The role of morphologic computed tomography characteristics in the management of subsolid nodules
The goal of this project is to gain more insight into the morphologic CT characteristics of subsolid nodules in a screening population. In addition to descriptive characteristics, mathematic descriptors of e.g. size will be calculated using computer assisted detection (CAD) techniques. This will allow us to study possible predictors based on morphologic characteristics that might discriminate (pre)malignant nodules from benign diseases, and predict progression into invasive cancer. Furthermore, predictors for growth and persistence may also be established.
1. Godoy MCB, Naidich DP. Subsolid pulmonary nodules and the spectrum of peripheral adenocarcinomas of the lung: recommended interim guidelines for assessment and management. Radiology. 2009 Dec; 253(3):606-22.
2. Henschke CI, Yankelevitz DF, Mirtcheva R, McGuinness G, McCauley D, Miettinen OS; ELCAP Group. CT screening for lung cancer: frequency and significance of part-solid and nonsolid nodules. AJR Am Roentgenol. 2002 May;178(5):1053-7.
- Establish predictors based on morphologic CT characteristics (descriptive characteristics and mathematic descriptors using CAD techniques) for transient versus persistent, growth and outcome of subsolid lesions in the NLST.
- Using the morphological predictors models will be developed for subsolid nodules detected at baseline and follow-up scans to predict vanishing nodules, nodule persistence and nodule growth. Using the same morphological predictors, a model to predict outcome endpoints will be developed.
Deni Aberle, MD. University of California Los Angeles
Cornelia Schaefer-Prokop, MD, PhD. Radboud University Medical Center, the Netherlands
Mathias Prokop, MD, PhD. Radboud University Medical Center, the Netherlands
Kaman Chung, MD. Radboud University Medical Center, the Netherlands
Visual discrimination of screen-detected persistent from transient subsolid nodules: An observer study.
Chung K, Ciompi F, Scholten ET, Goo JM, Prokop M, Jacobs C, van Ginneken B, Schaefer-Prokop CM
PLoS ONE. 2018; Volume 13 (Issue 2): Pages e0191874 PUBMED
Lung-RADS Category 4X: Does It Improve Prediction of Malignancy in Subsolid Nodules?
Chung K, Jacobs C, Scholten ET, Goo JM, Prosch H, Sverzellati N, Ciompi F, Mets OM, Gerke PK, Prokop M, van Ginneken B, Schaefer-Prokop CM
Radiology. 2017; Volume 284 (Issue 1): Pages 264-271 PUBMED
Malignancy estimation of Lung-RADS criteria for subsolid nodules on CT: accuracy of low and high risk spectrum when using NLST nodules.
Chung K, Jacobs C, Scholten ET, Mets OM, Dekker I, Prokop M, van Ginneken B, Schaefer-Prokop CM
Eur Radiol. 2017 Nov; Volume 27 (Issue 11): Pages 4672-4679 PUBMED