Li Mengzhou, Wu Mingye, Pack Jed, Wu Pengwei, Yan Pingkun, De Man Bruno, Wang Adam, Nieman Koen, Wang Ge
Biomedical Imaging Center, Center for Biotechnology and Interdisciplinary Research, Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, New York, USA.
GE HealthCare Technology & Innovation Center, Niskayuna, New York, USA.
Med Phys. 2024 Dec;51(12):8725-8741. doi: 10.1002/mp.17422. Epub 2024 Sep 25.
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.
近期光子计数计算机断层扫描(PCCT)的发展为斑块特征分析带来了巨大机遇,其空间分辨率和光谱成像能力有了显著提升。虽然现有的冠状动脉斑块PCCT成像结果是基于CZT或CdTe材料探测器,但深硅光子计数探测器具有独特的性能特点,并有望实现独特的成像能力。
本研究旨在通过数值模拟研究使用深硅PCCT扫描仪对斑块进行特征分析的可行性,并证明其相较于使用能量积分探测器(EID)的传统CT扫描仪所具有的潜在性能优势。
我们使用新开发的具有临床相关几何和化学特性的数字斑块模型,对深硅PCCT扫描仪进行了系统的模拟研究。通过定性和定量评估,本研究调查了空间分辨率、噪声和运动伪影对斑块成像的影响。
无噪声模拟表明,PCCT成像能够以比EID-CT成像精细得多 的分辨率描绘坏死核心的边界,结构相似性指数(SSIM)得分达到0.970,均方根误差(RMSE)降低了三分之二。坏死核心面积测量误差从91.5%降至24%,纤维帽厚度误差从349.8%降至33.3%。在存在噪声的情况下,使用0.25毫米体素和软重建内核可实现最佳重建,坏死核心检测的对比度噪声比(CNR)最高可达3.48,且在所有选择中图像质量指标最佳。然而,PCCT的超高分辨率增加了对运动伪影的敏感性,通过将残余运动幅度保持在0.4毫米以下可减轻这种影响。
研究结果表明,深硅PCCT扫描仪可为有效的斑块特征分析提供足够的空间分辨率和组织对比度,有望提高心血管成像的诊断准确性,前提是可使用先进算法减轻图像噪声和运动模糊。本模拟研究涉及若干简化,可能会导致一些理想化结果,无法直接转化为临床实践。有必要进行进一步的物理扫描验证研究,并将在未来工作中予以考虑。