The Radiologist's Gaze: Mapping Three-Dimensional Visual Search in Computed Tomography of the Abdomen and Pelvis

J Digit Imaging. 2019 Apr;32(2):234-240. doi: 10.1007/s10278-018-0121-8.

Abstract

A radiologist's search pattern can directly influence patient management. A missed finding is a missed opportunity for intervention. Multiple studies have attempted to describe and quantify search patterns but have mainly focused on chest radiographs and chest CTs. Here, we describe and quantify the visual search patterns of 17 radiologists as they scroll through 6 CTs of the abdomen and pelvis. Search pattern tracings varied among individuals and remained relatively consistent per individual between cases. Attendings and trainees had similar eye metric statistics with respect to time to first fixation (TTFF), number of fixations in the region of interest (ROI), fixation duration in ROI, mean saccadic amplitude, or total number of fixations. Attendings had fewer numbers of fixations per second versus trainees (p < 0.001), suggesting efficiency due to expertise. In those cases that were accurately interpreted, TTFF was shorter (p = 0.04), the number of fixations per second and number of fixations in ROI were higher (p = 0.04, p = 0.02, respectively), and fixation duration in ROI was increased (p = 0.02). We subsequently categorized radiologists as "scanners" or "drillers" by both qualitative and quantitative methods and found no differences in accuracy with most radiologists being categorized as "drillers." This study describes visual search patterns of radiologists in interpretation of CTs of the abdomen and pelvis to better approach future endeavors in determining the effects of manipulations such as fatigue, interruptions, and computer-aided detection.

Keywords: Body imaging; CT; Drillers; Eye tracking; Scanners; Visual search.

MeSH terms

  • Abdomen / diagnostic imaging*
  • Clinical Competence
  • Data Display
  • Diagnostic Errors / statistics & numerical data*
  • Eye Movements / physiology*
  • Fixation, Ocular / physiology
  • Humans
  • Pattern Recognition, Visual / physiology*
  • Pelvis / diagnostic imaging*
  • Radiologists*
  • Task Performance and Analysis
  • Tomography, X-Ray Computed*
  • User-Computer Interface