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Minimal point volumetric outlining and editing for radiotherapy treatment planning

Published online by Cambridge University Press:  01 September 2017

Pete Bridge ,
Andrew Fielding ,
Pamela Rowntree  and
Andrew Pullar
Pete Bridge*
Affiliation:
Science and Engineering Faculty, Queensland University of Technology, Brisbane, QLD, Australia
Andrew Fielding
Affiliation:
Science and Engineering Faculty, Queensland University of Technology, Brisbane, QLD, Australia
Pamela Rowntree
Affiliation:
School of Clinical Sciences, Queensland University of Technology, Brisbane, QLD, Australia
Andrew Pullar
Affiliation:
Radiation Oncology Mater Centre, Brisbane, QLD, Australia
*
Correspondence to: Pete Bridge, Queensland University of Technology, 2 George Street, Brisbane, QLD 4000, Australia. Tel: +6173 138 2273. E-mail: peter.bridge@connect.qut.edu.au
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Abstract

Purpose

A novel radiotherapy outlining application uses a small number of user-assigned points across orthogonal planes to generate a mesh which is then edited across multiple slices using innovative three-dimensional (3D) sculpting tools. This paper presents the results of a bladder outlining study that compared times and volumes for the new tool with those of a conventional manual outlining tool.

Materials and methods

All students undertaking their first University radiotherapy planning module were invited to participate. Following training, they performed a timed outlining of the same male bladder dataset and provided feedback on their preferred method.

Results

Comparison of times from the resulting ten datasets demonstrated that the 3D segmentation tool was significantly faster than conventional software with a mean time of 11·9 minutes compared with 19·2 minutes (p=0·03). The users expressed a preference for the new tool (eight users) over the conventional outlining software (two users).

Conclusions

A minimal point 3D volumetric manual outlining tool utilising orthogonal computed tomography planes demonstrated significant time saving for bladder segmentation compared with axial-based outlining within a group of novice outliners. Future work aims to establish the role of the 3D multi-slice sculpting tools in editing of auto-segmentation derived contour sets.

Keywords

outliningradiotherapysegmentationspeedtreatment planning
Type
Original Articles
Information
Journal of Radiotherapy in Practice , Volume 16 , Issue 3 , September 2017 , pp. 280 - 285
Copyright
© Cambridge University Press 2017 

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References

1. Chen, G T. Dose volume histograms in treatment planning. Int J Radiat Oncol Biol Phys 1988; 14 (6): 1319–1320.CrossRefGoogle ScholarPubMed
2. Marks, L B, Yorke, E D, Jackson, A et al. Introductory paper: use of normal tissue complication probability models in the clinic. Int J Radiat Oncol Biol Phys 2010; 76 (suppl): S10–S19.Google Scholar
3. ICRU. Prescribing, recording, and reporting photon-beam intensity-modulated radiation therapy (IMRT). J Int Comm Radiat Units 2010; 10: 1–106.Google Scholar
4. Anders, L C, Stieler, F, Siebenlist, K, Schäfer, J, Lohr, F, Wenz, F. Performance of an atlas-based autosegmentation software for delineation of target volumes for radiotherapy of breast and anorectal cancer. Radiother Oncol 2012; 102 (1): 68–73.Google Scholar
5. Conson, M, Cella, L, Pacelli, R et al. Autosegmentation: automated delineation of brain structures in patients undergoing radiotherapy for primary brain tumors: from atlas to dose–volume histograms. Radiother Oncol 2014; 112 (3): 326–331.CrossRefGoogle Scholar
6. Simmat, I, Georg, P, Georg, D, Birkfellner, W, Goldner, G, Stock, M. Assessment of accuracy and efficiency of atlas-based autosegmentation for prostate radiotherapy in a variety of clinical conditions. Strahlenther Onkol 2012; 188 (9): 807–815.CrossRefGoogle Scholar
7. Voet, P W J, Dirkx, M L P, Teguh, D N, Hoogeman, M S, Levendag, P C, Heijmen, B J M. Does atlas-based autosegmentation of neck levels require subsequent manual contour editing to avoid risk of severe target underdosage? A dosimetric analysis. Radiother Oncol 2011; 98 (3): 373–377.Google Scholar
8. Sharp, G, Fritscher, K D, Pekar, V et al. Vision 20/20: perspectives on automated image segmentation for radiotherapy. Med Phys 2014; 41 (5): 050902.Google Scholar
9. Whitfield, G A, Price, P, Price, G J, Moore, C J. Automated delineation of radiotherapy volumes: are we going in the right direction? Br J Radiol 2013; 86 (1021): 20110718.CrossRefGoogle ScholarPubMed
10. McBain, C A, Moore, C J, Green, M M L et al. Early clinical evaluation of a novel three-dimensional structure delineation software tool (SCULPTER) for radiotherapy treatment planning. Br J Radiol 2008; 81 (968): 643–652.CrossRefGoogle ScholarPubMed
11. Bridge, P, Fielding, A, Pullar, A, Rowntree, P. Development and initial evaluation of a novel 3D volumetric outlining system. J Radiother Pract 2015; 15 (1): 38–44.CrossRefGoogle Scholar
12. Bridge, P, Fielding, A, Rowntree, P, Pullar, A. Qualitative evaluation of a novel 3D volumetric radiotherapy segmentation tool. J Med Imag Radiat Sci 2016; 48 (2): 178–183.Google Scholar
13. Zou, K, Warfield, S, Bharatha, A et al. Statistical validation of image segmentation quality based on a spatial overlap index: scientific reports. Acad Radiol 2004; 11: 178–189.Google Scholar
14. Foucault, M, Gordon, C. Power/Knowledge: Selected Interviews and Other Writings. New York: Pantheon Books, 1980: 1972–1977.Google Scholar
15. Giezen, M, Kouwenhoven, E, Scholten, A N et al. Clinical investigation: magnetic resonance imaging-versus computed tomography-based target volume delineation of the glandular breast tissue (clinical target volume breast) in breast-conserving therapy: an exploratory study. Int J Radiat Oncol Biol Phys 2011; 81 (3): 804–811.CrossRefGoogle Scholar