Paper
14 April 2000 Evaluation of head CT exams: resident and attending diagnoses
Elizabeth A. Krupinski, William Berger, William Erly
Author Affiliations +
Abstract
The goal of this study was to evaluate performance of radiology resident in interpretation of head CT exams ordered by emergency room physicians, and to compare their accuracy with the attending radiologists. 1324 consecutive CT head exams ordered by the ER were interpreted by radiology residents. They reported whether the case was normal or abnormal, noted the relevant findings, and reported their decision confidence using a 6-point scale. Attending neuroradiologists subsequently interpreted the exams. The exams were grouped into 3 categories based on correlation of readings: agree, disagree-insignificant, disagree-significant. There was 91% agreement between resident and attending diagnoses, 7% disagree-insignificant and 2% disagree- significant. Disagreements occurred more often on abnormal than normal cases. Disagreements occurred more often with 1st and 2nd year residents than with 3rd and 4th. Resident confidence was highest for 3rd years, followed by 4th, 2nd and 1st. The less confident a resident was in their diagnosis, the more likely a disagreement occurred. Cases in which a resident expresses a low level of confidence should be carefully checked by the attending since these cases were more often associated with a disagreement than those with high confidence.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Elizabeth A. Krupinski, William Berger, and William Erly "Evaluation of head CT exams: resident and attending diagnoses", Proc. SPIE 3981, Medical Imaging 2000: Image Perception and Performance, (14 April 2000); https://doi.org/10.1117/12.383108
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Diagnostics

Head

Radiology

Computed tomography

Visualization

Medical imaging

Visual analytics

Back to Top