Automatic quantification of calcifications in the coronary arteries and thoracic aorta on radiotherapy planning CT scans of Western and Asian breast cancer patients
Publication date
2018-06
Authors
Gernaat, Sofie A M
van Velzen, S. G.
Koh, Vicky
Emaus, Marleen J.
Isgum, Ivana
Lessmann, Nikolas
Moes, Shinta
Jacobson, Anouk
Tan, Poey W
Grobbee, Rick
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Advisors
Supervisors
Document Type
Article
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taverne
Abstract
PURPOSE: This study automatically quantified calcifications in coronary arteries (CAC) and thoracic aorta (TAC) on breast planning computed tomography (CT) scans and assessed its reproducibility compared to manual scoring. MATERIAL AND METHODS: Dutch (n = 1199) and Singaporean (n = 1090) breast cancer patients with radiotherapy planning CT scan were included. CAC and TAC were automatically scored using deep learning algorithm. CVD risk categories were based on Agatson CAC: 0, 1-10, 11-100, 101-400 and >400. Reliability between automatic and manual scoring was assessed in 120 randomly selected CT scans from each population, with linearly weighted kappa for CAC categories and intraclass correlation coefficient for TAC. RESULTS: Median age was higher in Dutch patients than Singaporean patients: 57 versus 52 years. CAC and TAC increased with age and were more present in Dutch patients than Singaporean patients: 24.2% versus 17.3% and 73.0% versus 62.2%, respectively. Reliability of CAC categories and TAC was excellent in the Netherlands (0.85 (95% confidence interval (CI) = 0.77-0.93) and 0.98 (95% CI = 0.96-0.98) respectively) and Singapore (0.90 (95% CI = 0.84-0.96) and 0.99 (95% CI = 0.98-0.99) respectively). CONCLUSIONS: CAC and TAC prevalence was considerable and increased with age. Deep learning software is a reliable method to automatically measure CAC and TAC on radiotherapy breast CT scans.
Keywords
Aged, Aorta, Thoracic/diagnostic imaging, Aortic Diseases/diagnostic imaging, Breast Neoplasms/diagnostic imaging, Calcinosis/diagnostic imaging, Coronary Artery Disease/diagnostic imaging, Female, Humans, Male, Middle Aged, Radionuclide Imaging, Radiotherapy Planning, Computer-Assisted/methods, Reproducibility of Results, Tomography, X-Ray Computed/methods, Breast cancer, Thoracic aorta calcifications, Coronary artery calcifications, Radiotherapy planning CT scans, Automatic scoring, Taverne, Research Support, Non-U.S. Gov't, Journal Article
Citation
Gernaat, S A M, van Velzen, S G M, Koh, V, Emaus, M J, Išgum, I, Lessmann, N, Moes, S, Jacobson, A, Tan, P W, Grobbee, D E, van den Bongard, D H J, Tang, J I & Verkooijen, H M 2018, 'Automatic quantification of calcifications in the coronary arteries and thoracic aorta on radiotherapy planning CT scans of Western and Asian breast cancer patients', Radiotherapy & Oncology, vol. 127, no. 3, pp. 487-492. https://doi.org/10.1016/j.radonc.2018.04.011