Optimization of dual-energy imaging systems using generalized NEQ and imaging task

Area of Science:

• Medical Imaging Physics
• Radiological Sciences
• Diagnostic Imaging Technology

Background:

• Dual-energy (DE) imaging using flat-panel detectors (FPDs) offers advanced capabilities in various medical imaging applications.
• Optimizing DE imaging performance requires accounting for signal and noise propagation, including anatomical noise.

Purpose of the Study:

• To investigate and optimize the performance of FPD-based DE imaging systems.
• To develop a theoretical framework for optimizing DE image reconstruction, dose allocation, and kVp selection.

Main Methods:

• Incorporated anatomical noise (1/f characteristic) into noise-equivalent quanta (NEQ) to derive generalized NEQ (GNEQ).
• Utilized cascaded systems analysis to model signal and noise propagation in the DE imaging chain.
• Integrated a Fourier-based description of the imaging task with GNEQ to calculate a detectability index for optimization.

Main Results:

• Optimal kVp selection for DE imaging is dose-dependent, varying from [60/150] kVp at ~0.5 mGy ESD to [90/150] kVp at ~5.0 mGy ESD.
• Optimal low-energy technique is 60 kVp at very low dose (~0.05 mGy ESD), with high-kVp being less critical in the 120-150 kVp range.
• Optimal dose allocation (low-energy ESD/total ESD) ranged from 0.2 to 0.4 across different total dose levels.

Conclusions:

• The developed theoretical framework using GNEQ and task-based detectability index provides fundamental insights into DE imaging performance.
• Findings offer a basis for optimizing DE imaging system design, reconstruction parameters, and acquisition protocols.
• Double-shot DE imaging demonstrates approximately twice the detective quantum efficiency (DQE) compared to single-shot DE imaging.