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Updated: Jun 1, 2025

High-Resolution Cardiac Positron Emission Tomography/Computed Tomography for Small Animals
Published on: December 16, 2022
Optimizing energy threshold selection for low-concentration contrast agent quantification in small animal
Xiaoyu Hu1, Yuncheng Zhong1, Xun Jia1
1Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, MD, United States of America.
Abstract:
Objective.Gold nanoparticles (GNPs) are widely used for biological research and applications. The in-vivo concentration of GNPs is usually low due to biological safety concerns, thus posing a challenge for imaging. This work investigates on optimal energy threshold selection in photon-counting detector(PCD)-based CT (PCCT) for the quantification of low-concentration GNPs.Approach.We derived the mathematical expression of the upper bound of the material decomposition error in the gold image. Comprehensive simulations were implemented for cylindrical phantom with inserts of different GNP concentrations. CT scans of this phantom were simulated with a 140 kVp x-ray beam under a realistic pre-clinical CT dose range. The PCD energy thresholds from 30 to 110 keV were enumerated for 2,3-channel PCCT and the optimal energy thresholds were determined by searching for the lowest decomposition error.Main results.The optimal energy threshold(s) to minimize the decomposition error in gold image was 44 keV for the 2-channel PCCT and{34,40}keV for the 3-channel case. Numerical results also validated the derived upper bounds of the decomposition error.Significance.This work addressed the need for selecting appropriate energy thresholds for accurate quantification of contrast agent distributions in pre-clinical PCCT. Both the analytical expression of the upper bound of material decomposition error and simulation results showed that the balanced consideration on photon counting noise levels and the numerical properties of the decomposition matrix is required in selecting the appropriate energy thresholds to achieve the most accurate material decomposition.
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