Strategies for CT tissue segmentation for Monte Carlo calculations in nuclear medicine dosimetry

Purpose: CT images are used for patient specific Monte Carlo treatment planning in radionuclide therapy. The authors investigated the impact of tissue classification, CT image segmentation, and CT errors on Monte Carlo calculated absorbed dose estimates in nuclear medicine. Methods: CT errors as a function of patient size, CT reconstruction, and tube current modulation methods were assessed in a phantom experiment on a clinical CT system. The impact of tissue segmentation methods and CT number variations on EGSnrc Monte Carlo calculated absorbed dose distributions was assessed for Tc-99m and I-131 in the ICRP/ICRU male phantom and in a patient PET/CT-scanned with I-124 prior to radioiodine therapy. Results: CT number variations <20 HU were obtained for whole-body CT examinations at effective CT doses similar to 2 mSv. Monte Carlo calculated absorbed doses depended on both the number of media types and accurate calibration of the CT number-to-density conversion ramp. Tissue segmentation by a 13-tissue CT conversion ramp, calibrated by a stoichiometric method, resulted in low (<4%) dose errors in selected organs for both isotopes. Conclusions: A calibrated CT scanner specific conversion ramp is required for accurate patient specific dosimetry in nuclear medicine. Accurate dosimetry was obtained with a 13-tissue ramp that included five different bone types. (C) 2016 American Association of Physicists in Medicine.