A Linearized Fit Model for Robust Shape Parameterization of FET-PET TACs

Area of Science:

• Nuclear Medicine
• Radiochemistry
• Neuro-oncology

Background:

• Kinetic analysis of O-(2-[18F]fluoroethyl)-L-tyrosine (FET) time-activity curves (TACs) aids glioma diagnosis.
• Current methods often rely on averaged TACs and visual inspection, limiting detailed kinetic assessment.

Purpose of the Study:

• To derive and validate a linearized model for FET-PET TAC kinetic analysis.
• To assess the reliability of automatic voxel-wise TAC kinetic analysis.
• To evaluate the diagnostic performance of extracted parameters for distinguishing IDH-wildtype (wt) from IDH-mutant (mut) gliomas.

Main Methods:

• Developed and validated a linearized kinetic model for FET-PET TACs.
• Performed receiver-operating characteristic analysis on 33 adult glioma patients.
• Assessed voxel-wise fitting for kinetic parameter extraction and uncertainty.

Main Results:

• The linearized model showed high agreement with measured FET-PET TACs.
• Small relative parameter uncertainties were achieved with the linearized model.
• Optimal differentiation between IDH-wt and IDH-mut gliomas was observed using the linearized model fitted to TACs from 4-50 min p.i.
• Voxel-wise fitting was computationally efficient (≈ 1 min/slice) with parameter uncertainties < 80%.

Conclusions:

• The linearized kinetic model provides a robust and accurate method for analyzing FET-PET TACs in glioma.
• Voxel-wise analysis using this model enables reliable differentiation of IDH mutation status in gliomas.
• This approach enhances diagnostic capabilities in neuro-oncology, potentially improving patient management.