Herts Brian R, Schreiner Andrew, Dong Frank, Primak Andrew, Bullen Jennifer, Karim Wadih, Nachand Douglas, Hunter Sara, Baker Mark E
Cleveland Clinic, Imaging Institute - Desk L10, Cleveland, OH, USA.
Department of Medical Physics - Desk AC-211, Cleveland Clinic, Imaging Institute, Beachwood, OH, USA.
J Appl Clin Med Phys. 2021 Feb;22(2):138-144. doi: 10.1002/acm2.13149. Epub 2020 Dec 28.
The purpose of this study was to assess the effect of obesity and iterative reconstruction on the ability to reduce exposure by studying the accuracy for detection of low-contrast low-attenuation (LCLA) liver lesions on computed tomography (CT) using a phantom model.
A phantom with four unique LCLA liver lesions (5- to 15-mm spheres, -24 to -6 HU relative to 90-HU background) was scanned without ("thin" phantom) and with ("obese" phantom) a 5-cm thick fat-attenuation ring at 150 mAs (thin phantom) and 450 mAs (obese phantom) standard exposures and at 33% and 67% exposure reductions. Images were reconstructed using standard filtered back projection (FBP) and with iterative reconstruction (Adaptive Model-Based Iterative Reconstruction strength 3, ADMIRE). A noninferiority analysis of lesion detection was performed.
Mean area under the curve (AUC) values for lesion detection were significantly higher for the thin phantom than for the obese phantom regardless of exposure level (P < 0.05) for both FBP and ADMIRE. At 33% exposure reduction, AUC was noninferior for both FBP and ADMIRE strength 3 (P < 0.0001). At 67% exposure reduction, AUC remained noninferior for the thin phantom (P < 0.0035), but was no longer noninferior for the obese phantom (P ≥ 0.7353). There were no statistically significant differences in AUC between FBP and ADMIRE at any exposure level for either phantom.
Accuracy for lesion detection was not only significantly lower in the obese phantom at all relative exposures, but detection accuracy decreased sooner while reducing the exposure in the obese phantom. There was no significant difference in lesion detection between FBP and ADMIRE at equivalent exposure levels for either phantom.
本研究的目的是通过使用体模模型研究计算机断层扫描（CT）上低对比度低衰减（LCLA）肝脏病变的检测准确性，来评估肥胖和迭代重建对降低辐射剂量能力的影响。
使用一个带有四个独特的LCLA肝脏病变（5至15毫米球体，相对于90 HU背景为-24至-6 HU）的体模，在150 mAs（薄体模）和450 mAs（肥胖体模）的标准辐射剂量下，以及在33%和67%的辐射剂量降低情况下，分别在没有（“薄”体模）和有（“肥胖”体模）一个5厘米厚的脂肪衰减环的情况下进行扫描。图像使用标准滤波反投影（FBP）和迭代重建（基于自适应模型的迭代重建强度3，ADMIRE）进行重建。对病变检测进行非劣效性分析。
无论辐射剂量水平如何，对于FBP和ADMIRE，薄体模的病变检测平均曲线下面积（AUC）值均显著高于肥胖体模（P < 0.05）。在33%的辐射剂量降低时，FBP和ADMIRE强度3的AUC均为非劣效（P < 0.0001）。在67%的辐射剂量降低时，薄体模的AUC仍为非劣效（P < 0.0035），但肥胖体模的AUC不再为非劣效（P≥0.7353）。对于任何一个体模，在任何辐射剂量水平下，FBP和ADMIRE之间的AUC均无统计学显著差异。
在所有相对辐射剂量下，肥胖体模中的病变检测准确性不仅显著更低，而且在降低肥胖体模的辐射剂量时，检测准确性更快下降。对于任何一个体模，在等效辐射剂量水平下，FBP和ADMIRE之间的病变检测无显著差异。
