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

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Title: The role of computer-assisted radiographer reporting in lung cancer screening programmes.
Authors: Hall, Helen1, Ruparel, Mamta1, Quaife, Samantha L.2, Dickson, Jennifer L.1, Horst, Carolyn1, Tisi, Sophie1, Batty, James3, Woznitza, Nicholas4, Ahmed, Asia3, Burke, Stephen4, Shaw, Penny3, Soo, May Jan4, Taylor, Magali3, Navani, Neal1,5, Bhowmik, Angshu6, Baldwin, David R.7, Duffy, Stephen W.2, Devaraj, Anand8,9, Nair, Arjun3, Janes, Sam M.1,5 s.janes@ucl.ac.uk
Source: European Radiology. Oct2022, Vol. 32 Issue 10, p6891-6899. 9p. 2 Diagrams, 2 Charts.
Subjects: Computers, Lung tumors, Early detection of cancer, Research funding, Computed tomography, Sensitivity & specificity (Statistics)
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. [ABSTRACT FROM AUTHOR]
Copyright of European Radiology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: The role of computer-assisted radiographer reporting in lung cancer screening programmes.
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  Data: <searchLink fieldCode="JN" term="%22European+Radiology%22">European Radiology</searchLink>. Oct2022, Vol. 32 Issue 10, p6891-6899. 9p. 2 Diagrams, 2 Charts.
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  Data: <searchLink fieldCode="DE" term="%22Computers%22">Computers</searchLink><br /><searchLink fieldCode="DE" term="%22Lung+tumors%22">Lung tumors</searchLink><br /><searchLink fieldCode="DE" term="%22Early+detection+of+cancer%22">Early detection of cancer</searchLink><br /><searchLink fieldCode="DE" term="%22Research+funding%22">Research funding</searchLink><br /><searchLink fieldCode="DE" term="%22Computed+tomography%22">Computed tomography</searchLink><br /><searchLink fieldCode="DE" term="%22Sensitivity+%26+specificity+%28Statistics%29%22">Sensitivity & specificity (Statistics)</searchLink>
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  Data: <bold>Objectives: </bold>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).<bold>Methods: </bold>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.<bold>Results: </bold>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.<bold>Conclusion: </bold>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.<bold>Key Points: </bold>• 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. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of European Radiology is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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