Effects of CT dose and nodule characteristics on lung-nodule detectability in a cohort of 90 national lung screening trial patients

Stefano Young; Pechin Lo; John M. Hoffman; H. J. Grace Kim; Matthew S. Brown; Michael F. McNitt-Gray

doi:10.1117/12.2217405

24 March 2016 Effects of CT dose and nodule characteristics on lung-nodule detectability in a cohort of 90 national lung screening trial patients

Stefano Young, Pechin Lo, John M. Hoffman, H. J. Grace Kim, Matthew S. Brown, Michael F. McNitt-Gray

Author Affiliations +

Proceedings Volume 9785, Medical Imaging 2016: Computer-Aided Diagnosis; 97850G (2016) https://doi.org/10.1117/12.2217405
Event: SPIE Medical Imaging, 2016, San Diego, California, United States

Abstract

Lung cancer screening CT is already performed at low dose. There are many techniques to reduce the dose even further, but it is not clear how such techniques will affect nodule detectability. In this work, we used an in-house CAD algorithm to evaluate detectability. 90348 patients and their raw CT data files were drawn from the National Lung Screening Trial (NLST) database. All scans were acquired at ~2 mGy CTDIvol with fixed tube current, 1 mm slice thickness, and B50 reconstruction kernel on a Sensation 64 scanner (Siemens Healthcare). We used the raw CT data to simulate two additional reduced-dose scans for each patient corresponding to 1 mGy (50%) and 0.5 mGy (25%). Radiologists’ findings on the NLST reader forms indicated 65 nodules in the cohort, which we subdivided based on LungRADS criteria. For larger category 4 nodules, median sensitivities were 100% at all three dose levels, and mean sensitivity decreased with dose. For smaller nodules meeting the category 2 or 3 criteria, the dose dependence was less obvious. Overall, mean patient-level sensitivity varied from 38.5% at 100% dose to 40.4% at 50% dose, a difference of only 1.9%. However, the false-positive rate quadrupled from 1 per case at 100% dose to 4 per case at 25% dose. Dose reduction affected lung-nodule detectability differently depending on the LungRADS category, and the false-positive rate was very sensitive at sub-screening dose levels. Thus, care should be taken to adapt CAD for the very challenging noise characteristics of screening.

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Stefano Young, Pechin Lo, John M. Hoffman, H. J. Grace Kim, Matthew S. Brown, and Michael F. McNitt-Gray "Effects of CT dose and nodule characteristics on lung-nodule detectability in a cohort of 90 national lung screening trial patients", Proc. SPIE 9785, Medical Imaging 2016: Computer-Aided Diagnosis, 97850G (24 March 2016); https://doi.org/10.1117/12.2217405

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KEYWORDS

Computer aided design

Lung

Computer aided diagnosis and therapy

Scanners

Computed tomography

Image segmentation

Lung cancer

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