Noninvasive differentiation of uric acid versus non-uric acid kidney stones using dual-energy CT
Noninvasive differentiation of uric acid versus non-uric acid kidney stones using dual-energy CT
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DOI：
10.1016/j.acra.2007.09.016
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发表时间：
2007-12-01
影响因子：
4.8
通讯作者：
McCollough, Cynthia H.
中科院分区：
文献类型：
--
作者：
Primak, Andrew N.;Fletcher, Joel G.;McCollough, Cynthia H.
基本原理和目标。确定商业实施产品中双能计算机断层扫描 (DECT) 区分尿酸 (UA) 结石与其他（非 UA）肾结石的准确性和灵敏度。材料和方法。将 40 颗含有尿酸 (n = 16)、羟基磷灰石 (n = 8)、草酸钙 (n = 8) 和胱氨酸 (n = 8) 的人类肾结石插入四个猪肾（每个 10 个）中，并放置在尸体脊柱前的 32 厘米水箱内。使用临床协议和自动曝光控制在双源 64 层计算机断层扫描 (CT) 系统上获得螺旋双能量扫描。在两种不同的准直（0.6 毫米和 1.2 毫米）和三种体模尺寸（中号、大号和超大号）内进行扫描，总共产生了六个图像数据集。使用 CT 系统上提供的双能软件工具对这些数据集进行分析，以确保准确性（正确分类为 UA 或非 UA 的结石数量）和灵敏度（对于 UA 结石）。结石特征与显微 CT 结果相关。对于中型和大型体模尺寸，DECT 技术显示出 100% 的准确度 (40/40)，无论准直如何。对于超大模型尺寸和 0.6 毫米准直（导致噪声最大的数据集），无法对三块（两块胱氨酸和一块小 UA）结石进行分类（准确度为 93%，灵敏度为 94%）。对于超大体模尺寸和1.2毫米准直，双能工具未能识别两个小UA结石（准确度95％，灵敏度88％）。结论。在拟人体模模型中，双能CT可以准确区分尿酸结石和其他结石类型。
Rationale and Objectives. To determine the accuracy and sensitivity for dual-energy computed tomography (DECT) discrimination of uric acid (UA) stones from other (non-UA) renal stones in a commercially implemented product.Materials and Methods. Forty human renal stones comprising uric acid (n = 16), hydroxyapatite (n = 8), calcium oxalate (n = 8), and cystine (n = 8) were inserted in four porcine kidneys (10 each) and placed inside a 32-cm water tank anterior to a cadaver spine. Spiral dual-energy scans were obtained on a dual-source, 64-slice computed tomography (CT) system using a clinical protocol and automatic exposure control. Scanning was performed at two different collimations (0.6 mm and 1.2 mm) and within three phantom sizes (medium, large, and extra large) resulting in a total of six image datasets. These datasets were analyzed using the dual-energy software tool available on the CT system for both accuracy (number of stones correctly classified as either UA or non-UA) and sensitivity (for UA stones). Stone characterization was correlated with micro-CT.Results. For the medium and large phantom sizes, the DECT technique demonstrated 100% accuracy (40/40), regardless of collimation. For the extra large phantom size and the 0.6-mm collimation (resulting in the noisiest dataset), three (two cystine and one small UA) stones could not be classified (93% accuracy and 94% sensitivity). For the extra large phantom size and the 1.2-mm collimation, the dual-energy tool failed to identify two small UA stones (95% accuracy and 88% sensitivity).Conclusions. In an anthropomorphic phantom model, dual-energy CT can accurately discriminate uric acid stones from other stone types.