Focal lung pathology detection in radiology: Is there an effect of experience on visual search behavior?

Specific visual expertise reduces susceptibility to visual illusions

Extensive exposure to specific kinds of imagery tunes visual perception, enhancing recognition and interpretation abilities relevant to those stimuli (e.g. radiologists can rapidly extract important information from medical scans). For the first time, we tested whether specific visual expertise induced by professional training also affords domain-general perceptual advantages. Experts in medical image interpretation (n = 44; reporting radiographers, trainee radiologists, and certified radiologists) and a control group consisting of psychology and medical students (n = 107) responded to the Ebbinghaus, Ponzo, Müller-Lyer, and Shepard Tabletops visual illusions in forced-choice tasks. Our results show that medical image experts were significantly less susceptible to all illusions except for the Shepard Tabletops, demonstrating superior perceptual accuracy. These findings could possibly be attributed to a stronger local processing bias, a by-product of learning to focus on specific areas of interest by disregarding irrelevant context in their domain of expertise.

How expectations alter search performance

We assessed how expected search difficulty impacts search performance when expectations match and do not match reality. Expectations were manipulated using a blocked design (75% of trials presented at the expected difficulty; target-distractor similarity increased with difficulty). Expectancy was assessed by examining the change in search performance between trials with accurate expectations and easier-than-expected or harder-than-expected trials, matched for search difficulty. Observers searched for Landolt-C targets (Exp-1) or real-world objects (Exp-2). Increased difficulty resulted in reduced accuracy, increased RT and object dwell times (targets and distractors; both experiments), and reduced guidance (Exp-2). Relative to the same level of search difficulty and when expectations were accurate, harder-than-expected search reduced accuracy, RT, and target object dwell times (Exp-1). Whereas easier-than-expected search increased RT and target dwell times (Exp-1). While Experiment 2 showed somewhat muted expectancy effects, easier-than-expected search replicated the increased RT observed in Exp-1, with an additional guidance decrement and increased distractor dwell time. These results demonstrate that expectations shift search performance toward the expected difficulty level. Additionally, post hoc analyses revealed that observers who experience larger difficulty effects also experience larger expectancy effects in RT, guidance, and target dwell time.

Eye tracking in digital pathology: A comprehensive literature review

Eye tracking has been used for decades in attempt to understand the cognitive processes of individuals. From memory access to problem-solving to decision-making, such insight has the potential to improve workflows and the education of students to become experts in relevant fields. Until recently, the traditional use of microscopes in pathology made eye tracking exceptionally difficult. However, the digital revolution of pathology from conventional microscopes to digital whole slide images allows for new research to be conducted and information to be learned with regards to pathologist visual search patterns and learning experiences. This has the promise to make pathology education more efficient and engaging, ultimately creating stronger and more proficient generations of pathologists to come. The goal of this review on eye tracking in pathology is to characterize and compare the visual search patterns of pathologists. The PubMed and Web of Science databases were searched using 'pathology' AND 'eye tracking' synonyms. A total of 22 relevant full-text articles published up to and including 2023 were identified and included in this review. Thematic analysis was conducted to organize each study into one or more of the 10 themes identified to characterize the visual search patterns of pathologists: (1) effect of experience, (2) fixations, (3) zooming, (4) panning, (5) saccades, (6) pupil diameter, (7) interpretation time, (8) strategies, (9) machine learning, and (10) education. Expert pathologists were found to have higher diagnostic accuracy, fewer fixations, and shorter interpretation times than pathologists with less experience. Further, literature on eye tracking in pathology indicates that there are several visual strategies for diagnostic interpretation of digital pathology images, but no evidence of a superior strategy exists. The educational implications of eye tracking in pathology have also been explored but the effect of teaching novices how to search as an expert remains unclear. In this article, the main challenges and prospects of eye tracking in pathology are briefly discussed along with their implications to the field.

Enhancing Imaging Anatomy Competency: Integrating Digital Imaging and Communications in Medicine (DICOM) Viewers Into the Anatomy Lab Experience

INTRODUCTION

Radiologic interpretation is a skill necessary for all physicians to provide quality care for their patients. However, some medical students are not exposed to Digital Imaging and Communications in Medicine (DICOM) imaging manipulation until their third year during clinical rotations. The objective of this study is to evaluate how medical students exposed to DICOM manipulation perform on identifying anatomical structures compared to students who were not exposed.

METHODS

This was a cross-sectional cohort study with 19 medical student participants organized into a test and control group. The test group consisted of first-year students who had been exposed to a new imaging anatomy curriculum (n = 9). The control group consisted of second-year students who had not had this experience (n = 10). The outcomes measured included quiz performance, self-reported confidence levels, and eye-tracking data.

RESULTS

Students in the test group performed better on the quiz compared to students in the control group (p = 0.03). Confidence between the test and control groups was not significantly different (p = 0.16), though a moderate to large effect size difference was noted (Hedges' g = 0.75). Saccade peak velocity and fixation duration between the groups were not significantly different (p = 0.29, p = 0.77), though a moderate effect size improvement was noted in saccade peak velocity for the test group (Hedges' g = 0.49).

