Sara Börjesson

Investigation of image components affecting the detection of lung nodules in digital chest radiography

The aim of this work was to investigate and quantify the effects of system noise, nodule location, anatomical noise and anatomical background on the detection of lung nodules in different regions of the chest x-ray. Simulated lung nodules of diameter 10 mm but with varying detail contrast were randomly positioned in four different kinds of images: 1) clinical images collected with a 200 speed CR system, 2) images containing only system noise (including quantum noise) at the same level as the clinical images, 3) clinical images with removed anatomical noise, 4) artificial images with similar power spectrum as the clinical images but random phase spectrum. An ROC study was conducted with 5 observers. The detail contrast needed to obtain an Az of 0.80, C0.8, was used as measure of detectability. Five different regions of the chest x-ray were investigated separately. The C0.8 of the system noise images ranged from only 2% (the hilar regions) to 20% (the lateral pulmonary regions) of those of the clinical images. Compared with the original clinical images, the C0.8 was 16% lower for the de-noised clinical images and 71% higher for the random phase images, respectively, averaged over all five regions. In conclusion, regarding the detection of lung nodules with a diameter of 10 mm, the system noise is of minor importance at clinically relevant dose levels. The removal of anatomical noise and other noise sources uncorrelated from image to image leads to somewhat better detection, but the major component disturbing the detection is the overlapping of recognizable structures, which are, however, the main aspect of an x-ray image.

Detectability of pathological lesions in lumbar spine radiography

Thirty images with added simulated pathological lesions at two different dose levels (100% and 10% dose) were evaluated with the free-response forced error experiment by nine experienced radiologists. The simulated pathological lesions present in the images were classified according to four different parameters: the position within the lumbar spine, possibility to perform a symmetrical (left-right) comparison, the lesion contrast, and the complexity of the surrounding background where the lesion was situated. The detectability of each lesion was calculated as the fraction of radiologists who successfully detected the lesion before a false positive error was made. The influence of each of the four parameters on lesion detectability was investigated. The results of the study show that the influence of lesion contrast is the most important factor for detectability. Since the dose level had a limited effect on detectability, large dose savings can be made without reducing the detectability of pathological lesions in lumbar spine radiography.