When looking at an x-ray, radiologists are typically asked to localize a tumor (if present), and to classify it, judging its size, class, position and so on. Importantly, during this task, radiologists examine on a daily basis hundreds and hundreds of x-rays, seeing several images one after the other. A main underlying assumption of this task is that radiologists? percepts and decisions on a current X-ray are completely independent of prior events. Recent results showed that this is not true: our perception and decisions are strongly biased by our past visual experience. Although serial dependencies were proposed to be a purposeful mechanism to achieve perceptual stability of our otherwise noisy visual input, serial dependencies play a crucial and deleterious role in the everyday task performed by radiologists. For example, an x-ray containing a tumor can be classified as benign depending on the content of the previously seen x-ray. Given the importance and the impact of serial dependencies in clinical tasks, in this proposal, we plan to (1) establish, (2) identify and (3) mitigate the conditions under which serial effects determine our percepts and decisions in tumor search tasks.
In Aim 1, we will establish the presence of serial effects in four different clinically relevant domains: tumor detection, tumor classification, tumor position and recognition speed.
In Aim 2, we plan to identify the specific boundary conditions under which visual serial dependence impacts tumor search in radiology.
In Aim 3, once we will fully understand these boundary conditions in Aim 2, we will propose a series of task and stimulus manipulations to control and mitigate the deleterious effects of visual serial dependence on tumor search. As a result of these manipulations, visual search performance should improve in measurable ways (detection, classification, position, speed).
Aim 3 is particularly crucial because it will allow us to propose new guidelines which will greatly improve tumor recognition in x-ray images, making this task even more effective and reliable. Taken together, the proposed studies in Aim 1, 2, and 3 will allow us to establish, identify, and mitigate the deleterious effect of serial dependencies in radiological search tasks, which could have a significant impact on the health and well-being of patients everywhere. ! ! !

Public Health Relevance

Our proposal is designed to investigate the detrimental impact of visual serial dependencies in clinical settings. Serial dependencies significantly impact our perceptual experience, but little is known about their detrimental consequences when radiologists are asked to detect tumors in x-rays. Crucially, the final goal of our research project is to develop recommendations and guidelines to mitigate the negative effect of serial effects and, thus, improve diagnosis accuracy.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
1R01CA236793-01
Application #
9707393
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Horowitz, Todd S
Project Start
2019-04-17
Project End
2024-03-31
Budget Start
2019-04-17
Budget End
2020-03-31
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of California Berkeley
Department
Psychology
Type
Schools of Arts and Sciences
DUNS #
124726725
City
Berkeley
State
CA
Country
United States
Zip Code
94710