Risk modelling of time to lung cancer diagnosis
Principal Investigator
Name
Anton Schreuder
Degrees
M.D.
Institution
Radboudumc
Position Title
Ph.D. student
About this CDAS Project
Study
NLST
(Learn more about this study)
Project ID
NLST-267
Initial CDAS Request Approval
Dec 27, 2016
Title
Risk modelling of time to lung cancer diagnosis
Summary
This project aims to predict the lung cancer risk and estimate the time frame in which the cancer diagnosis is made following a scan. The model will be developed based on participant information and baseline and followup scan outcomes.
Aims
- To determine the best predictors of developing lung cancer after a screening round based on participant characteristics and CT scan morphology.
- To observe the effect of different screening intervals.
- To ultimately predict the time frame a screening participant is likely to develop cancer in, should they develop it at all.
Collaborators
Bram van Ginneken, Diagnostic Image Analysis Group, Radboud University Medical Center Nijmegen, Netherlands
Colin Jacobs, Diagnostic Image Analysis Group, Radboud University Medical Center Nijmegen, Netherlands
Cornelia Schaefer-Prokop, MD, PhD. Radboud University Medical Center, the Netherlands
Mathias Prokop, MD, PhD. Radboud University Medical Center, the Netherlands
Max Argus, MSc. Radboud University Medical Center, the Netherlands
Anton Schreuder, MD. Radboud University Medical Center, the Netherlands
Related Publications
-
Lung cancer risk to personalise annual and biennial follow-up computed tomography screening.
Schreuder A, Schaefer-Prokop CM, Scholten ET, Jacobs C, Prokop M, van Ginneken B
Thorax. 2018 Mar PUBMED