Variability of semiautomated lung nodule volumetry on ultralow-dose CT: comparison with nodule volumetry on standard-dose CT

Abstract

The study investigates the effect of a substantial dose reduction on the variability of lung nodule volume measurements by assessing and comparing nodule volumes using a dedicated semiautomated segmentation software on ultralow-dose computed tomography (ULD-CT) and standard-dose computed tomography (SD-CT) data. In 20 patients, thin-slice chest CT datasets (1 mm slice thickness; 20% reconstruction overlap) were acquired at ultralow-dose (120 kV, 5 mAs) and at standard-dose (120 kV, 75 mAs), respectively, and analyzed using the segmentation software OncoTREAT (MeVis, Bremen, Germany; version 1.3). Interobserver variability of volume measurements of 202 solid pulmonary nodules (mean diameter 11 mm, range 3.2-44.5 mm) was calculated for SD-CT and ULD-CT. With respect to interobserver variability, the 95% confidence interval for the relative differences in nodule volume in the intrascan analysis was measured with -9.7% to 8.3% (mean difference -0.7%) for SD-CT and with -12.6% to 12.4% (mean difference -0.2%) for ULD-CT. In the interscan analysis, the 95% confidence intervals for the differences in nodule volume ranged with -25.1% to -23.4% and 26.2% to 28.9% (mean difference 1.4% to 2.1%) dependent on the combination of readers and scans. Intrascan interobserver variability of volume measurements was comparable for ULD-CT and SD-CT data. The calculated variability of volume measurements in the interscan analysis was similar to the data reported in the literature for CT data acquired with equal radiation dose. Thus, the evaluated segmentation software provides nodule volumetry that appears to be independent of the dose level with which the CT source dataset is acquired.

Figures

Fig 1

Distribution of nodule diameters of 202 nodules included in the analysis as measured automatically by the software.

Fig 2

a The graph shows the interobserver agreement of volume measurements of 202 nodules at SD-CT. The relative differences between measurements of reader 1 and reader 2 are plotted against the mean nodule volume (logarithmic scale). The mean relative difference is shown by the continuous line; upper and lower limits of agreement are shown by the dashed lines. R1 reader 1, R2 reader 2. b The graph shows the interobserver agreement of volume measurements of 202 nodules at ULD-CT. The relative differences between measurements of reader 1 and reader 2 are plotted against the mean nodule volume (logarithmic scale). The mean relative difference is shown by the continuous line; upper and lower limits of agreement are shown by the dashed lines. R1 reader 1, R2 reader 2.

Fig 3

The graphs show the intraobserver and interobserver agreements of volume measurements of 202 nodules in the interscan analysis. The mean relative difference is shown by the continuous line; upper and lower limits of agreement are shown by the dashed lines. R1 reader 1, R2 reader 2.

Fig 4

a Volume measurement of an intraparenchymal pulmonary nodule using the CT dataset acquired in ultralow-dose technique. The axial thin-slice section is displayed on the left and multiplanar reconstructions as well as volume rendering on the right. b Volume measurement of the identical pulmonary nodule using the CT dataset acquired in standard-dose technique.

Fig 5

a Volume measurement of a more complex-shaped pulmonary nodule with pleural and vascular contact and spiculated margins in ULD-CT. The multiplanar reconstructions and volume-rendered image illustrate the segmentation result with successful separation of the nodule from the adjacent structures. b Corresponding images of the identical pulmonary nodule obtained with SD-CT.