Show simple item record

dc.contributor.authorBaldwin, David R.
dc.date.accessioned2024-01-24T10:47:15Z
dc.date.available2024-01-24T10:47:15Z
dc.date.issued2022
dc.identifier.citationHall, H., Ruparel, M., Quaife, S.L., Dickson, J.L., Horst, C., Tisi, S., Batty, J., Woznitza, N., Ahmed, A., Burke, S., Shaw, P., Soo, M.J., Taylor, M., Navani, N., Bhowmik, A., Baldwin, D.R., Duffy, S.W., Devaraj, A., Nair, A. and Janes, S.M. (2022) 'The role of computer-assisted radiographer reporting in lung cancer screening programmes', European Radiology, 32(10), pp. 6891-6899. doi: 10.1007/s00330-022-08824-1 https://doi.org/10.1007/s00330-022-08824-1.en_US
dc.identifier.issn0938-7994
dc.identifier.issn1432-1084
dc.identifier.urihttp://hdl.handle.net/20.500.12904/18152
dc.description.abstractObjectives: 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). Method(s): 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. Result(s): 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(s): 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.Copyright © 2022, The Author(s).
dc.description.urihttps://doi.org/10.1007/s00330-022-08824-1en_US
dc.language.isoenen_US
dc.subjectLung cancer screeningen_US
dc.subjectRadiographersen_US
dc.subjectLung canceren_US
dc.subjectRadiographyen_US
dc.titleThe role of computer-assisted radiographer reporting in lung cancer screening programmesen_US
dc.typeArticleen_US
rioxxterms.funderDefault funderen_US
rioxxterms.identifier.projectDefault projecten_US
rioxxterms.versionVoRen_US
rioxxterms.versionofrecord10.1007/s00330-022-08824-1en_US
rioxxterms.typeJournal Article/Reviewen_US
refterms.dateFCD2024-01-24T10:47:16Z
refterms.versionFCDVoR
refterms.dateFOA2024-01-24T10:47:16Z
refterms.panelUnspecifieden_US
html.description.abstractObjectives: 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). Method(s): 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. Result(s): 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(s): 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.Copyright © 2022, The Author(s).en_US
rioxxterms.funder.project94a427429a5bcfef7dd04c33360d80cden_US


Files in this item

Thumbnail
Name:
The role of computer-assisted ...
Size:
650.5Kb
Format:
PDF

This item appears in the following Collection(s)

Show simple item record