IJMPCERO  Vol.6 No.4 , November 2017
Method for Converting Cone-Beam CT Values into Hounsfield Units for Radiation Treatment Planning
Abstract: Cone-beam CT (CBCT) images acquired during radiation treatment can be used to recalculate the dose distribution as well as to confirm the treatment location. However, it is difficult to obtain the electron densities (EDs) necessary for dose calculation from CBCT images because of the effects of scatter contamination during CBCT image acquisition. This paper presents a mathematical method for converting the pixel values of CBCT images (CBCT values) into Hounsfield units (HUs) of radiation treatment simulation CT (simCT) images for use in radiation treatment planning. CBCT values are converted into HUs by matching the histograms of the CBCT values with the histograms of the HUs for each slice via linear scaling of the CBCT values. For prostate cancer and head-and-neck cancer patients, the EDs obtained from converted CBCT values (mCBCT values) show good agreement with the EDs obtained from HUs, within approximately 3.0%, and the dose calculated on the basis of CBCT images shows good agreement with the dose calculated on the basis of the simCT images, within approximately 2.0%. Because the CBCT values are converted for each slice, this conversion method can account for variation in the CBCT values associated with differences in body size, body shape, and inner tissue structures, as well as in longitudinally displaced positions from the isocenter, unlike conventional methods that use electron density phantoms. This method improves on conventional CBCT-ED conversion and shows considerable potential for improving the accuracy of radiation treatment planning using CBCT images.
Cite this paper: Abe, T. , Tateoka, K. , Saito, Y. , Nakazawa, T. , Yano, M. , Nakata, K. , Someya, M. , Hori, M. and Sakata, K. (2017) Method for Converting Cone-Beam CT Values into Hounsfield Units for Radiation Treatment Planning. International Journal of Medical Physics, Clinical Engineering and Radiation Oncology, 6, 361-375. doi: 10.4236/ijmpcero.2017.64032.

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