Raghunath Vignesh, Braxton Melissa O, Gagnon Stephanie A, Brunyé Tad T, Allison Kimberly H, Reisch Lisa M, Weaver Donald L, Elmore Joann G, Shapiro Linda G
Department of General Internal Medicine, University of Washington, USA.
J Pathol Inform. 2012;3:43. doi: 10.4103/2153-3539.104905. Epub 2012 Dec 20.
Digital pathology has the potential to dramatically alter the way pathologists work, yet little is known about pathologists' viewing behavior while interpreting digital whole slide images. While tracking pathologist eye movements when viewing digital slides may be the most direct method of capturing pathologists' viewing strategies, this technique is cumbersome and technically challenging to use in remote settings. Tracking pathologist mouse cursor movements may serve as a practical method of studying digital slide interpretation, and mouse cursor data may illuminate pathologists' viewing strategies and time expenditures in their interpretive workflow.
To evaluate the utility of mouse cursor movement data, in addition to eye-tracking data, in studying pathologists' attention and viewing behavior.
Pathologists (N = 7) viewed 10 digital whole slide images of breast tissue that were selected using a random stratified sampling technique to include a range of breast pathology diagnoses (benign/atypia, carcinoma in situ, and invasive breast cancer). A panel of three expert breast pathologists established a consensus diagnosis for each case using a modified Delphi approach.
Participants' foveal vision was tracked using SensoMotoric Instruments RED 60 Hz eye-tracking system. Mouse cursor movement was tracked using a custom MATLAB script.
Data on eye-gaze and mouse cursor position were gathered at fixed intervals and analyzed using distance comparisons and regression analyses by slide diagnosis and pathologist expertise. Pathologists' accuracy (defined as percent agreement with the expert consensus diagnoses) and efficiency (accuracy and speed) were also analyzed.
Mean viewing time per slide was 75.2 seconds (SD = 38.42). Accuracy (percent agreement with expert consensus) by diagnosis type was: 83% (benign/atypia); 48% (carcinoma in situ); and 93% (invasive). Spatial coupling was close between eye-gaze and mouse cursor positions (highest frequency ∆x was 4.00px (SD = 16.10), and ∆y was 37.50px (SD = 28.08)). Mouse cursor position moderately predicted eye gaze patterns (Rx = 0.33 and Ry = 0.21).
Data detailing mouse cursor movements may be a useful addition to future studies of pathologists' accuracy and efficiency when using digital pathology.
数字病理学有可能极大地改变病理学家的工作方式,但对于病理学家在解读数字全切片图像时的观察行为却知之甚少。虽然在查看数字切片时跟踪病理学家的眼球运动可能是捕捉病理学家观察策略的最直接方法,但这种技术在远程环境中使用起来既繁琐又具有技术挑战性。跟踪病理学家的鼠标光标移动可能是研究数字切片解读的一种实用方法,并且鼠标光标数据可能会揭示病理学家在其解读工作流程中的观察策略和时间消耗。
除了眼动追踪数据之外,评估鼠标光标移动数据在研究病理学家的注意力和观察行为方面的效用。
病理学家(N = 7)查看了10张使用随机分层抽样技术选取的乳腺组织数字全切片图像,这些图像涵盖了一系列乳腺病理诊断(良性/非典型性、原位癌和浸润性乳腺癌)。由三位乳腺病理专家组成的小组采用改良的德尔菲法为每个病例确定了共识诊断。
使用SensoMotoric Instruments RED 60 Hz眼动追踪系统跟踪参与者的中央凹视觉。使用自定义的MATLAB脚本跟踪鼠标光标移动。
以固定间隔收集眼注视和鼠标光标位置的数据,并通过幻灯片诊断和病理学家专业知识进行距离比较和回归分析。还分析了病理学家的准确性(定义为与专家共识诊断的一致百分比)和效率(准确性和速度)。
每张幻灯片的平均查看时间为75.2秒(标准差 = 38.42)。按诊断类型划分与专家共识的准确性(一致百分比)为:83%(良性/非典型性);48%(原位癌);93%(浸润性)。眼注视和鼠标光标位置之间的空间耦合紧密(最高频率的∆x为4.00像素(标准差 = 16.10),∆y为37.50像素(标准差 = 28.08))。鼠标光标位置适度预测了眼注视模式(Rx = 0.33,Ry = 0.21)。
详细说明鼠标光标移动的数据可能是未来研究病理学家使用数字病理学的准确性和效率时的一个有用补充。