Abdullah Ahmed K, Kelly Judith, Thompson John D, Mercer Claire E, Aspin Rob, Hogg Peter
1 University of Diyala, Baqubah, Diyala, Iraq.
2 Directorate of Radiography, University of Salford, Greater Manchester, UK.
Br J Radiol. 2017 Jul;90(1075):20160871. doi: 10.1259/bjr.20160871. Epub 2017 Jun 16.
Motion blur is a known phenomenon in full-field digital mammography, but the impact on lesion detection is unknown. This is the first study to investigate detection performance with varying magnitudes of simulated motion blur.
7 observers (15 ± 5 years' reporting experience) evaluated 248 cases (62 containing malignant masses, 62 containing malignant microcalcifications and 124 normal cases) for 3 conditions: no blurring (0 mm) and 2 magnitudes of simulated blurring (0.7 and 1.5 mm). Abnormal cases were biopsy proven. Mathematical simulation was used to provide a pixel shift in order to simulate motion blur. A free-response observer study was conducted to compare lesion detection performance for the three conditions. The equally weighted jackknife alternative free-response receiver operating characteristic was used as the figure of merit. Test alpha was set at 0.05 to control probability of Type I error.
The equally weighted jackknife alternative free-response receiver operating characteristic analysis found a statistically significant difference in lesion detection performance for both masses [F(2,22) = 6.01, p = 0.0084] and microcalcifications [F(2,49) = 23.14, p < 0.0001]. The figures of merit reduced as the magnitude of simulated blurring increased. Statistical differences were found between some of the pairs investigated for the detection of masses (0.0 vs 0.7 and 0.0 vs 1.5 mm) and all pairs for microcalcifications (0.0 vs 0.7, 0.0 vs 1.5 and 0.7 vs 1.5 mm). No difference was detected between 0.7 and 1.5 mm for masses.
The mathematical simulation of motion blur caused a statistically significant reduction in lesion detection performance. These false-negative decisions could have implications for clinical practice. Advances in knowledge: This research demonstrates for the first time that motion blur has a negative and statistically significant impact on lesion detection performance in digital mammography.
运动模糊是全视野数字化乳腺摄影中一种已知现象，但对病变检测的影响尚不清楚。这是第一项研究不同程度模拟运动模糊下检测性能的研究。
7名观察者（报告经验为15±5年）对248例病例（62例含有恶性肿块，62例含有恶性微钙化，124例正常病例）进行3种情况的评估：无模糊（0毫米）和2种程度的模拟模糊（0.7和1.5毫米）。异常病例经活检证实。使用数学模拟来提供像素偏移以模拟运动模糊。进行了一项自由反应观察者研究，以比较三种情况下的病变检测性能。采用等权重留一法替代自由反应接收器操作特性作为评估指标。将检验α设定为0.05以控制I型错误的概率。
等权重留一法替代自由反应接收器操作特性分析发现，对于肿块[F(2,22)=6.01，p=0.0084]和微钙化[F(2,49)=23.14，p<0.0001]，病变检测性能存在统计学显著差异。随着模拟模糊程度的增加，评估指标降低。在检测肿块的一些研究对之间（0.0对0.7和0.0对1.5毫米）以及微钙化的所有对之间（0.0对0.7、0.0对1.5和0.7对1.5毫米）发现了统计学差异。对于肿块，0.7和1.5毫米之间未检测到差异。
运动模糊的数学模拟导致病变检测性能出现统计学显著下降。这些假阴性结果可能对临床实践产生影响。知识进展：本研究首次证明运动模糊对数字化乳腺摄影中的病变检测性能有负面且统计学显著的影响。
