Semi-automated measurement of pulmonary nodule growth without explicit segmentation

Many nodule measurement methods rely on accurate segmentation of the nodule and may fail with complex nodule morphologies; often slight variations in segmentation result in large volume differences. A method, growth analysis from density (GAD), is presented that measures nodule growth without explicit segmentation through the application of a Gaussian weighting function to a region around the nodule, avoiding the drawbacks of segmentation-based methods. The resulting mean density is used as a surrogate for volume when computing growth. A zero-change nodule dataset was used to establish the variability of the method, followed by testing on datasets of stable, malignant, and complex nodules. There was no significant difference in percent volume change between the methods (p=0.55), and while GAD showed similar measurement variability and discriminative performance as a segmentation-based method (GAS), it was able to successfully measure growth on complex nodules where GAS failed.