Multi-Slice Computed Tomography (MSCT) imaging of the lungs allow for detection and follow-up of very small
lesions including solid and ground glass nodules (GGNs). However relatively few computer-based methods have been
implemented for GGN segmentation. GGNs can be divided into pure GGNs and mixed GGNs, which contain both nonsolid
and solid components (SC). This latter category is especially of interest since some studies indicate a higher
likelihood of malignancy in GGNs with SC. Due to their characteristically slow growth rate, GGNs are typically
monitored with multiple follow-up scans, making measurement of the volume of both solid and non-solid component
especially desirable. We have developed an automated method to estimate the SC percentage within a segmented GGN.
First, the SC algorithm uses a novel method to segment out the solid structures, while excluding any vessels passing near
or through the nodule. A gradient distribution analysis around solid structures validates the presence or absence of SC.
We tested 50 GGNs, split between three groups: 15 GGNs with SC, 15 GGNs with a solid nodule added to simulate SC,
and 20 GGNs without SC. With three defined satisfaction levels for the segmentation (A: succeed, B: acceptable, C:
failed), the first group resulted in 60% with score A, 40% with score B, 0% with score C. The second group resulted in
66.7% with score A and 33.3% with score B. In testing the first and 3rd groups, the algorithm correctly detected SC in
all cases where it was present (sensitivity of 100%) and correctly determined absence of SC in 15 out of 20 cases