Improvement in the reproducibility of region of interest using an auditory feedback loop: A pilot assessment using dynamic contrast‐enhanced (DCE) breast MR images

Abstract

To augment traditional visual data perception of complex multiparametric imaging data sets by adding auditory feedback to improve the delineation of regions of interest (ROIs) in tumor assessment in dynamic contrast-enhanced (DCE) MRI. In addition to conventional display methodologies, we have created an application window which interfaces with audio output using dynamically loadable sound modules, providing goodness of fit (GF) information through auditory feedback. We have assessed effectiveness of conveying sound information with three independent readers on eight DCE-MR breast image data sets. The assessment was based on either conventional visual only mode or combined visual plus auditory mode. For statistical comparison between two sensory approaches, interobserver repeatability was measured with three different criteria. Adding auditory feedback improves repeatability significantly (P < 0.01), and the enhanced sensory approach had higher repeatability than visual only mode in visually complex breast tumor cases. However, in easy and moderate cases, visual only mode was more reproducible than the combined mode with very high significance (P < 0.001). Adding auditory information to visual based image analysis for identifying tumor ROIs provides higher interobserver repeatability for analyzing complex multidimensional/multiparametric medical image data sets with visually difficult lesions to delineate.