Department of Urology, University Hospital Cologne, Cologne, Germany.
Department of Urology, University Stone Centre, University of Bonn, Bonn, Germany.
Invest Radiol. 2018 Aug;53(8):457-462. doi: 10.1097/RLI.0000000000000468.
The aim of this study was to investigate the feasibility of kidney stone composition analysis using spectral detector computed tomography scanner (SDCT) with normal- and low-dose imaging protocols.
A total of 154 stones harvested from nephrolithotripsy or nephrolithotomy with a known monocrystalline composition as determined by infrared spectroscopy were examined in a nonanthropomorphic phantom on an SDCT (IQon, Philips, Best, the Netherlands). Imaging was performed with 120 kVp and (a) 40 mAs and (b) 200 mAs, resulting in a computed tomography dose index (CTDIvol) of 2 and 10 mGy, respectively. Besides conventional CT images (CIs), SDCT enables reconstruction of virtual monoenergetic images (40-200 keV). Spectral coefficient images were calculated by performing a voxel-by-voxel combination of 40 and 200 keV images (Matlab R2017b, Mathworks Inc). All stones were semiautomatically 3D-segmented on CI using a threshold-based algorithm implemented in an offline DICOM viewer. Statistical assessment was performed using Steel-Dwass method to adjust for multiple comparisons.
Ca-phosphate (n = 22), Ca-oxalate (n = 82), cysteine (n = 20), struvite (n = 3), uric acid (n = 18), and xanthine stones (n = 9) were included in the analysis. Stone diameter ranged from 3.0 to 13.5 mm. On CI, attenuation differed significantly between calcific and noncalcific stones only (P ≤ 0.05), the spectral coefficient differed significantly between (//): Ca-oxalate//Ca-phosphate//cystine//struvite//uric acid//xanthine in 10 mGy protocol (all P ≤ 0.05). The same results were found for the 2 mGy-protocol, except that differentiation of Ca-oxalate and Ca-phosphate as well as uric acid and xanthine was not possible (P ≥ 0.05).
Spectral detector CT allows for differentiation of kidney stones using semi-automatic segmentation and advanced image post-processing, even in low-dose imaging protocols.
本研究旨在探讨使用光谱探测器 CT 扫描仪(SDCT)进行正常和低剂量成像方案的肾结石成分分析的可行性。
在一个非人体模型的 SDCT(IQon,飞利浦,Best,荷兰)体模上检查了 154 个从经皮肾镜碎石术或肾切开取石术获得的结石,这些结石的单晶成分通过红外光谱确定。使用 120 kVp 和(a)40 mAs 和(b)200 mAs 进行成像,分别导致 CT 剂量指数(CTDIvol)为 2 和 10 mGy。除了常规 CT 图像(CI)之外,SDCT 还可以重建虚拟单能量图像(40-200 keV)。通过在离线 DICOM 查看器中实现的基于阈值的算法对 40 和 200 keV 图像进行逐像素组合来计算光谱系数图像(Matlab R2017b,Mathworks Inc)。使用基于阈值的算法在离线 DICOM 查看器中实现,对 CI 上的所有结石进行半自动 3D 分割。使用 Steel-Dwass 方法进行统计评估,以调整多重比较。
纳入分析的结石包括磷酸钙(n = 22)、草酸钙(n = 82)、半胱氨酸(n = 20)、鸟粪石(n = 3)、尿酸(n = 18)和黄嘌呤结石(n = 9)。结石直径范围为 3.0 至 13.5 毫米。在 CI 上,仅在钙化和非钙化结石之间的衰减存在显著差异(P ≤ 0.05),在 10 mGy 方案中,光谱系数在(//)之间存在显著差异:草酸钙//磷酸钙//半胱氨酸//鸟粪石//尿酸//黄嘌呤(所有 P ≤ 0.05)。在 2 mGy 方案中也得到了相同的结果,只是无法区分草酸钙和磷酸钙以及尿酸和黄嘌呤(P ≥ 0.05)。
即使在低剂量成像方案中,光谱探测器 CT 也允许使用半自动分割和高级图像后处理来区分肾结石。