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Developing a lung nodule management protocol specifically for cardiac CT: Methodology in the DISCHARGE trial.
Haase, Robert Dodd, Jonathan D Kauczor, Hans-Ulrich Kazerooni, Ella A Dewey, Marc
Haase, Robert
Dodd, Jonathan D
Kauczor, Hans-Ulrich
Kazerooni, Ella A
Dewey, Marc
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Date
2020-06-25
Date Submitted
Keywords
ACR, American College of Radiology
ADULT
Computed tomography angiography*
Incidental findings*
LDCT, low-dose computed tomography
Lung/diagnostic imaging
NLST, national lung cancer screening trial
eCRF, electronic clinical report form
ADULT
Computed tomography angiography*
Incidental findings*
LDCT, low-dose computed tomography
Lung/diagnostic imaging
NLST, national lung cancer screening trial
eCRF, electronic clinical report form
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Subject Mesh
Planned Date
Start Date
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Principal Investigators
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Abstract
Purpose: In this methodology paper we describe the development of a lung nodule management algorithm specifically for patients undergoing cardiac CT.
Methods: We modified the Lung-RADS algorithm specifically to manage lung nodules incidentally detected on cardiac CT (Lung-RADS for cardiac CT). We will evaluate the modified algorithm as part of the DISCHARGE trial (www.dischargetrial.eu) in which patients with suspected coronary artery disease are randomly assigned to cardiac CT or invasive coronary angiography across Europe at 16 sites involving 3546 patients. Patients will be followed for up to four years.
Results: The major adjustments to Lung-RADS specifically for cardiac CT relate to 1) incomplete coverage of the lungs by cardiac CT compared with chest CT, and when to order a completion chest CT versus a follow up chest CT, 2) cardiac CT findings will not trigger annual lung-cancer screening, and 3) a lower threshold of at least 10 mm for classifying new ground glass nodules as probably benign (category 3).
Conclusions: The DISCHARGE trial will assess a lung nodule management algorithm designed specifically for cardiac CT in patients with stable chest pain across Europe.
Language
en
Citation
ISSN
2352-0477
eISSN
ISBN
DOI
10.1016/j.ejro.2020.100235
PMID
32637465