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Published in: Radiation Oncology 1/2017

Open Access 01-12-2017 | Research

An investigation into the range dependence of target delineation strategies for stereotactic lung radiotherapy

Authors: Dennis J. Mohatt, John M. Keim, Mathew C. Greene, Ami Patel-Yadav, Jorge A. Gomez, Harish K. Malhotra

Published in: Radiation Oncology | Issue 1/2017

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Abstract

Background

The “gold standard” approach for defining an internal target volume (ITV) is using 10 gross tumor volume (GTV) phases delineated over the course of one respiratory cycle. However, different sites have adopted several alternative techniques which compress all temporal information into one CT image set to optimize work flow efficiency. The purpose of this study is to evaluate alternative target segmentation strategies with respect to the 10 phase gold standard.

Methods

A Quasar respiratory motion phantom was employed to simulate lung tumor movement. Utilizing 4DCT imaging, a gold standard ITV was created by merging 10 GTV time resolved image sets. Four alternative planed ITV’s were compared using free breathing (FB), average intensity projection (AIP), maximum image projection (MIP), and an augmented FB (FB-Aug) set where the ITV included structures from FB plus max-inhale/exhale image sets. Statistical analysis was performed using the Dice similarity coefficient (DSC). Seventeen patients previously treated for lung SBRT were also included in this retroactive study.

Results

PTV’s derived from the FB image set are the least comparable with the 10 phase benchmark (DSC = 0.740-0.408). For phantom target motion greater than 1 cm, FB and AIP ITV delineation exceeded the 10 phase benchmark by 2% or greater, whereas MIP target segmentation was found to be consistently within 2% agreement with the gold standard (DSC > 0.878). Clinically, however, the FB-Aug method proved to be most favorable for tumor movement up to 2 cm (DSC = 0.881 ± 0.056).

