Robustness of Optimal Energy Thresholds in Photon-counting Spectral CT

TL;DR

This study investigates how to optimally select energy thresholds in photon-counting spectral CT, demonstrating that a single threshold set can be effective across various imaging conditions, especially with more bins.

Contribution

It introduces a method for optimizing energy thresholds considering pileup and response imperfections, and assesses their robustness across different imaging scenarios.

Findings

Optimal thresholds do not always increase with attenuation when pileup is included.

Thresholds optimized for a 30 cm phantom are effective across various tissues and attenuations.

Using 6 or 8 bins balances near-optimal image quality with manageable data size.

Abstract

An important question when developing photon-counting detectors for computed tomography is how to select energy thresholds. In this work thresholds are optimized by maximizing signal-difference-to-noise ratio squared (SDNR2) in an optimally weighted image and signal-to-noise ratio squared (SNR2) in a gadolinium basis image in a silicon-strip detector and a cadmium zinc telluride (CZT) detector, factoring in pileup and imperfect energy response in both detectors. To investigate to what extent one single set of thresholds could be applied in various imaging tasks, the robustness of optimal thresholds with 2 to 8 bins is examined with the variation of phantom thicknesses and target materials. In contrast to previous studies, the optimal threshold locations don't always increase with increasing attenuation if pileup is included. Optimizing the thresholds for a 30 cm phantom yields near-optimal SDNR2 or SNR2 regardless of target tissue types and surrounding attenuation for both detectors. Having more than 3 bins reduces the need for changing the thresholds depending on anatomies and tissues. Using around 6 bins or 8 bins may give near-optimal SDNR2 or SNR2 without generating an unnecessarily large amount of data.