Al-Murshedi Sadeq, Hogg Peter, England Andrew
1 School of Health Sciences, University of Salford , Salford , United Kingdom.
Br J Radiol. 2018 Sep;91(1089):20180317. doi: 10.1259/bjr.20180317. Epub 2018 Jul 5.
To determine if a relationship exists between low contrast detail (LCD) detectability using the CDRAD 2.0 phantom, visual measures of image quality (IQ) and simulated lesion visibility (LV) when performing digital chest radiography (CXR).
Using a range of acquisition parameters, a CDRAD 2.0 phantom was used to acquire a set of images with different levels of image quality. LCD detectability using the CDRAD 2.0 phantom, represented by an image quality figure inverse (IQF) metric, was determined using the phantom analyser software. A Lungman chest phantom was loaded with two simulated lesions, of different sizes/placed in different locations, and was imaged using the same acquisition factors as the CDRAD 2.0 phantom. A relative visual grading analysis (VGA) was used by seven observers for IQ and LV evaluation of the Lungman images. Correlations between IQF, IQ and LV were investigated.
Pearson's correlation demonstrated a strong positive correlation (r = 0.91; p < 0.001) between the IQ and the IQF. Spearman's correlation showed a good positive correlation (r = 0.79; p < 0.001) and (r = 0.68; p < 0.001) between the IQF and the LV for the first lesion (left upper lobe) and the second lesion (right middle lobe), respectively.
From results presented in this study, the automated evaluation of LCD detectability using CDRAD 2.0 phantom is likely to be a suitable option for IQ and LV evaluation in digital CXR optimisation studies. Advances in knowledge: This research establishes the potential of the CDRAD 2.0 phantom in digital CXR optimisation studies.
确定在进行数字化胸部X线摄影(CXR)时,使用CDRAD 2.0体模的低对比度细节(LCD)可探测性、图像质量(IQ)的视觉测量指标与模拟病变可见性(LV)之间是否存在关联。
使用一系列采集参数,通过CDRAD 2.0体模获取一组具有不同图像质量水平的图像。使用体模分析软件,以图像质量指数倒数(IQF)指标表示,确定使用CDRAD 2.0体模的LCD可探测性。在Lungman胸部体模中放置两个不同大小/位于不同位置的模拟病变,并使用与CDRAD 2.0体模相同的采集参数进行成像。七名观察者采用相对视觉分级分析(VGA)对Lungman图像的IQ和LV进行评估。研究IQF、IQ和LV之间的相关性。
Pearson相关性分析显示IQ与IQF之间存在强正相关(r = 0.91;p < 0.001)。Spearman相关性分析表明,对于第一个病变(左上叶)和第二个病变(右中叶),IQF与LV之间分别存在良好的正相关(r = 0.79;p < 0.001)和(r = 0.68;p < 0.001)。
根据本研究结果,在数字化CXR优化研究中,使用CDRAD 2.0体模对LCD可探测性进行自动评估可能是评估IQ和LV的合适选择。知识进展:本研究确立了CDRAD 2.0体模在数字化CXR优化研究中的潜力。