Nonsolid or ground-glass nodules (GGNs) are a major challenge, both clinically [1
] and in lung cancer screening trials, because these nodules are far less common than solid nodules, are slow-growing, are often multiple, and have a high malignancy rate. For example, in the Early Lung Cancer Action Project study [2
], 19% of cases of positive screening results involved pure or partly solid GGNs. In the first round of the Dutch-Belgian lung cancer screening trial [3
], only 2.0% of the total of 8673 nodules found in 7557 participants were pure nonsolid nodules or partly solid GGNs. Growth rates with a mean volume doubling time of 813 days and malignancy rates up to 63% have been reported for pure GGNs [2
A GGN is defined as an area of increased lung attenuation with preservation of the bronchial and vascular margins [5
]. Given the slow growth rate, the diagnosis of growing GGNs is challenging. According to results of a study by de Hoop et al. [6
], measurements of mass can lead to earlier detection of growth of GGNs than can volume and diameter measurements. Mass measurements were obtained through manual segmentation on axial CT images followed by calculation of volume with the computer. GGN mass was then calculated with the attenuation values expressed in terms of physical density. These manual measurements require approximately 5–10 minutes of segmentation time. Development of a more automated method for segmentation of these nodules would be a major scientific advance.
In this study, using a chest phantom with eight nodules of different size and density, we investigated a software program that automatically segments GGNs and allows adjustment of roundness and density and then calculates volume and mass. We also investigated the influence of CT machine, reconstruction algorithm, tube voltage, and tube current on the measurements.
Because volumetry is preferable to diameter measurements for quantifying the growth rate of GGNs as an indicator of malignancy [6
], we evaluated a prototype software program that semiautomatically measures density, mass, and volume. To the best of our knowledge, our study is the first to focus not only on computer-aided segmentation and volume measurement of GGNs but also on measurement of mass. Our study results are promising in showing the volume and mass measurements of nodules of different sizes and different densities. After easy manual adjustments, overall APE of volume and mass measurements of 5% and 13% was achieved with measurements that are made rapidly, within 1 second of computation time.
There have been limited reports on volume measurements of GGNs [9
]. Odaetal. [10
] reported errors between −4.1% and 7.1% in a study with a different phantom from ours with nodules measuring 5 mm or more. Those authors, however, performed only routine-dose CT, which is not available in the context of screening studies or follow-up studies for clinically detected nodules. We focused on a typical low-dose lung cancer screening protocol using 125 kVp and 25 mAs because that is the context in which most GGNs are found and evaluated in follow-up studies.
Linning and Daqing [11
] also varied the tube current–time product setting in a phantom study with tube current ranging from 30 to 210 mA, resulting in a tube current–time product of 15–105 mAs. Their nodules were all fairly large, between 589 and 897 mm3
. Those investigators reported an APE for volume measurements of 0.14–22.67% with a mean relative percentage error ranging from −7% at 60 mA to 2.32% at 120 mA. Taking into account the substantial differences between the nodules in their study and those in our study, it is difficult to compare our studies. It is important to realize the larger errors in small GGNs at low-dose CT in the evaluation of nodule growth, because growth is defined as an increase in the nodule measurement exceeding the measurement error. This emphasizes the difficulty of using low-dose imaging to diagnose growth of small GGNs.
We did not find significant differences between various generations of CT scanners from a single vendor or between filters. Unlike other authors [12
], however, in solid nodules we did find a negative influence of lowering the tube voltage to 80 kVp. This result was not statistically significant, which is probably explained by our small sample size. However, errors increased to 46%, and our impression, as shown in Figure 5
, is that dose must be considered more carefully for GGNs than for solid nodules, in which the contrast is much higher and thus less influenced by noise.
Small visible imperfections of the segmentation process were noted in the exclusion of vessels in the nodules in this phantom that had adjacent vessels. Inclusion of part of the vessel artificially raises the apparent mass of a nodule. In clinical practice, this situation would be even more complex because not only vessels adjacent to but also vessels running through a GGN have to be dealt with, and GGNs can have solid components. Further research into this problem is warranted.
The limitations of the study were mainly those inherent to use of a phantom, which removed any disturbance due to voluntary or involuntary movement of a subject. Nodules in the phantom were truly round, and this may have made it easier to adjust the measurement to an optimal result. Another limitation was that nodules did not contain vessels running through them that could influence the accuracy of the measurements. A third limitation was that even though the nodules in our phantom were surrounded by air and not by lung tissue, the lowest-attenuation nodules differed by only 200 HU from their surroundings, This might explain why measurements in these nodules were less accurate than in the −630-HU nodules.