Template Creation for High-Resolution Computed Tomography Scans of the Lung in R Software

Publication date: Available online 13 December 2019Source: Academic RadiologyAuthor(s): Sarah M. Ryan, Brian Vestal, Lisa A. Maier, Nichole E. Carlson, John MuschelliRationale and ObjectivesA standard lung template could improve population-level analyses for computed tomography (CT) scans of the lung. We develop a fully automated preprocessing pipeline for image analysis of the lungs using updated methodologies and R software that results in the creation of a standard lung template. We apply this pipeline to CT scans from a sarcoidosis population, exploring the influence of registration on radiomic analyses.Materials and MethodsUsing 65 high-resolution CT scans from healthy adults, we create a standard lung template by segmenting the left and right lungs, nonlinearly registering lung masks to an initial template mask, and using an unbiased, iterative procedure to converge to a standard lung shape (Dice similarity coefficient ≥0.99). We compare three-dimensional radiomic features between control and sarcoidosis patients, before and after registration to a study-specific lung template.ResultsThe final lung template had a right lung volume of 2967 cm3 and left lung volume of 2623 cm3, with a median HU = −862. Registration significantly affected radiomic features, shifting the HU distribution to the left, decreasing variability, and increasing smoothness (p
Source: Academic Radiology - Category: Radiology Source Type: research

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