Performance of segmentation software on large longitudinal database of pulmonary nodules in the Danish Lung Cancer Screening Trial (DLCST)
Introduction and aim Growth measurements of pulmonary nodules are subject to great interest due to the risk of malignancy. We examined the reproducibility of lung nodule volumetric software that offers two different volumetric algorithms. Materials and methods In the Danish Lung Cancer Screening trial, 2,052 participant with high risk of lung cancer where randomized to five annual multislice low-dose scans. All scans were double-read by two experienced chest radiologists and the location and size of nodules were registered. Subsequently the nodules were linked chronologically (same nodule in different scans) and independently reviewed by two readers using volumetric software. The software offers readers two different analysing algorithms, “solid nodule algorithm” and “partsolid/nonsolid algorithm”. We compared the inter-observer variability regarding use of algorithm and rate of success. Results 1442 nodules were measured 5988 times. The readers reviewed the segmentations visually and were able to correctly segment and measure 94% and 97% of the nodules, respectively. In 90% of these cases, the readers chose the same algorithm. Conclusion Using this volumetric software on a large database with longitudinal data shows a high success rate and large agreement in choosing algorithm.