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.
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References
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
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
Yan D, Vicini F, Wong JW, et al. (1997) Adaptive radiation therapy. Phys Med Biol, 42(1):123–132.
Battista JJ, Rider WD, and Van Dyk J. (1980) Computed tomography for radiotherapy planning. Int J Radiat Oncol Biol Phys 6(1):99–107.
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.
Constantinou C, Harrington JC, and DeWerd LA (1991) An electron density calibration phantom for CT-based treatment planning computers. Med Phys 19:325–327.
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.
Glover GH (1982) Compton scatter effects in CT reconstructions. Med Phys, 9:860–867.
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.
Sharpe MB (2006) Imaging capabilities at delivery: KV-CT. in ASTRO Image Guided Radiation Therapy (IGRT) Symposium. 2006. Las Vegas, Nevada.
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© 2007 International Federation for Medical and Biological Engineering
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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
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DOI: https://doi.org/10.1007/978-3-540-36841-0_454
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