基于虚拟非对比 CT 的肝脏脂肪变性评估：临床应用获批的光子计数 CT 的初步经验。
Assessment of hepatic steatosis based on virtual non-contrast computed tomography: Initial experiences with a photon counting scanner approved for clinical use.
机构信息
Department of Radiology, Neuroradiology and Nuclear Medicine, Johannes Wesling University Hospital, Ruhr University Bochum, Bochum, Germany.
Department of Radiology, Neuroradiology and Nuclear Medicine, Johannes Wesling University Hospital, Ruhr University Bochum, Bochum, Germany.
出版信息
Eur J Radiol. 2022 Apr;149:110185. doi: 10.1016/j.ejrad.2022.110185. Epub 2022 Jan 31.
PURPOSE
The present study evaluates the diagnostic accuracy of virtual non-contrast (VNC) images acquired with the first clinical photon counting CT scanner for the assessment of hepatic steatosis.
METHOD
140 patients were retrospectively enrolled in this study. The following CT indices were calculated according to the attenuation on VNC and true non-contrast (TNC) images: Liver attenuation CT (L), difference between liver and spleen attenuation CT (L-S) and the ratio between liver and spleen attenuation CT (L/S).
RESULTS
Considering previously reported cut-off values, the sensitivity, specificity, positive and negative predictive value (PPV, NPV) for the detection of hepatic steatosis on VNC images was 94%, 87%, 30% and 99.5% for CT (L), 52%, 99%, 81% and 96% for CT (L-S) and 67%, 98%, 74% and 94% for CT (L/S). When adjusting the cut-off values according to the present study, the sensitivity, specificity, PPV and NPV for the detection of hepatic steatosis on VNC images was 94%, 92%, 41% and 99.6% for CT (L), 96%, 90%, 46% and 99.6% for CT (L-S) and 95%, 99.6%, 42% and 99.6% for CT (L/S).
CONCLUSIONS
In conclusion, the spectral datasets acquired with the first clinical PCCT scanner enable the reconstruction of VNC images that are reliable for the image-based assessment of hepatic steatosis. By adjusting the cut-off values all tested CT indices perform well and offer an excellent sensitivity as well as specificity.
目的
本研究评估了首款临床光子计数 CT 扫描仪获得的虚拟非对比（VNC）图像在评估肝脂肪变性中的诊断准确性。
方法
本研究回顾性纳入 140 例患者。根据 VNC 和真实非对比（TNC）图像的衰减值计算以下 CT 指数：肝衰减 CT（L）、肝脾衰减差 CT（L-S）和肝脾衰减比 CT（L/S）。
结果
考虑到先前报道的截止值，VNC 图像检测肝脂肪变性的灵敏度、特异性、阳性预测值（PPV）和阴性预测值（NPV）分别为 CT（L）94%、87%、30%和 99.5%，CT（L-S）52%、99%、81%和 96%，CT（L/S）67%、98%、74%和 94%。根据本研究调整截止值后，VNC 图像检测肝脂肪变性的灵敏度、特异性、PPV 和 NPV 分别为 CT（L）94%、92%、41%和 99.6%，CT（L-S）96%、90%、46%和 99.6%，CT（L/S）95%、99.6%、42%和 99.6%。
结论
总之，首款临床 PCCT 扫描仪采集的光谱数据集能够重建 VNC 图像，这些图像可用于基于图像的肝脂肪变性评估。通过调整截止值，所有测试的 CT 指数均表现良好，具有优异的灵敏度和特异性。
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