A Human Computer Interaction Solution for Radiology Reporting: Evaluation of the Factors of Variation

Purpose: The purpose of this research is to evaluate the human and technical factors required to create a human-computer interface (HCI) for a structured reporting solution based on eye-gaze and speech signals. Gaze and speech signals from radiologists acquired during simulated image interpretation and dictation sessions were analyzed to determine a) variation of gaze – speech temporal relationships in a dictation environment, and b) variation in eye movements for a particular image interpretation task among radiologists. Knowledge of these factors provides information regarding the complexity of the image interpretation/dictation task, and provides information that can be used to design a HCI for use in diagnostic radiology. Our ultimate goal is to use these data to create an HCI to automate the generation of a particular type of structured radiology report[1]. Materials and Methods: This study received Institutional Review Board approval, which required informed consent from the participating radiologists as they were the subjects in this experiment. The radiologic images used in this study were de-identified to meet HIPAA compliance. Five radiologists performed image interpretation and dictation tasks on 30 images from 3 modalities (10 images per modality), during which their eye gaze and speech signals were recorded using a Tobii eye-tracking device (Tobii T60 XL, Tobii Technology, Danderyd, Sweden). The dictation tasks were designed to be consistent across each modality and with each radiologist identifying two targeted findings (e.g., identify and describe a lung mass on a chest x-ray followed by making a comment regarding heart size). The null hypothesis is that the gaze-speech temporal relationship is independent of certain human and technical factors, including the radiologist, image content, and target order. Results: Our results indicate that there are substantial differences in the gaze-speech relationship among radiologists (p<0.001). There is no statistically significant evidence that the gazespeech temporal relationship depends upon the particular image modality (p=0.909) or target order (p=0.142). Analysis of gaze paths suggests that the search path variance among radiologists is significant. Conclusions: Our data indicate that the a) gaze-speech relationships and b) scan paths substantially vary among radiologists, thus implying that a gaze-speech system for automating the capture of data for structured reporting processes should be customized for each user. The image resolution and layout, image content, and order of targets during an image interpretation session are not relevant factors to consider when designing an HCI. Our findings can be applied to the design of other HCI solutions for radiological applications that involve visual inspection and verbal descriptions of image findings.