Digital Pathology (DP) reporting workstations permit eye tracking experiments which can aid our understanding of reading strategies and medical errors in pathology. However, eye tracking with DP slides is complex due to the nature of the slide viewing process: slide panning and zooming. Eye tracking technology records gaze coordinates to a screen surface, but these coordinates do not account for the ever-changing on-screen content (due to slide navigation), and therefore it is essential to track pathologists’ slide navigation to determine where on the slide the pathologist has viewed and what features were fixated. Additionally, visualising the resulting eye tracking data proves challenging due to the zooming component. Other eye tracking studies in DP have accounted for slide navigation by employing custom slide viewers that output slide movements as a data stream with the eye tracking data which are co-registered for analysis. We are conducting a DP eye tracking study using a commercial slide viewer which has been adopted at selected UK hospital sites, but slide movement data cannot be outputted as a data stream in this context. Therefore, we’re developing a software platform using computer vision techniques that can be applied to the recorded screen capture of the DP workstation which is synchronised with the eye tracking data. The developed algorithm could be adapted for use with other commercial slide viewers for future studies. Here, we explore how studies have addressed these issues and we discuss our approach.
KEYWORDS: Digital breast tomosynthesis, Eye tracking, Diagnostics, Breast, Material fatigue, Displays, Cameras, Tunable filters, Statistical analysis, Signal detection
Digital Breast Tomosynthesis (DBT) increases breast cancer detection rates but produces a significantly greater number
of images for screeners to read compared to traditional two-dimensional (2-D) mammograms. Putting screeners at risk of
fatigue and therefore error in detecting cancers.
The aim of this study was to explore if screeners showed differences in subjective fatigue, blink metrics and diagnostic
accuracy during a DBT reading session with and without breaks.
Prospective study including 45 participants from 6 different hospital sites around England between December 2020 to
April 2022. Non-intrusive, screen mounted eye tracking cameras (60Hz sampling rate) were set up in the participant’s
natural reading environment. Forty DBT cases were read in a random order (47.5% malignant, 12.5% benign, 40%
normal). Each breast was rated as normal or benign (return to screen) or indeterminate, suspicious or highly suspicious
(recall). Twenty-one participants had a break at approximately 40 minutes into the session.
Participants without a break showed a significantly greater difference in subjective fatigue before and after the reporting
session (44% vs 33%, p=0.037). Furthermore, those without breaks exhibited significantly greater blinks per minute
(15.75 vs 13.25, p<0.001) and blink duration (milliseconds) (296 vs 286, p<0.001). There was no significant difference
in overall accuracy between the cohorts (p=0.921).
Blink metrics have the potential to be used in identifying early onset of fatigue during reading sessions.
Purpose: The introduction of whole slide imaging and digital pathology has enabled greater scrutiny of visual search behaviors among pathologists. We aim to investigate zooming and panning behaviors, external markers of visual processing capabilities, and the changes with experience.
Approaches: Twenty digitized breast core needle biopsy histopathology slides were obtained from the circulating slides from the main digital pathology trial (IRAS number: 258799). These were presented to five pathologists with varying experience (1.5 to 40 years) whose examinations were recorded. Data of visual fixations were collected using eye-tracking cameras, and the magnification data and zooming behaviors were extracted in an objective fashion by an automated algorithm. The relationship between experience and metrics was analyzed using mixed-effects regression analyses.
Results: There was a significant association between experience and both reading times (p < 0.001) and a number of fixations (p < 0.001), with these relationships being inversely proportional. The greater experience was also associated with greater diagnostic accuracy (p = 0.033). We found that experience was significantly associated with greater use of magnification changes (p < 0.001). Conversely, less experience showed a near significant association with the increased proportion of time spent panning (p = 0.070).
Conclusions: Fewer fixations needed to reach a diagnosis and quicker reading times are indicative of greater cognitive and visual processing capabilities with greater experience. These cognitive capabilities may be a prerequisite for the more frequent zooming changes that are more prevalent with increasing experience.
Purpose Digital breast tomosynthesis (DBT) exhibits increased sensitivity and specificity compared to 2D mammography (DM), but DBT images are complex and interpretation takes longer. Clinicians may fatigue or hit a cognitive limit sooner when reading DBT, potentially reducing diagnostic accuracy. Eye blink behaviour was investigated to explore fatigue and cognitive load. Methods Screeners (N=47) from five UK breast screening centres were eye tracked as they read 40 DBT cases (15 normal, 6 benign and 19 malignant), from November 2019-July 2021. Differences in diagnostic accuracy and blink behaviour were analysed over the course of the reading session. Blink rates and case durations were investigated by case malignancy and outcome using T-tests and ANOVAs (α=0.05). Results Blink rates were higher on malignant cases than on normal cases (p=0.004), and blink rates were higher for cases with true positive outcomes than for cases with true negative outcomes (p=0.013). Participants spent less time on malignant cases than normal or benign cases (ps=<0.0001), whilst spending more time on cases with a false positive outcome than on cases with a true negative or true positive outcome (ps<0.0001). No significant difference in blink rate or diagnostic performance by time through reporting session. Conclusion Differences in blink rate and time on case are associated with case malignancy and outcome, potentially reflecting varying cognitive demand and interpretation strategies. Further investigation into blinking during medical image interpretation may identify robust signals of cognition and fatigue that could be used for education and training purposes, whilst indicating optimal screening session duration.
