Felice Nicholas, Wildman-Tobriner Benjamin, Segars William Paul, Bashir Mustafa R, Marin Daniele, Samei Ehsan, Abadi Ehsan
Duke University, Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Durham, North Carolina, United States.
Duke University, Medical Physics Graduate Program, Durham, North Carolina, United States.
J Med Imaging (Bellingham). 2024 Sep;11(5):053502. doi: 10.1117/1.JMI.11.5.053502. Epub 2024 Oct 17.
Photon-counting computed tomography (PCCT) has the potential to provide superior image quality to energy-integrating CT (EICT). We objectively compare PCCT to EICT for liver lesion detection.
Fifty anthropomorphic, computational phantoms with inserted liver lesions were generated. Contrast-enhanced scans of each phantom were simulated at the portal venous phase. The acquisitions were done using DukeSim, a validated CT simulation platform. Scans were simulated at two dose levels ( 1.5 to 6.0 mGy) modeling PCCT (NAEOTOM Alpha, Siemens, Erlangen, Germany) and EICT (SOMATOM Flash, Siemens). Images were reconstructed with varying levels of kernel sharpness (soft, medium, sharp). To provide a quantitative estimate of image quality, the modulation transfer function (MTF), frequency at 50% of the MTF ( ), noise magnitude, contrast-to-noise ratio (CNR, per lesion), and detectability index ( , per lesion) were measured.
Across all studied conditions, the best detection performance, measured by , was for PCCT images with the highest dose level and softest kernel. With soft kernel reconstruction, PCCT demonstrated improved lesion CNR and compared with EICT, with a mean increase in CNR of 35.0% ( ) and 21% ( ) and a mean increase in of 41.0% ( ) and 23.3% ( ) for the 1.5 and 6.0 mGy acquisitions, respectively. The improvements were greatest for larger phantoms, low-contrast lesions, and low-dose scans.
PCCT demonstrated objective improvement in liver lesion detection and image quality metrics compared with EICT. These advances may lead to earlier and more accurate liver lesion detection, thus improving patient care.
光子计数计算机断层扫描（PCCT）有可能提供比能量积分CT（EICT）更高的图像质量。我们客观地比较了PCCT和EICT在肝脏病变检测方面的性能。
生成了50个插入肝脏病变的人体模拟计算体模。在门静脉期对每个体模进行了对比增强扫描。使用经过验证的CT模拟平台DukeSim进行采集。在两个剂量水平（1.5至6.0毫戈瑞）下模拟扫描，分别模拟PCCT（NAEOTOM Alpha，西门子，德国埃尔朗根）和EICT（SOMATOM Flash，西门子）。使用不同程度的核锐度（软、中、锐）重建图像。为了对图像质量进行定量评估，测量了调制传递函数（MTF）、MTF 50%时的频率（ ）、噪声幅度、对比噪声比（CNR，每个病变）和可检测性指数（ ，每个病变）。
在所有研究条件下，以 衡量的最佳检测性能出现在最高剂量水平和最软核的PCCT图像上。与EICT相比，采用软核重建时，PCCT的病变CNR和 有所改善，在1.5和6.0毫戈瑞采集时，CNR平均分别增加35.0%（ ）和21%（ ）， 平均分别增加41.0%（ ）和23.3%（ ）。对于更大的体模、低对比度病变和低剂量扫描，改善最为明显。
与EICT相比，PCCT在肝脏病变检测和图像质量指标方面有客观的改善。这些进展可能会导致更早、更准确地检测肝脏病变，从而改善患者护理。
