Assessment of heart-substructures auto-contouring accuracy for application in heart-sparing radiotherapy for lung cancer
Authors
Marchant, TomPrice, Gareth
McWilliam, Alan
Henderson, Edward
McSweeney, Dónal
van Herk, Mark
Banfill, Kathryn
Schmitt, M.
King, J.
Barker, C.
Faivre-Finn, Corinne
Affiliation
Christie Medical Physics & Engineering, The Christie NHS Foundation Trust, Manchester, M20 4BX, United Kingdom. Division of Cancer Sciences, The University of Manchester, Manchester, M13 9PL, United Kingdom. Radiotherapy Related Research, The Christie NHS Foundation Trust, Manchester, M20 4BX, United Kingdom. Department of Clinical Oncology, The Christie NHS Foundation Trust, Manchester, M20 4BX, United Kingdom.Issue Date
2024
Metadata
Show full item recordAbstract
OBJECTIVES: We validated an auto-contouring algorithm for heart substructures in lung cancer patients, aiming to establish its accuracy and reliability for radiotherapy (RT) planning. We focus on contouring an amalgamated set of subregions in the base of the heart considered to be a new organ at risk, the cardiac avoidance area (CAA), to enable maximum dose limit implementation in lung RT planning. METHODS: The study validates a deep-learning model specifically adapted for auto-contouring the CAA (which includes the right atrium, aortic valve root, and proximal segments of the left and right coronary arteries). Geometric, dosimetric, quantitative, and qualitative validation measures are reported. Comparison with manual contours, including assessment of interobserver variability, and robustness testing over 198 cases are also conducted. RESULTS: Geometric validation shows that auto-contouring performance lies within the expected range of manual observer variability despite being slightly poorer than the average of manual observers (mean surface distance for CAA of 1.6 vs 1.2 mm, dice similarity coefficient of 0.86 vs 0.88). Dosimetric validation demonstrates consistency between plans optimized using auto-contours and manual contours. Robustness testing confirms acceptable contours in all cases, with 80% rated as 'Good' and the remaining 20% as 'Useful.' CONCLUSIONS: The auto-contouring algorithm for heart substructures in lung cancer patients demonstrates acceptable and comparable performance to human observers. ADVANCES IN KNOWLEDGE: Accurate and reliable auto-contouring results for the CAA facilitate the implementation of a maximum dose limit to this region in lung RT planning, which has now been introduced in the routine setting at our institution.Citation
Marchant T, Price G, McWilliam A, Henderson E, McSweeney D, van Herk M, et al. Assessment of heart-substructures auto-contouring accuracy for application in heart-sparing radiotherapy for lung cancer. BJR open. 2024 Jan;6(1):tzae006. PubMed PMID: 38737623. Pubmed Central PMCID: PMC11087931. Epub 2024/05/13. eng.Journal
BJR OpenDOI
10.1093/bjro/tzae006PubMed ID
38737623Additional Links
https://dx.doi.org/10.1093/bjro/tzae006Type
ArticleLanguage
enae974a485f413a2113503eed53cd6c53
10.1093/bjro/tzae006