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Collimator optimization in myocardial perfusion SPECT using the ideal observer and realistic background variability for lesion detection and joint detection and localization tasks

机译:使用理想的观察者和实际背景可变性在心肌灌注SPECT中进行准直器优化用于病变检测以及关节检测和定位任务

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摘要

In SPECT imaging, collimators are a major factor limiting image quality and largely determine the noise and resolution of SPECT images. In this paper, we seek the collimator with the optimal tradeoff between image noise and resolution with respect to performance on two tasks related to myocardial perfusion SPECT: perfusion defect detection and joint detection and localization. We used the Ideal Observer (IO) operating on realistic background-known-statistically (BKS) and signal-known-exactly (SKE) data. The areas under the receiver operating characteristic (ROC) and localization ROC (LROC) curves (AUCd, AUCd+l), respectively, were used as the figures of merit for both tasks. We used a previously developed population of 54 phantoms based on the eXtended Cardiac Torso Phantom (XCAT) that included variations in gender, body size, heart size and subcutaneous adipose tissue level. For each phantom, organ uptakes were varied randomly based on distributions observed in patient data. We simulated perfusion defects at six different locations with extents and severities of 10% and 25%, respectively, which represented challenging but clinically relevant defects. The extent and severity are, respectively, the perfusion defect's fraction of the myocardial volume and reduction of uptake relative to the normal myocardium. Projection data were generated using an analytical projector that modeled attenuation, scatter, and collimator-detector response effects, a 9% energy resolution at 140 keV, and a 4 mm full-width at half maximum (FWHM) intrinsic spatial resolution. We investigated a family of eight parallel-hole collimators that spanned a large range of sensitivity-resolution tradeoffs. For each collimator and defect location, the IO test statistics were computed using a Markov Chain Monte Carlo (MCMC) method for an ensemble of 540 pairs of defect-present and -absent images that included the aforementioned anatomical and uptake variability. Sets of test statistics were computed for both tasks and analyzed using ROC and LROC analysis methodologies. The results of this study suggest that collimators with somewhat poorer resolution and higher sensitivity than those of a typical low-energy high-resolution (LEHR) collimator were optimal for both defect detection and joint detection and localization tasks in myocardial perfusion SPECT for the range of defect sizes investigated. This study also indicates that optimizing instrumentation for a detection task may provide near-optimal performance on the more challenging detection-localization task.
机译:在SPECT成像中,准直仪是限制图像质量的主要因素,并且在很大程度上决定了SPECT图像的噪声和分辨率。在本文中,我们寻求在图像噪声与分辨率之间就心肌灌注SPECT的两项相关任务的性能进行最佳权衡的准直仪:灌注缺陷检测以及关节检测和定位。我们使用理想观察者(IO)对实际的背景已知统计(BKS)和信号已知精确(SKE)数据进行操作。接收器工作特性(ROC)和定位ROC(LROC)曲线(AUCd,AUCd + 1)下的面积分别用作这两项任务的优值。我们基于扩展的心脏躯干体模(XCAT),使用了先前开发的54个幻像种群,其中包括性别,体重,心脏大小和皮下脂肪组织水平的变化。对于每个体模,根据患者数据中观察到的分布,器官摄取随机变化。我们模拟了六个不同位置的灌注缺陷,其程度和严重性分别为10%和25%,这代表了具有挑战性但与临床相关的缺陷。程度和严重程度分别是灌注缺陷占心肌体积的比例和相对于正常心肌的摄取减少。投影数据是使用分析投影仪生成的,该投影仪对衰减,散射和准直仪-检测器的响应效果,140 keV时的9%能量分辨率和4mm的半峰全宽(FWHM)固有空间分辨率进行建模。我们研究了一个由八个平行孔准直仪组成的系列,这些准直仪涵盖了各种灵敏度-分辨率折衷方案。对于每个准直仪和缺陷位置,使用马尔可夫链蒙特卡洛(MCMC)方法计算540对缺陷存在和缺失图像的集合(包括上述解剖结构和摄取变化)的IO测试统计量。为这两个任务计算了测试统计数据集,并使用ROC和LROC分析方法进行了分析。这项研究的结果表明,相比于典型的低能量高分辨率(LEHR)准直器,分辨率和灵敏度稍差的准直器对于心肌灌注SPECT的范围内的缺陷检测以及关节检测和定位任务都是最佳的。调查缺陷尺寸。这项研究还表明,针对检测任务优化仪器可能会为更具挑战性的检测定位任务提供接近最佳的性能。

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