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在乳腺钼靶筛查诊断解读中对序列上下文效应进行建模。

Modeling sequential context effects in diagnostic interpretation of screening mammograms.

作者信息

Alamudun Folami, Paulus Paige, Yoon Hong-Jun, Tourassi Georgia

机构信息

Oak Ridge National Laboratory, Computational Sciences and Engineering Division, Oak Ridge, Tennessee, United States.

Oak Ridge National Laboratory, Health Data Sciences Institute, Oak Ridge, Tennessee, United States.

出版信息

J Med Imaging (Bellingham). 2018 Jul;5(3):031408. doi: 10.1117/1.JMI.5.3.031408. Epub 2018 Mar 19.

Abstract

Prior research has shown that physicians' medical decisions can be influenced by sequential context, particularly in cases where successive stimuli exhibit similar characteristics when analyzing medical images. This type of systematic error is known to psychophysicists as sequential context effect as it indicates that judgments are influenced by features of and decisions about the preceding case in the sequence of examined cases, rather than being based solely on the peculiarities unique to the present case. We determine if radiologists experience some form of context bias, using screening mammography as the use case. To this end, we explore correlations between previous perceptual behavior and diagnostic decisions and current decisions. We hypothesize that a radiologist's visual search pattern and diagnostic decisions in previous cases are predictive of the radiologist's current diagnostic decisions. To test our hypothesis, we tasked 10 radiologists of varied experience to conduct blind reviews of 100 four-view screening mammograms. Eye-tracking data and diagnostic decisions were collected from each radiologist under conditions mimicking clinical practice. Perceptual behavior was quantified using the fractal dimension of gaze scanpath, which was computed using the Minkowski-Bouligand box-counting method. To test the effect of previous behavior and decisions, we conducted a multifactor fixed-effects ANOVA. Further, to examine the predictive value of previous perceptual behavior and decisions, we trained and evaluated a predictive model for radiologists' current diagnostic decisions. ANOVA tests showed that previous visual behavior, characterized by fractal analysis, previous diagnostic decisions, and image characteristics of previous cases are significant predictors of current diagnostic decisions. Additionally, predictive modeling of diagnostic decisions showed an overall improvement in prediction error when the model is trained on additional information about previous perceptual behavior and diagnostic decisions.

摘要

先前的研究表明,医生的医疗决策可能会受到顺序背景的影响,尤其是在分析医学图像时,连续的刺激呈现出相似特征的情况下。这种类型的系统误差被心理物理学家称为顺序背景效应,因为它表明判断受到所检查病例序列中前一个病例的特征和决策的影响,而不是仅仅基于当前病例特有的特性。我们以乳腺钼靶筛查为例,确定放射科医生是否会经历某种形式的背景偏差。为此,我们探讨先前的感知行为和诊断决策与当前决策之间的相关性。我们假设放射科医生在先前病例中的视觉搜索模式和诊断决策能够预测其当前的诊断决策。为了验证我们的假设,我们让10位经验各异的放射科医生对100份四视图乳腺钼靶筛查图像进行盲法评估。在模拟临床实践的条件下,收集每位放射科医生的眼动追踪数据和诊断决策。使用凝视扫描路径的分形维数对感知行为进行量化,该分形维数通过闵可夫斯基 - 布利冈德盒计数法计算得出。为了测试先前行为和决策的影响,我们进行了多因素固定效应方差分析。此外,为了检验先前感知行为和决策的预测价值,我们训练并评估了一个用于预测放射科医生当前诊断决策的模型。方差分析测试表明,以分形分析为特征的先前视觉行为、先前的诊断决策以及先前病例的图像特征是当前诊断决策的重要预测因素。此外,诊断决策的预测建模显示,当模型基于有关先前感知行为和诊断决策的额外信息进行训练时,预测误差总体上有所改善。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf9f/5858736/e2c17a24fd93/JMI-005-031408-g001.jpg

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