Conclusion

Our results indicate the range of tumor motion dictates the accuracy of the defined PTV with respect to the gold standard. When considering delineation efficiency relative to the 10 phase benchmark, the FB-Aug technique presents a potentially proficient and viable clinical alternative. Among various techniques used for image segmentation, a judicious balance between accuracy and efficiency is inherently required to account for tumor trajectory, range and rate of mobility.
Literature
1.
go back to reference Benedict SH, Yenice KM, Followill D, et al. Stereotactic body radiation therapy: the report of AAPM task group 101. Med Phys. 2010;37(8):4078–101.CrossRefPubMed Benedict SH, Yenice KM, Followill D, et al. Stereotactic body radiation therapy: the report of AAPM task group 101. Med Phys. 2010;37(8):4078–101.CrossRefPubMed
2.
go back to reference Keall PJ, Mageras GS, Balter JM, et al. The management of respiratory motion in radiation oncology report of AAPM task group 76a. Med Phys. 2006;33(10):3874–900.CrossRefPubMed Keall PJ, Mageras GS, Balter JM, et al. The management of respiratory motion in radiation oncology report of AAPM task group 76a. Med Phys. 2006;33(10):3874–900.CrossRefPubMed
3.
go back to reference Allen AM, Siracuse KM, Hayman JA, Balter JM. Evaluation of the influence of breathing on the movement and modeling of lung tumors. Int J of Radiat Oncol Biol Phys. 2004;58(4):1251–7.CrossRef Allen AM, Siracuse KM, Hayman JA, Balter JM. Evaluation of the influence of breathing on the movement and modeling of lung tumors. Int J of Radiat Oncol Biol Phys. 2004;58(4):1251–7.CrossRef
4.
go back to reference Rietzel E, Pan T, Chen GT. Four-dimensional computed tomography: image formation and clinical protocol. Med Phys. 2005;32(4):874–89.CrossRefPubMed Rietzel E, Pan T, Chen GT. Four-dimensional computed tomography: image formation and clinical protocol. Med Phys. 2005;32(4):874–89.CrossRefPubMed
5.
go back to reference Bradley JD, Nofal AN, El Naqa IM, et al. Comparison of helical, maximum intensity projection (MIP), and averaged intensity (AI) 4D CT imaging for stereotactic body radiation therapy (SBRT) planning in lung cancer. Radiat Oncol. 2006;81(3):264–8.CrossRef Bradley JD, Nofal AN, El Naqa IM, et al. Comparison of helical, maximum intensity projection (MIP), and averaged intensity (AI) 4D CT imaging for stereotactic body radiation therapy (SBRT) planning in lung cancer. Radiat Oncol. 2006;81(3):264–8.CrossRef
6.
go back to reference Zamora DA, Riegel AC, Sun X, et al. Thoracic target volume delineation using various maximum-intensity projection computed tomography image sets for radiotherapy treatment planning. Med Phys. 2010;37(11):5811–20.CrossRefPubMedPubMedCentral Zamora DA, Riegel AC, Sun X, et al. Thoracic target volume delineation using various maximum-intensity projection computed tomography image sets for radiotherapy treatment planning. Med Phys. 2010;37(11):5811–20.CrossRefPubMedPubMedCentral
7.
go back to reference Han K, Basran PS, Cheung P. Comparison of helical and average computed tomography for stereotactic body radiation treatment planning and normal tissue contouring in lung cancer. Clinic Oncol. 2010;22(10):862–7.CrossRef Han K, Basran PS, Cheung P. Comparison of helical and average computed tomography for stereotactic body radiation treatment planning and normal tissue contouring in lung cancer. Clinic Oncol. 2010;22(10):862–7.CrossRef
8.
go back to reference Speight R, Sykes J, Lindsay R, Franks K, Thwaites D. The evaluation of a deformable image registration segmentation technique for semi-automating internal target volume (ITV) production from 4DCT images of lung stereotactic body radiotherapy (SBRT) patients. Radiother Oncol. 2011;98(2):277–83.CrossRefPubMed Speight R, Sykes J, Lindsay R, Franks K, Thwaites D. The evaluation of a deformable image registration segmentation technique for semi-automating internal target volume (ITV) production from 4DCT images of lung stereotactic body radiotherapy (SBRT) patients. Radiother Oncol. 2011;98(2):277–83.CrossRefPubMed
9.
go back to reference Tian Y, Wang Z, Ge H, Zhang T, Cai J, Kelsey C, Yoo D, Yin FF. Dosimetric comparison of treatment plans based on free breathing, maximum, and average intensity projection CTs for lung cancer SBRT. Med Phys. 2012;39(5):2754–60.CrossRefPubMed Tian Y, Wang Z, Ge H, Zhang T, Cai J, Kelsey C, Yoo D, Yin FF. Dosimetric comparison of treatment plans based on free breathing, maximum, and average intensity projection CTs for lung cancer SBRT. Med Phys. 2012;39(5):2754–60.CrossRefPubMed
10.
go back to reference Radiation Therapy Oncology Group. RTOG 0915: a randomized phase ii study comparing 2 stereotactic body radiation therapy (SBRT) schedules for medically inoperable patients with stage I peripheral non-small cell lung cancer. Philadelphia: RTOG; 2009. Radiation Therapy Oncology Group. RTOG 0915: a randomized phase ii study comparing 2 stereotactic body radiation therapy (SBRT) schedules for medically inoperable patients with stage I peripheral non-small cell lung cancer. Philadelphia: RTOG; 2009.
11.
go back to reference Dice LR. Measures of the amount of ecologic association between species. Ecology. 1945;26(3):297–302.CrossRef Dice LR. Measures of the amount of ecologic association between species. Ecology. 1945;26(3):297–302.CrossRef
12.
go back to reference Zou KH, Warfield SK, Bharatha A, et al. Statistical validation of image segmentation quality based on a spatial overlap index 1: scientific reports. Academ Rad. 2004;11(2):178–89.CrossRef Zou KH, Warfield SK, Bharatha A, et al. Statistical validation of image segmentation quality based on a spatial overlap index 1: scientific reports. Academ Rad. 2004;11(2):178–89.CrossRef
13.
go back to reference Zijdenbos AP, Dawant BM, Margolin RA, Palmer AC. Morphometric analysis of white matter lesions in MR images: method and validation. IEEE Trans Med Imaging. 1994 Dec;13(4):716–24.CrossRefPubMed Zijdenbos AP, Dawant BM, Margolin RA, Palmer AC. Morphometric analysis of white matter lesions in MR images: method and validation. IEEE Trans Med Imaging. 1994 Dec;13(4):716–24.CrossRefPubMed
14.
go back to reference Park K, Huang L, Gagne H, Papiez L. Do maximum intensity projection images truly capture tumor motion? Int J of Radiat Oncol Biol Phys. 2009;73(2):618–25.CrossRef Park K, Huang L, Gagne H, Papiez L. Do maximum intensity projection images truly capture tumor motion? Int J of Radiat Oncol Biol Phys. 2009;73(2):618–25.CrossRef
15.
go back to reference Underberg RW, Lagerwaard FJ, Slotman BJ, Cuijpers JP, Senan S. Use of maximum intensity projections (MIP) for target volume generation in 4DCT scans for lung cancer. Int. J. of Radiat. Oncol. Biol. Phys. 2005;63(1):253–60.CrossRef Underberg RW, Lagerwaard FJ, Slotman BJ, Cuijpers JP, Senan S. Use of maximum intensity projections (MIP) for target volume generation in 4DCT scans for lung cancer. Int. J. of Radiat. Oncol. Biol. Phys. 2005;63(1):253–60.CrossRef
16.
go back to reference Muirhead R, McNee SG, Featherstone C, Moore K, Muscat S. Use of maximum intensity projections (MIPs) for target outlining in 4DCT radiotherapy planning. Journal of Thorac Oncol. 2008;3(12):1433–8.CrossRef Muirhead R, McNee SG, Featherstone C, Moore K, Muscat S. Use of maximum intensity projections (MIPs) for target outlining in 4DCT radiotherapy planning. Journal of Thorac Oncol. 2008;3(12):1433–8.CrossRef
Metadata
Title
An investigation into the range dependence of target delineation strategies for stereotactic lung radiotherapy
Authors
Dennis J. Mohatt
John M. Keim
Mathew C. Greene
Ami Patel-Yadav
Jorge A. Gomez
Harish K. Malhotra
Publication date
01-12-2017
Publisher
BioMed Central
Published in
Radiation Oncology / Issue 1/2017
Electronic ISSN: 1748-717X
DOI
https://doi.org/10.1186/s13014-017-0907-8

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