The UK national screening program for breast cancer currently uses Full Field Digital Mammography (FFDM). Various studies have shown that DBT has a higher sensitivity and specificity in identifying early breast cancer apart from benign pathologies, even in very dense breasts. This potentially makes DBT a better screening modality to detect early breast cancer, as well as minimize false positive recall rates. However, DBT has multiple image slices and thereby makes reading cases inherently a longer and potentially more visually fatiguing task. Our previous studies (Dong et al, 2017 and 2018) have demonstrated the impact of institutional training on reading techniques in DBT. The reading technique itself appears to have an effect on total reading time. In other follow-on studies we have employed eye tracking which gives rise to complex data sets, including parameters such as eyelid opening and pupil diameter measures, which can then be employed to gauge blinks and fatigue onset. Findings from this work have guided changes in our blink identification techniques and we have now developed semi-automated programmed processes which can analyze the large data set and provide a more accurate assessment of fatigue and vigilance parameters through blink detection. Here, we have considered ‘eyelid opening’ parameters of both the left and the right eye separately. Having such a separated approach allowed us to tease out particular aspects of blinking. Similar to Schleicher et al (2008), we found there to be ultra-short blinks (30-50 milli seconds), short blinks (51- 100 msecs), long blinks (101-500 msecs) and also microsleeps (>500 msecs). We argue that the changes observed in the frequencies of these blinks can be used as a measure of vigilance and fatigue during DBT reading.
Currently in the UK, a national trial to test the effect of a transition from traditional Full Field Digital Mammography (FFDM) to Digital Breast Tomosynthesis (DBT) is being conducted. DBT, having a higher sensitivity and specificity as compared to FFDM alone, could be a better modality in national breast cancer screening. However, its incorporation in the incredibly busy and detailed UK screening program is difficult. Reading times in DBT have been shown to be longer and strenuous (Connor et al, 2012). Therefore, much research needs to be completed to develop recommendations for its efficiency. One key factor in DBT reading is the progression of fatigue, as both a cause and effect of prolonged reading times. We aimed to develop a program to process real time raw eye tracking data to identify a change in fatigue-state through blink detection. Our focus was on analysing the whole data set and defining blinks through observed events. Two real time signals which the eye tracker generates, namely the left and right ‘Eyelid Opening’ value, were considered. Through assessment of these signals, blinks of varying duration were identified. Additional parameters such as recorded frame sequences and time stamps were added to the processing to delineate the exact occurrence of these blinks during the reading process. We aim to analyse past and future large DBT eye tracked files, with our processing software, to identify the point of fatigue onset in a DBT reading session.
Traditional diagnostic modalities have been, for the most part, static two-dimensional images displayed on film
or computer screen. More recent diagnostic modalities are solely computer-based and consist of large data-sets
of multiple images. Image perception and visual search using these new modalities are complicated by the need
to interact with the computer in order to navigate through the data. This paper reports the late-breaking results
from two small studies into visual search within two types of CT Colonography (CTC) visualisations. The twelve
novice observers in the study were taking part in a week-long course in CTC and were tested at the beginning
and end of the course. A number of expert observers were also recorded. The two visualisations used in the
study were 2D axial view and 3D colon fly-through. In both cases, searching was performed by inspecting the
colon wall, but by two distinct mechanisms. The first study recorded observer eye-gaze and image navigation in
a CTC axial view. The search strategy was to follow the lumen of the colon and detect abnormalities in the colon
wall. The observer used the physical computer interface to navigate through the set of axial images to perform
this task. The 3D fly-through study recorded observer eye-gaze whilst watching a recording of a computed flight
through the colon lumen. Unlike the axial view there was no computer control, so inspection of the colon surface
was dictated by the speed of flight through the colon.
This paper describes a software framework and analysis tool to support the collection and analysis of eye movement and perceptual feedback data for a variety of diagnostic imaging modalities. The framework allows the rapid creation of experiment software that can display a collection of medical images of a particular modality, capture eye trace data, and record marks added to an image by the observer, together with their final decision. There are also a number of visualisation techniques for the display of eye trace information. The analysis tool supports the comparison of individual eye traces for a particular observer or traces from multiple observers for a particular image. Saccade and fixation data can be visualised, with user control of fixation identification functions and properties. Observer markings are displayed, and predefined regions of interest are supported. The software also supports some interactive and multi-image modalities. The analysis tool includes a novel visualisation of scan paths across multi-image modalities. Using an exploded 3D view of a stack of MRI scan sections, an observer's scan path can be shown traversing between images, in addition to inspecting them.
Four observer groups with different levels of expertise were tested to determine the effect of feedback on eye movements and accuracy whilst performing a simple radiological task. The observer groups were 8 experts, 9 year 1 radiography students, 9 year 3 radiography students, and 10 naive observers (psychology students). The task was fracture detection in the wrist. A test bank of 32 films was compiled with 14 normals, 6 grade 1 fractures (subtle appearance), 6 grade 2 fractures, and 6 grade 3 fractures (obvious appearance). Eye tracking was carried out on all observers to demonstrate differences in visual activity. Observers were asked to rate their confidence in their decision on a ten point scale. Feedback was presented to the observers in the form of circles displayed on the film where fixations had occurred, the size of which was proportional to the length of fixation. Observers were asked to repeat their decision rating. Accuracy was determined by ROC analysis and the area under the curve (AUC). In two groups, the novices and first year radiography students, the feedback resulted in no significant difference in the AUC. In the other two groups, experts (p = 0.002) and second year radiography students (p = 0.031), feedback had a negative effect on performance. The eye tracking parameters were measured for all subjects and compared. This is work in progress, but initial analysis of the data suggests that in a simple radiological task such as fracture detection, where search is very limited, feedback by encouraging observers to look harder at the image can have a negative effect on image interpretation performance, however for the novice feedback is beneficial as post feedback eye-tracking parameters measured more closely matched those of the experts.
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