Low-Dose CT Iterative Reconstructions can Impact Lung Nodule Measurements and Type Classification

This paper investigates the impact of different reconstruction kernels on lung nodule measurements in lung cancer screening. The study uses AVIEW LCS software to measure the largest solid nodules in low-dose CT (LDCT) scans from a European lung cancer screening population. The measurements were performed using both B30f (non-iterative) and I30f (iterative) kernels to compare total volume and nodule type classification. The preliminary results show significant inconsistencies when using the iterative I30f kernel. In 90% of the cases, volumetric nodule measurements were not reproducible with the I30f kernel. Notably, in two instances, the use of the I30f kernel led to nodules being upgraded to a higher management category, necessitating a follow-up scan. Additionally, in seven cases, the kernel choice resulted in different nodule type classifications. The study concludes that the use of an iterative kernel can significantly affect volumetric nodule measurements, leading to variations in nodule management strategies and volume doubling time calculations. It recommends using the same reconstruction kernel for nodule measurements in both baseline and follow-up scans to standardize lung cancer screening practices.