Skip to main content

Part of the book series: IFMBE Proceedings ((IFMBE,volume 14))

Abstract

Purpose: This study investigates feasibility of CBCT-based treatment planning.

Methods and materials: Hounsfield unit (HU) values and profiles of phantoms and patients in CBCT images were compared to those in CT images. CBCT-based treatment plans for the phantoms and patients were compared to CT-based treatment plans dosimetrically.

Results: Mean HU values of different materials in CBCT images were very close to those in CT images for Catphan. CBCT images included scatters and artifacts. As a consequent, the HU profiles of the homogeneous phantoms in CBCT images showed inhomogeneous HU distribution and the peripheral areas near the edge of the field-of-view showed reduced HU values. The HU profiles of the inhomogeneous phantom showed reduced HU values throughout the phantom and more significantly around the peripheral areas and lungs than other areas. The HU values in patients were also reduced in most tissue regions in CBCT images. Most plans based on CBCT with a bowtie filter showed good agreement with those based on CT with less than 1 % of MU/cGy difference or 1 – 2 mm of isodose discrepancy. Large dosimetrical discrepancy occurred when CBCT was scanned without a bowtie filter, when a treatment beam passed through a significant amount of lung, and when a treatment beam was largely off-centered so as to pass through a body part imaged near the edge of the field-of-view. All IMRT plans based on CBCT and CT showed isodose distribution with very good agreement for patient cases except for one lung cancer patient.

Conclusion: This study proves feasibility of CBCT-based treatment planning by comparing HU values, MU/cGy and isodose distributions to the gold standard CT-based treatment planning. CBCT could be used for treatment planning purposes for most cases except for the cases with large discrepancy shown in this study.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 429.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 549.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Jaffray DA, Drake D, Moreau M et al. (1999) A radiographic and tomographic imaging system integrated into a medical linear accelerator for localization of bone and soft-tissue targets. Int J Radiat Oncol Biol Phys 45(3):773–789

    Article  Google Scholar 

  2. Mohan R, Zhang X, Wang H, et al. (2005) Use of deformed intensity distributions for on-line modification of image-guided IMRT to account for interfractional anatomic changes. Int J Radiat Oncol Biol Phys 61(4):1258–1266

    Article  Google Scholar 

  3. Yan D, Vicini F, Wong JW, et al. (1997) Adaptive radiation therapy. Phys Med Biol, 42(1):123–132.

    Article  Google Scholar 

  4. Battista JJ, Rider WD, and Van Dyk J. (1980) Computed tomography for radiotherapy planning. Int J Radiat Oncol Biol Phys 6(1):99–107.

    Google Scholar 

  5. Cozzi L, Fogliata A, Buffa F et al. (1998) Dosimetric impact of computed tomography calibration on a commercial treatment planning system for external radiation therapy. Radiother Oncol 48(3):335–338.

    Article  Google Scholar 

  6. Constantinou C, Harrington JC, and DeWerd LA (1991) An electron density calibration phantom for CT-based treatment planning computers. Med Phys 19:325–327.

    Article  Google Scholar 

  7. McCullough E and Holmes TW (1985) Acceptance testing computerized radiation therapy treatment planning systems: Direct utilization of CT scan data. Med Phys 12:237–242.

    Article  Google Scholar 

  8. Glover GH (1982) Compton scatter effects in CT reconstructions. Med Phys, 9:860–867.

    Article  Google Scholar 

  9. Siewerdsen JH and Jaffray DA (2001) Cone-beam computed tomography with a flat-panel imager: magnitude and effects of x-ray scatter. Med Phys 28:220–231.

    Article  Google Scholar 

  10. Sharpe MB (2006) Imaging capabilities at delivery: KV-CT. in ASTRO Image Guided Radiation Therapy (IGRT) Symposium. 2006. Las Vegas, Nevada.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sua Yoo Ph.D. .

Editor information

R. Magjarevic J. H. Nagel

Rights and permissions

Reprints and permissions

Copyright information

© 2007 International Federation for Medical and Biological Engineering

About this paper

Cite this paper

Yoo, S., Yin, F. (2007). Feasibility of Cone-beam CT based treatment planning. In: Magjarevic, R., Nagel, J.H. (eds) World Congress on Medical Physics and Biomedical Engineering 2006. IFMBE Proceedings, vol 14. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-36841-0_454

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-36841-0_454

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-36839-7

  • Online ISBN: 978-3-540-36841-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics