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Establishing inherent uncertainty in the shifts determined by volumetric imaging

Published online by Cambridge University Press:  18 April 2017

Upendra Kumar Giri*
Affiliation:
Department of Radiation Oncology, Fortis Memorial Research Institute, Gurgaon-122002, Haryana, India Department of Physics, Institute of Applied Sciences & Humanities, GLA University, Mathura-281406, Uttar Pradesh, India
Anirudh Pradhan
Affiliation:
Department of Mathematics, Institute of Applied Sciences & Humanities, GLA University, Mathura-281406, Uttar Pradesh, India
*
Correspondence to: Upendra Kumar Giri, Department of Radiation Oncology, Fortis Memorial Research Institute, Opposite to Huda City Metro Station, Gurgaon, Haryana 122002, India. Tel: +9196 5077 8852. E-mail: upendragiribhu@gmail.com

Abstract

Objective

This study was conducted for establishing inherent uncertainty in the shift determination by X-ray volumetric imaging (XVI) and calculating margins due to this inherent uncertainty using van Herk formula.

Material and methods

The study was performed on the XVI which was cone-beam computed tomography integrated with the Elekta AxesseTM linear accelerator machine having six degree of freedom enabled HexaPOD couch. Penta-Guide phantom was used for inherent translational and rotational shift determination by repeated imaging. The process was repeated 20 times a day without moving the phantom for 30 consecutive working days. The measured shifts were used for margins calculation using van Herk formula.

Results

The mean standard deviations were calculated as 0·05, 0·05, 0·06 mm in the three translational (x, y and z) and 0·05°, 0·05°, 0·05° in the three rotational axes (about x, y, z). Paired sample t-test was performed between the mean values of translational shifts (x, y, z) and rotational shifts. The systematic errors were found to be 0·03, 0·04 and 0·03 mm while the random errors were 0·05, 0·06 and 0·06 mm in the lateral, cranio-caudal and anterio-posterior directions, respectively. For the rotational shifts, the systematic errors were 0·02, 0·03 and 0·03 and the random errors were 0·06, 0·05 and 0·05 in the pitch, roll and yaw directions, respectively.

Conclusion

Our study concluded that there was an inherent uncertainty associated with the XVI tools, on the basis of these six-dimensional shifts, margins were calculated and recorded as a baseline for the quality assurance (QA) programme for XVI imaging tools by checking its reproducibility once in a year or after any major maintenance in hardware or upgradation in software. Although the shift determined was of the order of submillimetre order, still that shift had great significance for the image quality control of the XVI tools. Every departments practicing quality radiotherapy with such imaging tools should establish their own baseline value of inherent shifts and margins during the commissioning and must use an important QA protocol for the tools.

Type
Original Articles
Copyright
© Cambridge University Press 2017 

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References

1. Sykes, J R, Lindsay, R, Dean, C J, Brettle, D S, Magee, D R, Thwaites, D I. Measurement of cone beam CT coincidence with megavoltage isocentre and image sharpness using the QUASAR™ Penta-Guide phantom. Phys Med Biol 2008; 53 (19): 5275.CrossRefGoogle ScholarPubMed
2. McBain, C A, Henry, A M, Sykes, J et al. X-ray volumetric imaging in image-guided radiotherapy: the new standard in on-treatment imaging. Int J Radiat Oncol Biol Phys 2006; 64 (2): 625634.CrossRefGoogle ScholarPubMed
3. Herman, M G, Balter, J M, Jaffray, D A et al. Clinical use of electronic portal imaging: report of AAPM Radiation therapy Committee Task Group 58. Med Phys 2001; 28 (5): 712737.CrossRefGoogle ScholarPubMed
4. Islam, M K, Purdie, T G, Norrlinger, B D et al. Patient dose from kilovoltage cone beam computed tomography imaging in radiation therapy. Med Phys 2006; 33 (6): 15731582.CrossRefGoogle ScholarPubMed
5. Hu, W, Ye, J, Wang, J, Ma, X, Zhang, Z. Use of kilovoltage X-ray volume imaging in patient dose calculation for head-and-neck and partial brain radiation therapy. Radiat Oncol 2010; 5 (1): 1.CrossRefGoogle ScholarPubMed
6. Hyer, D E, Serago, C F, Kim, S, Li, J G, Hintenlang, D E. An organ and effective dose study of XVI and OBI cone-beam CT systems. J Appl Clin Med Phys 2010; 11 (2): 181197.CrossRefGoogle ScholarPubMed
7. Ding, G X, Duggan, D M, Coffey, C W et al. A study on adaptive IMRT treatment planning using kV cone-beam CT. Radiother Oncol 2007; 85 (1): 116125.CrossRefGoogle Scholar
8. Bissonnette, J P, Moseley, D J, Jaffray, D A. A quality assurance program for image quality of cone-beam CT guidance in radiation therapy. Med Phys 2008; 35 (5): 18071815.CrossRefGoogle ScholarPubMed
9. Yoo, S, Kim, G Y, Hammoud, R et al. A quality assurance program for the on-board imager ®. Med Phys 2006; 33 (11): 44314447.CrossRefGoogle Scholar
10. Feldkamp, L A, Davis, L C, Kress, J W. Practical cone-beam algorithm. J Opt Soc Am A. 1984; 1 (6): 612619.CrossRefGoogle Scholar
11. Van Herk, M. Errors and margins in radiotherapy. Semin Radiat Oncol 2004; 14 (1): 5264.CrossRefGoogle ScholarPubMed
12. Nakahara, S, Tachibana, M, Watanabe, Y. One-year analysis of Elekta CBCT image quality using NPS and MTF. J Appl Clin Med Phys 2016; 17 (3): 211222.CrossRefGoogle ScholarPubMed
13. Thilmann, C, Nill, S, Tücking, T et al. Correction of patient positioning errors based on in-line cone beam CTs: clinical implementation and first experiences. Radiat Oncol 2006; 1 (1): 1.CrossRefGoogle ScholarPubMed
14. Yang, Y, Schreibmann, E, Li, T, Wang, C, Xing, L. Evaluation of on-board kV cone beam CT (CBCT)-based dose calculation part of this work was presented in 2006 annual meeting of American Association of Physicists in Medicine. Phys Med Biol 2007; 52 (3): 685.CrossRefGoogle Scholar
15. Yoo, S, Yin, F F. Dosimetric feasibility of cone-beam CT-based treatment planning compared to CT-based treatment planning. Int J Radiat Oncol Biol Phys 2006; 66 (5): 15531561.CrossRefGoogle ScholarPubMed
16. Hellman, S. Adverse effects of radiation. In: DeVita VT, Hellman S, Rosenberg SA (eds). Cancer: Principles and Practice of Oncology, 6th edition. Philadelphia, PA: Lippincott Williams and Wilkins, 2001: 281282.Google Scholar