CONCLUSION

The results from this study suggest that the early introduction of DICOM imaging into a medical school curriculum does impact students' performance when asked to identify anatomical structures on a standardized quiz.

Spotting the difference between pairs of nearly identical Perlin images: Influences of presentation formats

We investigated human performance in speed and precision of detecting a deviating visual target embedded in one of two otherwise identical non-figurative Perlin-noise images (i.e. a spot-the-difference task). The image-pairs were presented in four different presentation formats: spatially separated in horizontal or vertical direction while simultaneously presented, or sequentially separated on the same location with a brief delay or without any delay. In the two spatial conditions failure to detect the target within 30 sec (change blindness) occurred in about 6–7% of the trials, and with the brief delay 2.4% of the trials. Fast error-free detection (i.e. pop out) was obtained using the sequential format with no delay. Average detection time when target was detected was about 9 sec for the two spatial formats. Detection time was faster, about 6 sec, for the brief delay condition. In trials where detection was reported, the precision of locating the target was equal in the horizontal and brief delay conditions, and better than in the vertical condition. Misses obtained in the horizontal and brief delay conditions were also more strongly correlated than correlations between misses in the vertical and horizontal, and between the vertical and brief delay conditions. Some individuals’ performances when comparing images in the vertical direction were at chance level. This suggests influences of known poorer precision when making saccades in the vertical compared to horizontal direction. The results may have applications for radiologists since the stimuli and task is similar to radiologists’ task when detecting deviations between radiological images.

Training focal lung pathology detection using an eye movement modeling example

Purpose: Published reports suggest that nonoptimal visual search behavior is associated with false negatives in chest x-ray interpretation. Eye movement modeling example (EMME)-based training interventions, that is, interventions showing models of visual search to trainees, have been shown to improve visual search as well as task accuracy. Approach: We examined the detection of focal lung pathology on chest x-rays before and after two different EMME training interventions that have been shown to be efficient: (i) an EMME showing moving fixations on a blurred background (spotlight group) and (ii) an EMME showing moving fixations on a nonblurred background (circle group). These two experimental groups were compared to a control group that was only provided with the correct location of pathologies on the chest x-rays. Results: Performance outcomes showed improved detection sensitivity and specificity in all groups (also the control group). It appears that repetitive exposure to pathologies on chest x-rays with feedback resulted in enhanced pattern recognition. In addition, visual search strategies became more efficient during post-tests. Conclusion: Repetitive exposure to a focal lung pathology detection task with feedback improves overall performance. However, the specific EMME training interventions did not add any further advantages. Similar training interventions can be provided online to assess feasibility and reproducibility of such (or similar) training formats. Such training can, for example, reduce the number of false negative errors, especially for novices.

Eye movements reflect expertise development in hybrid search

Domain-specific expertise changes the way people perceive, process, and remember information from that domain. This is often observed in visual domains involving skilled searches, such as athletics referees, or professional visual searchers (e.g., security and medical screeners). Although existing research has compared expert to novice performance in visual search, little work has directly documented how accumulating experiences change behavior. A longitudinal approach to studying visual search performance may permit a finer-grained understanding of experience-dependent changes in visual scanning, and the extent to which various cognitive processes are affected by experience. In this study, participants acquired experience by taking part in many experimental sessions over the course of an academic semester. Searchers looked for 20 categories of targets simultaneously (which appeared with unequal frequency), in displays with 0-3 targets present, while having their eye movements recorded. With experience, accuracy increased and response times decreased. Fixation probabilities and durations decreased with increasing experience, but saccade amplitudes and visual span increased. These findings suggest that the behavioral benefits endowed by expertise emerge from oculomotor behaviors that reflect enhanced reliance on memory to guide attention and the ability to process more of the visual field within individual fixations.

What do radiologists look for? Advances and limitations of perceptual learning in radiologic search

Supported by guidance from training during residency programs, radiologists learn clinically relevant visual features by viewing thousands of medical images. Yet the precise visual features that expert radiologists use in their clinical practice remain unknown. Identifying such features would allow the development of perceptual learning training methods targeted to the optimization of radiology training and the reduction of medical error. Here we review attempts to bridge current gaps in understanding with a focus on computational saliency models that characterize and predict gaze behavior in radiologists. There have been great strides toward the accurate prediction of relevant medical information within images, thereby facilitating the development of novel computer-aided detection and diagnostic tools. In some cases, computational models have achieved equivalent sensitivity to that of radiologists, suggesting that we may be close to identifying the underlying visual representations that radiologists use. However, because the relevant bottom-up features vary across task context and imaging modalities, it will also be necessary to identify relevant top-down factors before perceptual expertise in radiology can be fully understood. Progress along these dimensions will improve the tools available for educating new generations of radiologists, and aid in the detection of medically relevant information, ultimately improving patient health.