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Photon-counting computed tomography (PCCT) enables spectral imaging by counting individual X-ray photons with multiple energy thresholds. Most current PCCT systems use semiconductor detectors (CdTe/CZT), which provide high energy resolution but remain costly and are affected by spectral degradation such as charge sharing. As a cost-effective alternative, we have been developing scintillator-based PCCT using a fast scintillator coupled to a silicon photomultiplier (SiPM). Our previous 1 × 64-channel PCCT system with a dedicated application-specific integrated circuit (ASIC) demonstrated spectral CT imaging, including preclinical imaging, but 3D acquisition required substantial scan time because the one-dimensional detector geometry required translate–rotate acquisition (first-generation CT geometry). To enable faster mouse imaging and future dynamic imaging, we developed a large-area 2D scintillator-based PCCT system consisting of a 16 × 64 (1024-channel) SiPM/scintillator array and a newly designed high-performance ASIC. In this paper, we report the fundamental performance evaluation of the newly developed system as a prerequisite for in vivo high-speed and dynamic imaging. The ASIC integrates six energy thresholds, an on-chip digital calibration function, and a CR differentiator with pole-zero cancellation (PZC) to improve spectroscopic performance and count-rate capability. Using on-chip calibration, we achieved energy alignment within ± 0.5 keV across 6144 counters and obtained an energy resolution of 33.6 ± 2.0 % full width at half maximum (FWHM) at 60 keV. The count-rate capability reached 12 Mcps/ch for 1 × 1 mm 2 pixels, which is more than twice that of our previous 64-channel system. We also demonstrated rotation-only multicolor 3D CT imaging with the large-area detector and successfully separated iodine, gadolinium, and gold nanoparticles (AuNP) using six-threshold data. These results demonstrate the feasibility of a scalable scintillator-based PCCT platform for fast preclinical mouse spectral CT imaging and provide the technical basis for future dynamic imaging studies.
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Ro et al. (2026) studied this question.
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