Calibration methods influence quantitative material decomposition in photon-counting spectral CT

Abstract

Photon-counting detectors and nanoparticle contrast agents can potentially enable molecular imaging and material decomposition in computed tomography (CT). Material decomposition has been investigated using both simulated and acquired data sets. However, the effect of calibration methods on material decomposition has not been systematically investigated. Therefore, the objective of this study was to investigate the influence of the range and number of contrast agent concentrations within a modular calibration phantom on quantitative material decomposition. A commerciallyavailable photon-counting spectral micro-CT (MARS Bioimaging) was used to acquire images with five energy bins selected to normalize photon counts and leverage the contrast agent k-edge. Material basis matrix values were determined using multiple linear regression models and material decomposition was performed using a maximum a posteriori estimator. The accuracy of quantitative material decomposition was evaluated by the root mean squared error (RMSE), specificity, sensitivity, and area under the curve (AUC). An increased maximum concentration (range) in the calibration significantly improved RMSE, specificity and AUC. The effects of an increased number of concentrations in the calibration were not statistically significant for the conditions in this study. The overall results demonstrated that the accuracy of quantitative material decomposition in spectral CT is significantly influenced by calibration methods, which must therefore be carefully considered for the intended diagnostic imaging application.