Abstract
Gross tumor volume (GTV) delineation is central for radiotherapy planning. It provides the basis of the clinical target volume and, ultimately, the planning target volume which is used for dose optimization. Manual GTV delineations are prone to intra- and inter-observer variation and automatic segmentation methods also produce different results. There is no consensus on how to account for the contouring uncertainty, but has been suggested to incorporate it into the planning target volume (PTV) margin. Current recipes for the PTV margin are based on normal distribution assumptions and are more suitable for setup and execution errors. In this study we use the GTV delineations made by 6 experienced clinicians to create delineation-specific dose plans. These dose plans are then used to calculate theoretic tumor control probabilities (TCP) differences between delineations. The results show that current margin recipes are inadequate for maintaining the same TCP despite manual delineation variation. New methods to account for delineation variation should be developed.
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References
Global status report on noncommunicable diseases 2010, pp. 9–15. World Health Organization (2011)
ICRU, I. C. o. R. U. & Measurements. Prescribing, recording and reporting Intensity-Modulated Photon-Beam Therapy (IMRT). ICRU Report 10, 41–53 (2010)
Steenbakkers, R.J.H.M., et al.: Reduction of observer variation using matched CT-PET for lung cancer delineation: a three-dimensional analysis. International Journal of Radiation Oncology Biology Physics 64, 435–448 (2006)
Persson, G.F., et al.: Interobserver delineation variation in lung tumour stereotactic body radiotherapy. Br. J. Radiol. 85, e654–e660 (2012)
Van Herk, M.: Errors and margins in radiotherapy. Semin. Radiat. Oncol. 14, 52–64 (2004)
Webb, S., Nahum, A.E.: A model for calculating tumour control probability in radiotherapy including the effects of inhomogeneous distributions of dose and clonogenic cell density. Phys. Med. Biol. 38, 653–666 (1993)
Deacon, J., Peckham, M.J., Steel, G.G.: The radioresponsiveness of human tumours and the initial slope of the cell survival curve. Radiother. Oncol. 2, 317–323 (1984)
Drzymala, R.E., et al.: Dose-volume histograms. Int. J. Radiat. Oncol. Biol. Phys. 21, 71–78 (1991)
Van Herk, M., Remeijer, P., Lebesque, J.V.: Inclusion of geometric uncertainties in treatment plan evaluation. Int. J. Radiat. Oncol. Biol. Phys. 52, 1407–1422 (2002)
Persson, G.F.: Uncertainties in target definition for radiotherapy of peripheral lung tumours. Dan. Med. Bull. 58, B4314 (2011)
Daisne, J.-F., et al.: Tumor volume in pharyngolaryngeal squamous cell carcinoma: comparison at CT, MR imaging, and FDG PET and validation with surgical specimen. Radiology 233, 93–100 (2004)
Van Loon, J., et al.: Microscopic disease extension in three dimensions for non-small-cell lung cancer: development of a prediction model using pathologyvalidated positron emission tomography and computed tomography features. Int. J. Radiat. Oncol. Biol. Phys. 82, 448–456 (2012)
Galavis, P.E., Hollensen, C., Jallow, N., Paliwal, B., Jeraj, R.: Variability of textural features in FDG PET images due to different acquisition modes and reconstruction parameters. Acta. Oncol. 49, 1012–1016 (2010)
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Hollensen, C., Persson, G., Højgaard, L., Specht, L., Larsen, R. (2013). Differences in Radiotherapy Delivery and Outcome Due to Contouring Variation. In: Drechsler, K., et al. Clinical Image-Based Procedures. From Planning to Intervention. CLIP 2012. Lecture Notes in Computer Science, vol 7761. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38079-2_16
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DOI: https://doi.org/10.1007/978-3-642-38079-2_16
Publisher Name: Springer, Berlin, Heidelberg
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