Department of Radiology, UT Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX, 75390-8827, USA.
UT Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX, 75390-8827, USA.
Abdom Radiol (NY). 2018 Nov;43(11):3075-3081. doi: 10.1007/s00261-018-1589-x.
To assess the non-inferiority of dual-layer spectral detector CT (SDCT) compared to dual-source dual-energy CT (dsDECT) in discriminating uric acid (UA) from non-UA stones.
Fifty-seven extracted urinary calculi were placed in a cylindrical phantom in a water bath and scanned on a SDCT scanner (IQon, Philips Healthcare) and second- and third-generation dsDECT scanners (Somatom Flash and Force, Siemens Healthcare) under matched scan parameters. For SDCT data, conventional images and virtual monoenergetic reconstructions were created. A customized 3D growing region segmentation tool was used to segment each stone on a pixel-by-pixel basis for statistical analysis. Median virtual monoenergetic ratios (VMRs) of 40/200, 62/92, and 62/100 for each stone were recorded. For dsDECT data, dual-energy ratio (DER) for each stone was recorded from vendor-specific postprocessing software (Syngo Via) using the Kidney Stones Application. The clinical reference standard of X-ray diffraction analysis was used to assess non-inferiority. Area under the receiver-operating characteristic curve (AUC) was used to assess diagnostic performance of detecting UA stones.
Six pure UA, 47 pure calcium-based, 1 pure cystine, and 3 mixed struvite stones were scanned. All pure UA stones were correctly separated from non-UA stones using SDCT and dsDECT (AUC = 1). For UA stones, median VMR was 0.95-0.99 and DER 1.00-1.02. For non-UA stones, median VMR was 1.4-4.1 and DER 1.39-1.69.
SDCT spectral reconstructions demonstrate similar performance to those of dsDECT in discriminating UA from non-UA stones in a phantom model.
评估双层光谱探测器 CT（SDCT）与双源双能 CT（dsDECT）在区分尿酸（UA）与非 UA 结石方面的非劣效性。
将 57 个提取的尿结石放置在圆柱形水浴体模中，在 SDCT 扫描仪（IQon，飞利浦医疗保健）和第二代和第三代 dsDECT 扫描仪（Somatom Flash 和 Force，西门子医疗保健）上以匹配的扫描参数进行扫描。对于 SDCT 数据，创建常规图像和虚拟单能量重建图像。使用定制的 3D 生长区域分割工具对每个结石进行逐像素分割，用于统计分析。记录每个结石的中位数虚拟单能量比值（VMR）为 40/200、62/92 和 62/100。对于 dsDECT 数据，从供应商特定的后处理软件（Syngo Via）使用 Kidney Stones Application 记录每个结石的双能量比值（DER）。使用 X 射线衍射分析的临床参考标准来评估非劣效性。接收者操作特征曲线下的面积（AUC）用于评估检测 UA 结石的诊断性能。
共扫描了 6 个纯 UA、47 个纯钙基、1 个纯胱氨酸和 3 个混合鸟粪石结石。使用 SDCT 和 dsDECT 可正确区分所有纯 UA 结石与非 UA 结石（AUC=1）。对于 UA 结石，中位数 VMR 为 0.95-0.99，DER 为 1.00-1.02。对于非 UA 结石，中位数 VMR 为 1.4-4.1，DER 为 1.39-1.69。
在结石模型中，SDCT 光谱重建在区分 UA 与非 UA 结石方面表现出与 dsDECT 相似的性能。
