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

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 o...

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Autores principales: Hall, Helen, Ruparel, Mamta, Quaife, Samantha L., Dickson, Jennifer L., Horst, Carolyn, Tisi, Sophie, Batty, James, Woznitza, Nicholas, Ahmed, Asia, Burke, Stephen, Shaw, Penny, Soo, May Jan, Taylor, Magali, Navani, Neal, Bhowmik, Angshu, Baldwin, David R., Duffy, Stephen W., Devaraj, Anand, Nair, Arjun, Janes, Sam M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9474336/
https://www.ncbi.nlm.nih.gov/pubmed/35567604
http://dx.doi.org/10.1007/s00330-022-08824-1
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author Hall, Helen
Ruparel, Mamta
Quaife, Samantha L.
Dickson, Jennifer L.
Horst, Carolyn
Tisi, Sophie
Batty, James
Woznitza, Nicholas
Ahmed, Asia
Burke, Stephen
Shaw, Penny
Soo, May Jan
Taylor, Magali
Navani, Neal
Bhowmik, Angshu
Baldwin, David R.
Duffy, Stephen W.
Devaraj, Anand
Nair, Arjun
Janes, Sam M.
author_facet Hall, Helen
Ruparel, Mamta
Quaife, Samantha L.
Dickson, Jennifer L.
Horst, Carolyn
Tisi, Sophie
Batty, James
Woznitza, Nicholas
Ahmed, Asia
Burke, Stephen
Shaw, Penny
Soo, May Jan
Taylor, Magali
Navani, Neal
Bhowmik, Angshu
Baldwin, David R.
Duffy, Stephen W.
Devaraj, Anand
Nair, Arjun
Janes, Sam M.
author_sort Hall, Helen
collection PubMed
description 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00330-022-08824-1.
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spelling pubmed-94743362022-09-16 The role of computer-assisted radiographer reporting in lung cancer screening programmes Hall, Helen Ruparel, Mamta Quaife, Samantha L. Dickson, Jennifer L. Horst, Carolyn Tisi, Sophie Batty, James Woznitza, Nicholas Ahmed, Asia Burke, Stephen Shaw, Penny Soo, May Jan Taylor, Magali Navani, Neal Bhowmik, Angshu Baldwin, David R. Duffy, Stephen W. Devaraj, Anand Nair, Arjun Janes, Sam M. Eur Radiol Chest 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00330-022-08824-1. Springer Berlin Heidelberg 2022-05-14 2022 /pmc/articles/PMC9474336/ /pubmed/35567604 http://dx.doi.org/10.1007/s00330-022-08824-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Chest
Hall, Helen
Ruparel, Mamta
Quaife, Samantha L.
Dickson, Jennifer L.
Horst, Carolyn
Tisi, Sophie
Batty, James
Woznitza, Nicholas
Ahmed, Asia
Burke, Stephen
Shaw, Penny
Soo, May Jan
Taylor, Magali
Navani, Neal
Bhowmik, Angshu
Baldwin, David R.
Duffy, Stephen W.
Devaraj, Anand
Nair, Arjun
Janes, Sam M.
The role of computer-assisted radiographer reporting in lung cancer screening programmes
title The role of computer-assisted radiographer reporting in lung cancer screening programmes
title_full The role of computer-assisted radiographer reporting in lung cancer screening programmes
title_fullStr The role of computer-assisted radiographer reporting in lung cancer screening programmes
title_full_unstemmed The role of computer-assisted radiographer reporting in lung cancer screening programmes
title_short The role of computer-assisted radiographer reporting in lung cancer screening programmes
title_sort role of computer-assisted radiographer reporting in lung cancer screening programmes
topic Chest
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9474336/
https://www.ncbi.nlm.nih.gov/pubmed/35567604
http://dx.doi.org/10.1007/s00330-022-08824-1
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