Performance of an AI based CAD system in solid lung nodule detection on chest phantom radiographs compared to radiology residents and fellow radiologists.

ABSTRACT:

Background

Despite the decreasing relevance of chest radiography in lung cancer screening, chest radiography is still frequently applied to assess for lung nodules. The aim of the current study was to determine the accuracy of a commercial AI based CAD system for the detection of artificial lung nodules on chest radiograph phantoms and compare the performance to radiologists in training.

Methods

Sixty-one anthropomorphic lung phantoms were equipped with 140 randomly deployed artificial lung nodules (5, 8, 10, 12 mm). A random generator chose nodule size and distribution before a two-plane chest X-ray (CXR) of each phantom was performed. Seven blinded radiologists in training (2 fellows, 5 residents) with 2 to 5 years of experience in chest imaging read the CXRs on a PACS-wor

SUBMITTER: Peters AA 

PROVIDER: S-EPMC8182550 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature