Optimization of region of interest luminances may enhance radiologists' light adaptation

Acad Radiol. 2008 Apr;15(4):488-93. doi: 10.1016/j.acra.2007.11.005.

Abstract

Rationale and objectives: Radiologic image details are best discriminated at luminance levels to which the eye is adapted. Recommendations that ambient light conditions are matched to overall monitor luminance to encourage appropriate adaptation are based on an assumption that clinically significant regions within the image match average monitor luminance. The current work examines this assumption.

Materials and methods: Three image types were considered: posteroanterior (PA) chest; PA wrist; and computed tomography (CT) head. Luminance at clinically significant regions was measured at hilar region and peripheral lung (chest), distal radius (wrist), and supraventricular white matter (head). Average monitor luminances were calculated from measurements at 16 regions of the display face plate. Three ambient light levels-30, 100 and 400 lux-were employed. Thirty samples of each image type were used.

Results: Statistically significant differences were noted between average monitor luminances and clinically important regions of interest of up to a factor of 3.8, 2, and 6.3 for chest, wrist, and CT head images respectively (P < .0001). Values for the hilum of the chest and distal radius were higher than average monitor levels, whereas the reverse was observed for the peripheral lung and CT brain. Increasing ambient light had no impact on results.

Conclusions: Clinically important radiologic information for common radiologic examinations is not being presented to observers in a way that facilitates optimized adaptation. This may have a significant impact on the ability of the observer to identify details with low contrast discriminability. The importance of image-processing algorithms focussing on clinically significant abnormalities rather than anatomic regions is highlighted.

MeSH terms

  • Adaptation, Physiological*
  • Analysis of Variance
  • Computer Terminals*
  • Humans
  • Lighting*
  • Observer Variation
  • Radiographic Image Enhancement*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Task Performance and Analysis
  • Tomography, X-Ray Computed*
  • Visual Perception