Fig 1.
A custom GUI allowed thoracic radiologists to evaluate nodules.
For the purposes of this study, only the solid components were considered. Semi-automated segmentations made by radiologists for a given nodule are shown. Top left in Yellow: Radiologist 1; top right in Red: Radiologist 2; bottom left: non-segmented original; bottom right in Orange, both radiologist’s segmentations combined.
Fig 2.
Segmentation procedure for lung nodules.
Each nodule was segmented from 100%-dose/FBP B50f-kernel images reconstructed at 8 different slice thicknesses. The resulting 8 thickness-specific ROI stacks were then applied to the corresponding images reconstructed at 4 different dose levels and 10 different kernels at stable slice thickness.
Fig 3.
Methodologies used during volumetric assessment of lung nodules.
The following represent expert segmentation of lung nodules: (a) Reference radiologist-segmented ROI stacks obtained using 100%-dose level, a FBP B50f kernel, and 1-mm slice thickness. Nodules are sorted by their average volumes and numbered 1 to 23. (b) Calculated volumes for each nodule using 8 reference ROIs depending on slice thicknesses (colors indicate the corresponding nodules shown on the left). (c) Normalized volumes of nodules obtained using their average volumes.
Table 1.
Extracted features.
Fig 4.
Reconstruction-condition compatibility map based on extracted features and patients.
Intersections of conditions are highlighted (Red: incompatible, Green: compatible) based on their compatibility ratios calculated using t-test. Diagonal shows 100% compatibility which satisfies all comparisons (28x23). Changing reconstruction parameters (thickness/dose/kernel-sharpness) decreases the compatibility. In order to obtain higher compatibility, changes to the reconstruction parameters should be applied carefully. For example if thickness needs to be switched from 2 mm to 0.75 mm, softer kernels and/or higher dose levels are needed as seen from the intersection of two thicknesses. Data are available in S1 Data.
Fig 5.
Normalized volumetric measurements and trend lines based on slice thickness.
Fig 6.
P values for compatibility analysis of slice thicknesses based on volumetric measurements.
Higher P value indicates higher compatibility. Intersection of compatible thicknesses with P values higher than 0.05 are highlighted with green; P values lower than 0.05 (highlighted with orange to red) indicate incompatible slice thicknesses.
Fig 7.
Percentage compatibilities of features based on dose, kernel, and thickness changes.
Fig 8.
Percentage of compatible texture features in different kernel pairs while keeping slice thickness and dose levels fixed for all 23 patients and 28 features.
For example, by changing the kernel from I31f to I26f, on average, 54.7% of the 28 texture features will be statistically the same (compatible) in our patient population under the same slice thickness and dose level configurations (32 different conditions).
Fig 9.
Percentage of compatible texture features in different slice thickness pairs while keeping kernel and dose levels fixed for all 23 patients.
Fig 10.
Percentage of compatible texture features in different dose level pairs while keeping kernel and slice thickness fixed for all 23 patients.