Technical Note: Long-term stability of Hounsfield unit calibration for cone-beam computed tomography.

PURPOSE The goal of this study was to investigate the stability of a phantom based Hounsfield unit (HU) calibration for cone beam CT (CBCT). METHODS Three consecutive scans of a large and a small phantom configuration were acquired and reconstructed with a uniform scatter correction method. The CBCT grey-values of the phantom inserts were measured and the three values of each insert averaged. The linear calibration curve was determined and its slope and intercept were evaluated. This procedure was performed for three CBCT scanners (Elekta Synergy) over a period of ten months with one, two, or four weeks between measurements. A dosimetric estimation of the HU fluctuations was made. RESULTS The CBCT HUs were stable over time with only small variations in slope and intercept resulting in HU differences on the water level, i.e. intercepts, of less than 7 HU (standard deviation). Therefore, the dosimetric influence of these HU differences was limited. The inter-scanner disparities (up to ~16 HU) were larger than the intra-scanner ones (up to ~7 HU). CONCLUSIONS Stable HUs were observed over a period of ten months. Due to the differences between the CBCT scanners, scanner specific calibration curves are necessary.

[1]  J. Sonke,et al.  Evaluating the impact of cone-beam computed tomography scatter mitigation strategies on radiotherapy dose calculation accuracy , 2019, Physics and imaging in radiation oncology.

[2]  Jan-Jakob Sonke,et al.  Optimal combination of anti‐scatter grids and software correction for CBCT imaging , 2017, Medical physics.

[3]  Jonas Andersson,et al.  Quality control in cone-beam computed tomography (CBCT) : EFOMP-ESTRO-IAEA protocol , 2017 .

[4]  C. Brink,et al.  Accuracy of dose calculation based on artefact corrected Cone Beam CT images of lung cancer patients , 2017 .

[5]  F. Verhaegen,et al.  Accuracy of dose calculations on kV cone beam CT images of lung cancer patients. , 2016, Medical physics.

[6]  Jan-Jakob Sonke,et al.  Clinical introduction of image lag correction for a cone beam CT system. , 2016, Medical physics.

[7]  Uwe Oelfke,et al.  Comparison of CT number calibration techniques for CBCT-based dose calculation , 2015, Strahlentherapie und Onkologie.

[8]  S. Tanabe,et al.  Long-term stability of the Hounsfield unit to electron density calibration curve in cone-beam computed tomography images for adaptive radiotherapy treatment planning , 2015, Journal of Radiotherapy in Practice.

[9]  Hao Yan,et al.  A practical cone-beam CT scatter correction method with optimized Monte Carlo simulations for image-guided radiation therapy , 2015, Physics in medicine and biology.

[10]  Jan-Jakob Sonke,et al.  Improved image quality of cone beam CT scans for radiotherapy image guidance using fiber-interspaced antiscatter grid. , 2014, Medical physics.

[11]  W. Yuh,et al.  Image guided radiation therapy (IGRT) technologies for radiation therapy localization and delivery. , 2013, International journal of radiation oncology, biology, physics.

[12]  Lei Zhu,et al.  Scatter correction for full-fan volumetric CT using a stationary beam blocker in a single full scan. , 2011, Medical physics.

[13]  Klaus Klingenbeck,et al.  Erratum: "A general framework and review of scatter correction methods in x-ray cone beam CT. Part 1: Scatter Compensation Approaches" [Med. Phys. 38(7), 4296-4311 (2011)]. , 2011, Medical physics.

[14]  J. Star-Lack,et al.  Improved scatter correction using adaptive scatter kernel superposition , 2010, Physics in medicine and biology.

[15]  Boyd McCurdy,et al.  Cone beam computerized tomography: the effect of calibration of the Hounsfield unit number to electron density on dose calculation accuracy for adaptive radiation therapy , 2009, Physics in medicine and biology.

[16]  V. Khoo,et al.  X-ray volumetric imaging in image-guided radiotherapy: the new standard in on-treatment imaging. , 2006, International journal of radiation oncology, biology, physics.

[17]  D. Yan,et al.  Computed tomography guided management of interfractional patient variation. , 2005, Seminars in radiation oncology.

[18]  J. Wong,et al.  Flat-panel cone-beam computed tomography for image-guided radiation therapy. , 2002, International journal of radiation oncology, biology, physics.

[19]  D. Jaffray,et al.  A ghost story: spatio-temporal response characteristics of an indirect-detection flat-panel imager. , 1999, Medical physics.