognostic radiomic indicators includes immune, proliferative, migratory, metabolic, and cellular biological function-related pathways.

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

BACKGROUND

Conventional brain magnetic resonance imaging (MRI) produces image intensities that have an arbitrary scale, hampering quantification. Intensity scaling aims to overcome this shortfall. As neurodegenerative and inflammatory disorders may affect all brain compartments, reference regions within the brain may be misleading. Here we summarize approaches for intensity scaling of conventional T1-weighted (w) and T2w brain MRI avoiding reference regions within the brain.

METHODS

Literature was searched in the databases of Scopus, PubMed, and Web of Science. We included only studies that avoided reference regions within the brain for intensity scaling and provided validating evidence, which we divided into four categories: 1) comparative variance reduction, 2) comparative correlation with clinical parameters, 3) relation to quantitative imaging, or 4) relation to histology.

RESULTS

Of the 3825 studies screened, 24 fulfilled the inclusion criteria. Three studies used scaled T1w images, 2 scaled T2w images, and 21 T1w/T2w-ratio calculation (with double counts). A robust reduction in variance was reported. Twenty studies investigated the relation of scaled intensities to different types of quantitative imaging. Statistically significant correlations with clinical or demographic data were reported in 8 studies. Four studies reporting the relation to histology gave no clear picture of the main signal driver of conventional T1w and T2w MRI sequences.

CONCLUSIONS

T1w/T2w-ratio calculation was applied most often. Variance reduction and correlations with other measures suggest a biologically meaningful signal harmonization. However, there are open methodological questions and uncertainty on its biological underpinning. Validation evidence on other scaling methods is even sparser.