The role of computer-assisted radiographer reporting in lung cancer screening programmes

Helen Hall, Mamta Ruparel, Samantha L Quaife, Jennifer L Dickson, Carolyn Horst, Sophie Tisi, James Batty, Nicholas Woznitza, Asia Ahmed, Stephen Burke, Penny Shaw, May Jan Soo, Magali Taylor, Neal Navani, Angshu Bhowmik, David R Baldwin, Stephen W Duffy, Anand Devaraj, Arjun Nair, Sam M Janes, Helen Hall, Mamta Ruparel, Samantha L Quaife, Jennifer L Dickson, Carolyn Horst, Sophie Tisi, James Batty, Nicholas Woznitza, Asia Ahmed, Stephen Burke, Penny Shaw, May Jan Soo, Magali Taylor, Neal Navani, Angshu Bhowmik, David R Baldwin, Stephen W Duffy, Anand Devaraj, Arjun Nair, Sam M Janes

Abstract

Objectives: Successful lung cancer screening delivery requires sensitive, timely reporting of low-dose computed tomography (LDCT) scans, placing a demand on radiology resources. Trained non-radiologist readers and computer-assisted detection (CADe) software may offer strategies to optimise the use of radiology resources without loss of sensitivity. This report examines the accuracy of trained reporting radiographers using CADe support to report LDCT scans performed as part of the Lung Screen Uptake Trial (LSUT).

Methods: In this observational cohort study, two radiographers independently read all LDCT performed within LSUT and reported on the presence of clinically significant nodules and common incidental findings (IFs), including recommendations for management. Reports were compared against a 'reference standard' (RS) derived from nodules identified by study radiologists without CADe, plus consensus radiologist review of any additional nodules identified by the radiographers.

Results: A total of 716 scans were included, 158 of which had one or more clinically significant pulmonary nodules as per our RS. Radiographer sensitivity against the RS was 68-73.7%, with specificity of 92.1-92.7%. Sensitivity for detection of proven cancers diagnosed from the baseline scan was 83.3-100%. The spectrum of IFs exceeded what could reasonably be covered in radiographer training.

Conclusion: Our findings highlight the complexity of LDCT reporting requirements, including the limitations of CADe and the breadth of IFs. We are unable to recommend CADe-supported radiographers as a sole reader of LDCT scans, but propose potential avenues for further research including initial triage of abnormal LDCT or reporting of follow-up surveillance scans.

Key points: • Successful roll-out of mass screening programmes for lung cancer depends on timely, accurate CT scan reporting, placing a demand on existing radiology resources. • This observational cohort study examines the accuracy of trained radiographers using computer-assisted detection (CADe) software to report lung cancer screening CT scans, as a potential means of supporting reporting workflows in LCS programmes. • CADe-supported radiographers were less sensitive than radiologists at identifying clinically significant pulmonary nodules, but had a low false-positive rate and good sensitivity for detection of confirmed cancers.

Keywords: Early detection of cancer; Lung neoplasms; Mass screening; Radiology; Solitary pulmonary nodule.

Conflict of interest statement

The authors of this manuscript declare relationships with the following companies: SJ is on the advisory board for Optellum, and AN is on the advisory board for Aidence BV and Faculty Science Ltd. The authors do not perceive an academic conflict with this study.

© 2022. The Author(s).

Figures

Fig. 1
Fig. 1
Derivation of reference standard
Fig. 2
Fig. 2
Reporting process and reference standard

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