The objective of this investigation was to determine the effectiveness of three motion reducing strategies in diminishing the degrading impact of respiratory motion on the detection of small solitary pulmonary nodules (SPNs) in single-photon emission computed tomographic (SPECT) imaging in comparison to a standard clinical acquisition and the ideal case of imaging in the absence of respiratory motion. To do this nonuniform rational B-spline cardiac-torso (NCAT) phantoms based on human-volunteer CT studies were generated spanning the respiratory cycle for a normal background distribution of Tc-99 m NeoTect. Similarly, spherical phantoms of 1.0-cm diameter were generated to model small SPN for each of the 150 uniquely located sites within the lungs whose respiratory motion was based on the motion of normal structures in the volunteer CT studies. The SIMIND Monte Carlo program was used to produce SPECT projection data from these. Normal and single-lesion containing SPECT projection sets with a clinically realistic Poisson noise level were created for the cases of 1) the end-expiration (EE) frame with all counts, 2) respiration-averaged motion with all counts, 3) one fourth of the 32 frames centered around EE (Quarter Binning), 4) one half of the 32 frames centered around EE (Half Binning), and 5) eight temporally binned frames spanning the respiratory cycle. Each of the sets of combined projection data were reconstructed with RBI-EM with system spatial-resolution compensation (RC). Based on the known motion for each of the 150 different lesions, the reconstructed volumes of respiratory bins were shifted so as to superimpose the locations of the SPN onto that in the first bin (Reconstruct and Shift). Five human observers performed localization receiver operating characteristics (LROC) studies of SPN detection. The observer results were analyzed for statistical significance differences in SPN detection accuracy among the three correction strategies, the standard acquisition, and the ideal case of the absence of respiratory motion. Our human-observer LROC determined that Quarter Binning and Half Binning strategies resulted in SPN detection accuracy statistically significantly below ( ) that of standard clinical acquisition, whereas the Reconstruct and Shift strategy resulted in a detection accuracy not statistically significantly different from that of the ideal case. This investigation demonstrates that tumor detection based on acquisitions associated with less than all the counts which could potentially be employed may result in poorer detection despite limiting the motion of the lesion. The Reconstruct and Shift method results in tumor detection that is equivalent to ideal motion correction.

中文翻译：

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减少呼吸运动对 SPECT 中孤立性肺结节检测影响的三种策略的 LROC 调查

本研究的目的是确定三种运动减少策略在减少呼吸运动对单光子发射计算机断层扫描 (SPECT) 成像中小孤立性肺结节 (SPN) 检测的影响方面的有效性，与标准相比临床采集和在没有呼吸运动的情况下成像的理想情况。为了做到这一点，基于人类志愿者 CT 研究的非均匀理性 B 样条心脏躯干 (NCAT) 体模被生成，跨越呼吸周期，用于 Tc-99 m NeoTect 的正常背景分布。类似地，生成了直径为 1.0 厘米的球形体模，以模拟肺内 150 个独特定位部位中的每一个的小 SPN，这些部位的呼吸运动基于志愿者 CT 研究中正常结构的运动。SIMIND Monte Carlo 程序用于从这些中生成 SPECT 投影数据。为以下情况创建了包含具有临床真实泊松噪声水平的 SPECT 投影集的正常和单病灶：1) 呼气末 (EE) 帧，所有计数，2) 呼吸平均运动，所有计数，3) 四分之一以 EE 为中心的 32 个帧中（四分之一分箱），4）以 EE 为中心的 32 帧中的一半（半分箱），以及 5）跨越呼吸周期的八个时间分箱帧。每组组合投影数据均使用具有系统空间分辨率补偿 (RC) 的 RBI-EM 进行重建。根据 150 个不同病变中每一个的已知运动，呼吸箱的重建体积被移位，以便将 SPN 的位置叠加到第一个箱中的位置上（重建和移位）。五名人类观察者对 SPN 检测进行了定位接收器操作特性 (LROC) 研究。观察者结果分析了三种校正策略、标准采集和没有呼吸运动的理想情况之间 SPN 检测精度的统计显着差异。我们的人类观察者 LROC 确定 Quarter Binning 和 Half Binning 策略导致 SPN 检测精度在统计上显着低于标准临床采集的 ( )，而重建和转移策略导致检测精度与理想情况下的检测精度没有统计学显着差异. 该调查表明，尽管限制了病灶的运动，但基于与少于所有可能使用的计数相关的采集的肿瘤检测可能会导致较差的检测。Reconstruct and Shift 方法导致相当于理想运动校正的肿瘤检测。