Keywords: Tumors (Pre-Treatment), Diagnosis/Prediction
Motivation: To demonstrate the feasibility of using continuous-time random walk (CTRW) and fractional order calculus (FROC) models with histogram analysis in identifying molecular biomarkers in diffuse gliomas.
Goal(s): To non-invasively differentiate glioma molecular subtypes (IDH1, ATRX, MGMT, TERT) using multi-b-value DWI, ultimately aiding personalized clinical management.
Approach: Histogram parameters of CTRW and FROC models and mean ADC were compared across molecular states using student-t or Mann-Whitney U test, with ROC curves evaluating diagnostic performance.
Results: CTRW and FROC models outperformed mean ADC in IDH1 genotyping. The 90th CTRW_Dm, median CTRW_β and 10th CTRW_β showed the highest diagnostic performance for ATRX, MGMT, and TERT, respectively.
Impact: The CTRW and FROC models have the potential to preoperatively discriminate different molecular subtypes (IDH1, ATRX, MGMT, and TERT) in diffuse gliomas, which can help clinical physicians in treatment selection and prognostic assessment for glioma patients.
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