Ataei, Afrouz

Abstract Background Dual‐contrast imaging of iodine and bismuth has shown promise in previous phantom and animal studies utilizing spectral CT. However, these studies often employed Pepto‐Bismol containing bismuth subsalicylate with dosages exceeding the recommended limits for human consumption, limiting their clinical applicability. Purpose The purpose of this study was to improve iodine–bismuth dual‐contrast imaging on a clinical photon‐counting CT (PCCT) system using a noise‐optimized virtual monoenergetic imaging (VMI) approach. Methods Four bismuth samples (0.6, 1.3, 2.5, and 5.1 mg/mL) and three iodine rods (1.0, 2.0, and 5.0 mg/mL) were inserted into a multi‐energy CT phantom and scanned on a PCCT system at 140 kV. VMIs were generated from 40 to 190 keV in 10 keV increments. Iodine and bismuth maps were computed for all possible keV pairs using a generic image‐based three‐material decomposition method and compared with maps generated from the original low‐/high‐energy PCCT images. Mass concentrations, noise levels, and individual as well as joint root‐mean‐square error (RMSE) for iodine and bismuth were measured to determine the optimal keV pair. The contrast‐to‐noise ratios (CNRs) of low concentration samples (bismuth: 0.6 and 1.3 mg/mL; iodine: 1.0 mg/mL) were calculated at the optimal keV pair and compared to the values determined with the original PCCT images. In an IRB‐approved feasibility study, a research patient was administered two doses of Pepto‐Bismol prior to a routine abdomen‐pelvis CT scan. Material decomposition was performed using both the original low‐/high‐energy images and the optimal VMI pair identified in the phantom study. Bismuth signals in the stomach and proximal small bowel were assessed qualitatively and quantitatively. Results The VMI pair of 110 and 190 keV was determined to be optimal, achieving the lowest joint RMSE of 0.49 mg/mL, compared to 1.42 mg/mL for the original low‐/high‐energy pair. It also yielded the highest CNR, representing a 190–318% improvement over the original low/high‐energy decomposition. Qualitatively, both phantom and patient studies demonstrated improved iodine–bismuth separation and reduced noise using the optimized VMI pair. Conclusions These findings suggest that noise‐optimized VMI selection can enhance dual‐contrast material decomposition performance on clinical PCCT, supporting its potential for translation into gastrointestinal imaging applications.

Simultaneous dual-contrast imaging of iodine and bismuth has shown promise in prior phantom and animal studies utilizing spectral CT. However, it is noted that in previous studies, Pepto-Bismol has frequently been employed as the source of bismuth, exceeding the recommended levels for human subjects. This investigation sought to assess the feasibility of visually differentiating and precisely quantifying low-concentration bismuth using clinical dual-source photon-counting CT (PCCT) in a scenario involving both iodinated and bismuth-based contrast materials. Four bismuth samples (0.6, 1.3, 2.5, and 5.1 mg/mL) were prepared using Pepto-Bismol, alongside three iodine rods (1, 2, and 5 mg/mL), inserted into multi-energy CT phantoms with three different sizes, and scanned on a PCCT system at three tube potentials (120, 140, and Sn140 kV). A generic image-based three-material decomposition method generated iodine and bismuth maps, with mean mass concentrations and noise levels measured. The root-mean-square errors for iodine and bismuth determined the optimal tube potential. The tube potential of 140 kV demonstrated optimal quantification performance when both iodine and bismuth were considered. Distinct differentiation of iodine rods with all three concentrations and bismuth samples with mass concentrations ≥ 1.3 mg/mL was observed across all phantom sizes at the optimal kV setting.