Abstract
PURPOSE: This study investigates the imaging performance of a deep silicon-based photon-counting CT (Si-PCCT) in quantifying iodine contrast through a virtual imaging trial (VIT). METHODS: We developed a VIT framework using Si-PCCT simulator and benchmarked it against a prototype using an ACR phantom for assessing spatial resolution and noise characteristics, and a geometric phantom for iodine quantification. We imaged geometrical phantoms (20 - 40 cm) with iodine concentrations ranging from 1 to 19.7 mg/ml and XCAT human models with iodine contrast at BMI of 19 to 38 kg/m(2) across different radiation dose levels (13.9, 27.8, and 41.7 mGy of CTDI(vol)). We performed material decomposition, reconstructed iodine CT images, and evaluated iodine quantification accuracy. RESULTS: The Si-PCCT simulator closely matched with the prototype, with differences within 3 % in MTF (f(50) and f(10)) and 3.7 % (f(peak)) in NNPS, and Root-Mean-Square Error of 0.12 mg/ml in iodine quantification. The mean absolute errors (MAE) between the estimated and ground-truth iodine concentration were 0.10, 0.25, and 1.80 mg/ml for 20, 30, and 40 cm phantoms, and 0.31, 0.37, and 0.70 mg/ml for XCAT human models with BMIs of 19, 28, and 38 kg/m(2), respectively. Similarly, the MAEs were 0.88, 0.45, and 0.31 mg/ml for the geometrical phantoms, and 0.66, 0.5, and 0.46 mg/ml for human models at CTDI(vol) of 13.9, 27.8, and 41.7 mGy respectively. These results demonstrate accurate iodine quantification performance, influenced by object size and radiation dose. CONCLUSION: This study shows the promising clinical utility of Si-PCCT for accurate iodine quantification under clinically relevant imaging conditions.