Coronary atherosclerotic plaque characterization with silicon-based photon-counting computed tomography (CT): A...

Recent photon-counting computed tomography (PCCT) development brings great opportunities for plaque characterization with much-improved spatial resolution and spectral imaging capability. While existing coronary plaque PCCT imaging results are based on CZT- or CdTe-materials detectors, deep-silicon photon-counting detectors offer unique performance characteristics and promise distinct imaging capabilities.

This study aims to numerically investigate the feasibility of characterizing plaques with a deep-silicon PCCT scanner and to demonstrate its potential performance advantages over traditional CT scanners using energy-integrating detectors (EID).

We conducted a systematic simulation study of a deep-silicon PCCT scanner using a newly developed digital plaque phantom with clinically relevant geometrical and chemical properties. Through qualitative and quantitative evaluations, this study investigates the effects of spatial resolution, noise, and motion artifacts on plaque imaging.

Noise-free simulations indicated that PCCT imaging could delineate the boundary of necrotic cores with a much finer resolution than EID-CT imaging, achieving a structural similarity index metric (SSIM) score of 0.970 and reducing the root mean squared error (RMSE) by two-thirds. Measuring necrotic core area errors were reduced from 91.5% to 24%, and fibrous cap thickness errors were reduced from 349.8% to 33.3%. In the presence of noise, the optimal reconstruction was achieved using 0.25 mm voxels and a soft reconstruction kernel, yielding the highest contrast-to-noise ratio (CNR) of 3.48 for necrotic core detection and the best image quality metrics among all choices. However, the ultrahigh resolution of PCCT increased sensitivity to motion artifacts, which could be mitigated by keeping residual motion amplitude below 0.4 mm.

The findings suggest that deep-silicon PCCT scanner can offer sufficient spatial resolution and tissue contrast for effective plaque characterization, potentially improving diagnostic accuracy in cardiovascular imaging, provided image noise and motion blur can be mitigated using advanced algorithms. This simulation study involves several simplifications, which may result in some idealized outcomes that do not directly translate to clinical practice. Further validation studies with physical scans are necessary and will be considered for future work.