Purpose: During the COVID-19 pandemic, many radiologists transitioned to remote reading at home. One concern when reading in a non-controlled reading environment is the appropriateness of ambient light levels. The purpose of this study was to develop a visual test pattern-based evaluation method to assess ambient light appropriateness.
Methods: A series of six test patterns were created by adding letters at different contrasts to a uniform background. Each pattern contained 5 to 10 letters, distributed in a uniform, random fashion, to create an element of search. The choice of letters was loosely based on a Snellen chart. The uniform background pixel values ranged from 0 to 98% at 6 different levels. In a controlled reading environment and by use of a medical-grade DICOM GSDF calibrated display, three readers identified the lowest detectable contrast letter at two ambient light level settings (30 and 200 lux). To assess the generalizability of the approach, at each background brightness level, four sets of patterns were read.
Results: In the darkest background, readers were able to detect the lowest contrast letter in 11 out of 12 reads (91% correct) at low ambient light levels (30 lux), but at 200 lux they were never able to detect the lowest contrast letter. In the second darkest background, low contrast detectability was 100% at 30 lux and 50% at 200 lux. The low contrast detectability was not affected by ambient light level in brighter backgrounds.
Conclusion: The results indicate that these display test patterns enable the identification of excessive ambient light levels that potentially interfere with radiologists’ low-contrast detection performance, particularly in darker luminance regions of the images. This test pattern-based approach does not require external photometers and can be readily implemented into PACS.
Diagnostic Radiology, Image Visualization, Observer Performance