Dosimetric feasibility of cone-beam CT-based treatment planning compared to CT-based treatment planning.

PURPOSE Cone-beam computed tomography (CBCT) images are currently used for positioning verification. However, it is yet unknown whether CBCT could be used in dose calculation for replanning in adaptive radiation therapy. This study investigates the dosimetric feasibility of CBCT-based treatment planning. METHODS AND MATERIALS Hounsfield unit (HU) values and profiles of Catphan, homogeneous/inhomogeneous phantoms, and various tissue regions of patients in CBCT images were compared to those in CT. The dosimetric consequence of the HU variation was investigated by comparing CBCT-based treatment plans to conventional CT-based plans for both phantoms and patients. RESULTS The maximum HU difference between CBCT and CT of Catphan was 34 HU in the Teflon. The differences in other materials were less than 10 HU. The profiles for the homogeneous phantoms in CBCT displayed reduced HU values up to 150 HU in the peripheral regions compared to those in CT. The scatter and artifacts in CBCT became severe surrounding inhomogeneous tissues with reduced HU values up to 200 HU. The MU/cGy differences were less than 1% for most phantom cases. The isodose distributions between CBCT-based and CT-based plans agreed very well. However, the discrepancy was larger when CBCT was scanned without a bowtie filter than with bowtie filter. Also, up to 3% dosimetric error was observed in the plans for the inhomogeneous phantom. In the patient studies, the discrepancies of isodose lines between CT-based and CBCT-based plans, both 3D and IMRT, were less than 2 mm. Again, larger discrepancy occurred for the lung cancer patients. CONCLUSION This study demonstrated the feasibility of CBCT-based treatment planning. CBCT-based treatment plans were dosimetrically comparable to CT-based treatment plans. Dosimetric data in the inhomogeneous tissue regions should be carefully validated.

[1]  J. Ravenel.  The Essential Physics of Medical Imaging, 2nd ed. , 2003 .

[2]  Jiang Hsieh,et al.  Computed Tomography: Principles, Design, Artifacts, and Recent Advances, Fourth Edition , 2022 .

[3]  D. Jaffray,et al.  Cone-beam computed tomography with a flat-panel imager: magnitude and effects of x-ray scatter. , 2001, Medical physics.

[4]  R. Jeraj,et al.  Re-optimization in adaptive radiotherapy. , 2002, Physics in medicine and biology.

[5]  T. Holmes,et al.  Acceptance testing computerized radiation therapy treatment planning systems: direct utilization of CT scan data. , 1985, Medical physics.

[6]  M. Oldham,et al.  Cone-beam-CT guided radiation therapy: technical implementation. , 2005, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[7]  Fang-Fang Yin,et al.  Accuracy of inhomogeneity correction in photon radiotherapy from CT scans with different settings. , 2002, Physics in medicine and biology.

[8]  K. Langen,et al.  Organ motion and its management. , 2001, International journal of radiation oncology, biology, physics.

[9]  J. Bushberg.  The Essential Physics of Medical Imaging , 2001 .

[10]  L Cozzi,et al.  Dosimetric impact of computed tomography calibration on a commercial treatment planning system for external radiation therapy. , 1998, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[11]  T E Schultheiss,et al.  Ultrasound-based stereotactic guidance in prostate cancer--quantification of organ motion and set-up errors in external beam radiation therapy. , 2000, Computer aided surgery : official journal of the International Society for Computer Aided Surgery.

[12]  J J Battista,et al.  Computed tomography for radiotherapy planning. , 1980, International journal of radiation oncology, biology, physics.

[13]  N J Pelc,et al.  Nonlinear partial volume artifacts in x-ray computed tomography. , 1980, Medical physics.

[14]  L A DeWerd,et al.  An electron density calibration phantom for CT-based treatment planning computers. , 1992, Medical physics.

[15]  J. Fowler,et al.  Image guidance for precise conformal radiotherapy. , 2003, International journal of radiation oncology, biology, physics.

[16]  J. O’Sullivan,et al.  MO‐D‐I‐611‐07: The Influence of Bowtie Filters On X‐Ray CT Signals , 2005 .

[17]  He Wang,et al.  Use of deformed intensity distributions for on-line modification of image-guided IMRT to account for interfractional anatomic changes. , 2005, International journal of radiation oncology, biology, physics.

[18]  Masahiro Endo,et al.  Effect of scatter radiation on image noise in cone-beam CT , 2000, Medical Imaging.

[19]  E. Pedroni,et al.  The calibration of CT Hounsfield units for radiotherapy treatment planning. , 1996, Physics in medicine and biology.

[20]  D A Jaffray,et al.  A radiographic and tomographic imaging system integrated into a medical linear accelerator for localization of bone and soft-tissue targets. , 1999, International journal of radiation oncology, biology, physics.

[21]  D. Yan,et al.  Adaptive radiation therapy , 1997, Physics in medicine and biology.

[22]  M. Goitein.  Organ and tumor motion: an overview. , 2004, Seminars in radiation oncology.

[23]  J. Battista,et al.  Improved lung dose calculation using tissue-maximum ratios in the Batho correction. , 1984, Medical physics.

[24]  A. Boyer,et al.  Tissue Inhomogeneity Corrections for Megavoltage Photon Beams , 2004 .

[25]  Julia F. Barrett,et al.  Artifacts in CT: recognition and avoidance. , 2004, Radiographics : a review publication of the Radiological Society of North America, Inc.

[26]  B. Harrison.  Las Vegas, Nevada , 2002 .

[27]  Prakash Chinnaiyan,et al.  The impact of daily setup variations on head-and-neck intensity-modulated radiation therapy. , 2005, International journal of radiation oncology, biology, physics.