Li Qin, Gavrielides Marios A, Zeng Rongping, Myers Kyle J, Sahiner Berkman, Petrick Nicholas
Division of Imaging, Diagnostics, and Software Reliability, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD 20993, USA.
Phys Med Biol. 2015 Jan 21;60(2):671-88. doi: 10.1088/0031-9155/60/2/671. Epub 2015 Jan 2.
Measurements of lung nodule volume with multi-detector computed tomography (MDCT) have been shown to be more accurate and precise compared to conventional lower dimensional measurements. Quantifying the size of lesions is potentially more difficult when the object-to-background contrast is low as with lesions in the liver. Physical phantom and simulation studies are often utilized to analyze the bias and variance of lesion size estimates because a ground truth or reference standard can be established. In addition, it may also be useful to derive theoretical bounds as another way of characterizing lesion sizing methods. The goal of this work was to study the performance of a MDCT system for a lesion volume estimation task with object-to-background contrast less than 50 HU, and to understand the relation among performances obtained from phantom study, simulation and theoretical analysis. We performed both phantom and simulation studies, and analyzed the bias and variance of volume measurements estimated by a matched-filter-based estimator. We further corroborated results with a theoretical analysis to estimate the achievable performance bound, which was the Cramer-Rao's lower bound (CRLB) of minimum variance for the size estimates. Results showed that estimates of non-attached solid small lesion volumes with object-to-background contrast of 31-46 HU can be accurate and precise, with less than 10.8% in percent bias and 4.8% in standard deviation of percent error (SPE), in standard dose scans. These results are consistent with theoretical (CRLB), computational (simulation) and empirical phantom bounds. The difference between the bounds is rather small (for SPE less than 1.9%) indicating that the theoretical- and simulation-based performance bounds can be good surrogates for physical phantom studies.
与传统的低维测量相比，多探测器计算机断层扫描（MDCT）对肺结节体积的测量已被证明更准确、更精确。当物体与背景的对比度较低时，如肝脏中的病变，量化病变大小可能会更困难。由于可以建立一个真实值或参考标准，物理体模和模拟研究经常被用来分析病变大小估计的偏差和方差。此外，推导理论界限作为表征病变大小测量方法的另一种方式可能也很有用。这项工作的目标是研究MDCT系统在物体与背景对比度小于50 HU的病变体积估计任务中的性能，并了解从体模研究、模拟和理论分析中获得的性能之间的关系。我们进行了体模和模拟研究，并分析了基于匹配滤波器的估计器估计的体积测量的偏差和方差。我们进一步通过理论分析来证实结果，以估计可达到的性能界限，即大小估计的最小方差的克拉美-罗下界（CRLB）。结果表明，在标准剂量扫描中，对于物体与背景对比度为31-46 HU的非附着实性小病变体积的估计可以准确、精确，偏差百分比小于10.8%，百分比误差标准差（SPE）小于4.8%。这些结果与理论（CRLB）、计算（模拟）和经验体模界限一致。这些界限之间的差异相当小（对于SPE小于1.9%），表明基于理论和模拟的性能界限可以很好地替代物理体模研究。
