The Monte Carlo N-Particle (MCNP) is often used to calculate the radiation dose during computed tomography (CT) scans. However, the physical calculation process of the model is complicated, the input file structure of the program is complex, and the three-dimensional (3D) display of the geometric model is not supported, so that the researchers cannot establish an accurate CT radiation system model, which affects the accuracy of the dose calculation results. Aiming at these two problems, this study designed a software that visualized CT modeling and automatically generated input files. In terms of model calculation, the theoretical basis was based on the integration of CT modeling improvement schemes of major researchers. For 3D model visualization, LabVIEW was used as the new development platform, constructive solid geometry (CSG) was used as the algorithm principle, and the introduction of editing of MCNP input files was used to visualize CT geometry modeling. Compared with a CT model established by a recent study, the root mean square error between the results simulated by this visual CT modeling software and the actual measurement was smaller. In conclusion, the proposed CT visualization modeling software can not only help researchers to obtain an accurate CT radiation system model, but also provide a new research idea for the geometric modeling visualization method of MCNP.
In recent years, photon-counting computed tomography (PCD-CT) based on photon-counting detectors (PCDs) has become increasingly utilized in clinical practice. Compared with conventional CT, PCD-CT has the potential to achieve micron-level spatial resolution, lower radiation dose, negligible electronic noise, multi-energy imaging, and material identification, etc. This advancement facilitates the promotion of ultra-low dose scans in clinical scenarios, potentially detecting minimal and hidden lesions, thus significantly improving image quality. However, the current state of the art is limited and issues such as charge sharing, pulse pileup, K-escape and count rate drift remain unresolved. These issues could lead to a decrease in image resolution and energy resolution, while an increasing in image noise and ring artifact and so on. This article systematically reviewed the physical principles of PCD-CT, and outlined the structural differences between PCDs and energy integration detectors (EIDs), and the current challenges in the development of PCD-CT. In addition, the advantages and disadvantages of three detector materials were analysed. Then, the clinical benefits of PCD-CT were presented through the clinical application of PCD-CT in the three diseases with the highest mortality rate in China (cardiovascular disease, tumour and respiratory disease). The overall aim of the article is to comprehensively assist medical professionals in understanding the technological innovations and current technical limitations of PCD-CT, while highlighting the urgent problems that PCD-CT needs to address in the coming years.