Department of Radiology and Biomedical Imaging, University of California, San Francisco, 505 Parnassus Avenue, 3rd Floor, M372, San Francisco, CA, 94143, USA.
Department of Radiology, Zuckerberg San Francisco General Hospital, 1001 Potrero Ave, SFGH 5 Room 1x56, Box 0628, San Francisco, CA, 94110, USA.
Abdom Radiol (NY). 2022 Jun;47(6):2046-2056. doi: 10.1007/s00261-022-03482-9. Epub 2022 Mar 19.
Determine whether liver attenuation measured on dual-energy CT (DECT) virtual non-contrast examinations predicts the presence of fatty liver.
Single-institution retrospective review from 2016 to 2020 found patients with DECT and proton density fat fraction MRI (MRI PDFF) within 30 days. MRI PDFF was the reference standard for determining hepatic steatosis. Attenuation measurements from VNC and mixed 120 kVp-like images were compared to MRI PDFF in the right and left lobes. Performance of VNC was compared to measurement of the liver-spleen attenuation difference (LSAD).
128 patients were included (69 men, 59 women) with mean age 51.6 years (range 14-98 years). > 90% of patients received CT and MRI in the emergency department or as inpatients. Median interval between DECT and MRI PDFF was 2 days (range 0-28 days). Prevalence of fatty liver using the reference standard (MRI PDFF > 6%) was 24%. Pearson correlation coefficient between VNC and MRI- DFF was -0.64 (right) and -0.68 (left, both p < 0.0001). For LSAD, correlation was - 0.43 in both lobes (p < 0.0001). Considering MRI PDFF > 6% as diagnostic of steatosis, area under the receiver operator characteristic curve (AUC) was 0.834 and 0.872 in the right and left hepatic lobes, with an optimal threshold of 54.8 HU (right) and 52.5 HU (left), yielding sensitivity/specificity of 57%/93.9% (right) and 67.9%/90% (left). For LSAD, AUC was 0.808 (right) and 0.767 (left) with optimal sensitivity/specificity of 93.3%/57.1% (right) and 78.6%/68% (left).
Attenuation measured at VNC CT was moderately correlated with liver fat content and had > 90% specificity for diagnosis of fatty liver.
确定双能 CT（DECT）虚拟非对比检查中测量的肝脏衰减值是否可预测脂肪肝的存在。
对 2016 年至 2020 年期间的单中心回顾性研究进行分析，发现患者在 30 天内进行了 DECT 和质子密度脂肪分数 MRI（MRI PDFF）检查。MRI PDFF 为确定肝脂肪变性的参考标准。比较右叶和左叶 VNC 和混合 120kVp 样图像的衰减测量值与 MRI PDFF。比较 VNC 的性能与肝脾衰减差（LSAD）的测量值。
共纳入 128 例患者（69 名男性，59 名女性），平均年龄为 51.6 岁（范围 14-98 岁）。超过 90%的患者在急诊科或住院期间同时接受 CT 和 MRI 检查。DECT 和 MRI PDFF 之间的中位间隔时间为 2 天（范围 0-28 天）。使用参考标准（MRI PDFF>6%）检测到脂肪肝的患病率为 24%。VNC 与 MRI-PDFF 之间的 Pearson 相关系数分别为 -0.64（右叶）和 -0.68（左叶，均<0.0001）。LSAD 在两个叶的相关性均为 -0.43（均<0.0001）。将 MRI PDFF>6%视为脂肪变性的诊断标准，右叶和左叶的受试者工作特征曲线下面积（AUC）分别为 0.834 和 0.872，最佳阈值为 54.8HU（右叶）和 52.5HU（左叶），敏感性/特异性分别为 57%/93.9%（右叶）和 67.9%/90%（左叶）。对于 LSAD，AUC 分别为 0.808（右叶）和 0.767（左叶），最佳敏感性/特异性分别为 93.3%/57.1%（右叶）和 78.6%/68%（左叶）。
VNC CT 测量的衰减值与肝脂肪含量中度相关，对脂肪肝的诊断具有>90%的特异性。
