Norberg Pernilla, Olsson Anna, Alm Carlsson Gudrun, Sandborg Michael, Gustafsson Agnetha
Medical Radiation Physics, Department of Medical and Health Sciences, Linköping University, Linköping, 581 83 Sweden ; Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, 581 83 Sweden.
Medical Radiation Physics, Department of Medical and Health Sciences, Linköping University, Linköping, 581 83 Sweden ; Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, 581 83 Sweden ; Clinical Physiology, Department of Medical and Health Sciences, Linköping University, Linköping, 581 83 Sweden.
EJNMMI Res. 2015 Mar 22;5:16. doi: 10.1186/s13550-015-0086-2. eCollection 2015.
The amount of inhomogeneities in a (99m)Tc Technegas single-photon emission computed tomography (SPECT) lung image, caused by reduced ventilation in lung regions affected by chronic obstructive pulmonary disease (COPD), is correlated to disease advancement. A quantitative analysis method, the CVT method, measuring these inhomogeneities was proposed in earlier work. To detect mild COPD, which is a difficult task, optimised parameter values are needed.
In this work, the CVT method was optimised with respect to the parameter values of acquisition, reconstruction and analysis. The ordered subset expectation maximisation (OSEM) algorithm was used for reconstructing the lung SPECT images. As a first step towards clinical application of the CVT method in detecting mild COPD, this study was based on simulated SPECT images of an advanced anthropomorphic lung software phantom including respiratory and cardiac motion, where the mild COPD lung had an overall ventilation reduction of 5%.
The best separation between healthy and mild COPD lung images as determined using the CVT measure of ventilation inhomogeneity and 125 MBq (99m)Tc was obtained using a low-energy high-resolution collimator (LEHR) and a power 6 Butterworth post-filter with a cutoff frequency of 0.6 to 0.7 cm(-1). Sixty-four reconstruction updates and a small kernel size should be used when the whole lung is analysed, and for the reduced lung a greater number of updates and a larger kernel size are needed.
A LEHR collimator and 125 (99m)Tc MBq together with an optimal combination of cutoff frequency, number of updates and kernel size, gave the best result. Suboptimal selections of either cutoff frequency, number of updates and kernel size will reduce the imaging system's ability to detect mild COPD in the lung phantom.
在慢性阻塞性肺疾病（COPD）影响的肺区域，通气减少导致（99m）锝气体单光子发射计算机断层扫描（SPECT）肺图像出现不均匀性，这种不均匀性的程度与疾病进展相关。早期研究提出了一种测量这些不均匀性的定量分析方法，即CVT方法。为了检测轻度COPD（这是一项艰巨的任务），需要优化参数值。
在这项研究中，针对采集、重建和分析的参数值对CVT方法进行了优化。采用有序子集期望最大化（OSEM）算法重建肺SPECT图像。作为CVT方法在检测轻度COPD临床应用的第一步，本研究基于包含呼吸和心脏运动的高级拟人化肺软件模型的模拟SPECT图像，其中轻度COPD肺的总体通气减少了5%。
使用低能高分辨率准直器（LEHR）和截止频率为0.6至0.7 cm⁻¹的6次幂巴特沃斯后置滤波器，通过CVT通气不均匀性测量和125 MBq（99m）锝，可实现健康肺与轻度COPD肺图像之间的最佳区分。分析全肺时应使用64次重建更新和较小的核大小，而对于缩小的肺，则需要更多的更新次数和更大的核大小。
LEHR准直器和125 MBq（99m）锝，再加上截止频率、更新次数和核大小的最佳组合，可得到最佳结果。截止频率、更新次数和核大小的次优选择会降低成像系统检测肺模型中轻度COPD的能力。
