Krishnan, Aravind R.; Kim, Michael E.; Gao, Chenyu; Rudravaram, Gaurav; Schwartz, Trent; Hucke, Andre T. S.; Remedios, Lucas W.; Li, Thomas Z.; Xu, Kaiwen; Sandler, Kim L.; Martinez, Yency Forero; Antic, Sanja; Maldonado, Fabien; Zuo, Lianrui; Landman, Bennett A. (2026).听.听PLOS ONE, 21(10), e0352075.听
Low-dose chest CT scans collected across multiple medical centers can differ in image resolution, reconstruction methods, and the amount of the body included in each scan, making quantitative measurements difficult to compare. We developed a standardization pipeline and applied it to more than 105,000 scans from 23,669 participants in the National Lung Screening Trial (NLST). The pipeline standardized image resolution, harmonized reconstruction differences across scanner manufacturers, and extended the field of view. Testing showed improved consistency in measurements of emphysema, skeletal muscle, and body fat across scans, including measurements taken over time. The approach reduced differences related to reconstruction methods and improved agreement with body measurements after field-of-view extension. This work provides a more standardized NLST imaging resource that could support reliable quantitative biomarker measurements and broader use of the dataset in lung cancer screening research.
Fig 1.听Acquisition heterogeneity in scans obtained from different vendors in the NLST.
The National Lung Screening Trial houses heterogeneous low-dose chest CT scans acquired from multiple institutions and vendors. Image variability arises from differences in through-plane spatial resolution, reconstruction kernels and semantic field-of-view. Reconstruction kernels influence the pixel noise and image texture in the underlying anatomy, creating differences in quantitative biomarker measures. In addition, scanner specific field-of-view configurations may truncate anatomy, affecting body composition assessment. These sources of heterogeneity motivate the need for a standardized dataset that enables consistent and reproducible quantitative image measures.