Can megavoltage computed tomography reduce proton range uncertainties in treatment plans for patients with large metal implants?

Treatment planning calculations for proton therapy require an accurate knowledge of radiological path length, or range, to the distal edge of the target volume. In most cases, the range may be calculated with sufficient accuracy using kilovoltage (kV) computed tomography (CT) images. However, metal implants such as hip prostheses can cause severe streak artifacts that lead to large uncertainties in proton range. The purposes of this study were to quantify streak-related range errors and to determine if they could be avoided by using artifact-free megavoltage (MV) CT images in treatment planning. Proton treatment plans were prepared for a rigid, heterogeneous phantom and for a prostate cancer patient with a metal hip prosthesis using corrected and uncorrected kVCT images alone, uncorrected MVCT images and a combination of registered MVCT and kVCT images (the hybrid approach). Streak-induced range errors of 5-12 mm were present in the uncorrected kVCT-based patient plan. Correcting the streaks by manually assigning estimated true Hounsfield units improved the range accuracy. In a rigid heterogeneous phantom, the implant-related range uncertainty was estimated at <3 mm for both the corrected kVCT-based plan and the uncorrected MVCT-based plan. The hybrid planning approach yielded the best overall result. In this approach, the kVCT images provided good delineation of soft tissues due to high-contrast resolution, and the streak-free MVCT images provided smaller range uncertainties because they did not require artifact correction.

[1]  M. Moyers,et al.  Range, Range Modulation, and Field Radius Requirements for Proton Therapy of Prostate Cancer , 2003, Technology in cancer research & treatment.

[2]  Jikun Wei,et al.  Dosimetric impact of a CT metal artefact suppression algorithm for proton, electron and photon therapies , 2006, Physics in medicine and biology.

[3]  E. Pedroni,et al.  Dose calculation models for proton treatment planning using a dynamic beam delivery system: an attempt to include density heterogeneity effects in the analytical dose calculation. , 1999, Physics in medicine and biology.

[4]  William Preston,et al.  Proton therapy for prostate cancer: the initial Loma Linda University experience. , 2004, International journal of radiation oncology, biology, physics.

[5]  Patrick Dupont,et al.  An iterative maximum-likelihood polychromatic algorithm for CT , 2001, IEEE Transactions on Medical Imaging.

[6]  Lei Dong,et al.  Reducing metal artifacts in cone-beam CT images by preprocessing projection data. , 2007, International journal of radiation oncology, biology, physics.

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

[8]  V. Bashkirovb,et al.  Issues in Proton Computed Tomography , 2003 .

[9]  A Brahme,et al.  Radiotherapeutic computed tomography with scanned photon beams. , 1987, International journal of radiation oncology, biology, physics.

[10]  Mehran Yazdi,et al.  An adaptive approach to metal artifact reduction in helical computed tomography for radiation therapy treatment planning: experimental and clinical studies. , 2005, International journal of radiation oncology, biology, physics.

[11]  G H Olivera,et al.  The use of megavoltage CT (MVCT) images for dose recomputations , 2005, Physics in medicine and biology.

[12]  W Swindell,et al.  A 4-MV CT scanner for radiation therapy: the prototype system. , 1982, Medical physics.

[13]  D. McLean,et al.  Artefact reduction on CT images of fossils to allow 3D visualisation , 2001 .

[14]  M W Vannier,et al.  Fast iterative algorithm for metal artifact reduction in X-ray CT. , 2000, Academic radiology.

[15]  W Swindell,et al.  Computed tomography with a linear accelerator with radiotherapy applications. , 1983, Medical physics.

[16]  Radhe Mohan,et al.  Monte Carlo simulations for configuring and testing an analytical proton dose-calculation algorithm , 2007, Physics in medicine and biology.

[17]  James M. Balter,et al.  The Influence of Intrafraction Movement on Margins for Prostate Radiotherapy , 2005 .

[18]  John Styles,et al.  The University of Texas M.D. Anderson Cancer Center Proton Therapy Facility , 2003 .

[19]  David J. Hawkes,et al.  X-ray attenuation coefficients of elements and mixtures , 1981 .

[20]  Patrick A Kupelian,et al.  Influence of intrafraction motion on margins for prostate radiotherapy. , 2006, International journal of radiation oncology, biology, physics.

[21]  Martin Hoheisel,et al.  Review of medical imaging with emphasis on X-ray detectors , 2006 .

[22]  C Coolens,et al.  Calibration of CT Hounsfield units for radiotherapy treatment planning of patients with metallic hip prostheses: the use of the extended CT-scale. , 2003, Physics in medicine and biology.

[23]  Robert Jeraj,et al.  Radiation characteristics of helical tomotherapy. , 2004, Medical physics.

[24]  M Goitein,et al.  Compensating for heterogeneities in proton radiation therapy. , 1984, Physics in medicine and biology.

[25]  Joao Seco,et al.  Conversion of CT numbers into tissue parameters for Monte Carlo dose calculations: a multi-centre study , 2007, Physics in medicine and biology.

[26]  Daniel W. Miller,et al.  Methodologies and tools for proton beam design for lung tumors. , 2001, International journal of radiation oncology, biology, physics.

[27]  H. Sadrozinski,et al.  Issues in Proton Computed Tomography , 2003 .

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

[29]  Oliver Jäkel,et al.  The influence of metal artefacts on the range of ion beams , 2007, Physics in medicine and biology.