TY - JOUR T1 - Risk index: A rational alternative to effective dose for procedure optimization JF - Journal of Nuclear Medicine JO - J Nucl Med SP - 1583 LP - 1583 VL - 62 IS - supplement 1 AU - Juan Ocampo Ramos AU - Lukas Carter AU - Adam Kesner AU - Pat Zanzonico AU - Justin Brown AU - Wesley Bolch Y1 - 2021/05/01 UR - http://jnm.snmjournals.org/content/62/supplement_1/1583.abstract N2 - 1583Introduction: The aim of this work is to show the use of the Risk Index (RI) as a more clinically relevant alternative to the effective dose (ED) with potential application in risk communication and optimization processes for the use of radiopharmaceuticals in diagnostic nuclear medicine. This quantity is recently established in the literature [1, 2] and can be easily evaluated in a spreadsheet as a tool to refine risk optimization metrics. The RI expresses the detriment in terms of the projected age- and risk-specific increased cancer incidence risk and has potential use in optimizing administered activities (AA). RIs were calculated for several illustrative cases. Materials/Method: The RI is defined as a ratio of the estimated incidence risk of cancer from specific radiation exposure, relative to the estimated natural risk of cancer. For implementation we estimated the lifetime attributable risk of cancer (LAR) from a given exposure using the National Cancer Institute’s Radiation Risk Assessment Tool (RadRAT) [3]. The baseline risk, given as the natural incidence of cancer in a population in the absence of radiation exposure, was derived from the SEER database of the National Cancer Institute as defined in RadRAT. All risks were extracted on an age and sex basis. In this work, examples of RI were calculated for two sample PET and SPECT imaging radiopharmaceuticals, using the ICRP 128 biokinetics data [4] and the dose coefficients from the reference voxel phantoms available in the new MIRDcalc software.Results: The RI for our diagnostic radiopharmaceuticals set ranged from between 1.0% and 0.07% for 18F-FDG studies and between 0.26% to 0.03% for 99mTc-MDP studies for both females/males and across the newborn to 80 years range. Full results of the risk index are provided in Tables 1 and 2. This data provides a glimpse into and initial introduction of typical RI values for diagnostic nuclear medicine, but they are by no means specific to any individual patient. The RI can be used as a new way to optimize the risk associated with radiation doses and is an alternative of the effective dose. For example, from our tabulated RI results, one can see that there is “space” to optimize the AA for the 1-year and 15-year individuals and specially for female patients. The use of specific organs/tissues at risk and for patients of a particular age and sex, risk values yield a more refined and clinically appropriate metric for risk/benefit optimization. Conclusions: Clearly, the effective dose has been used as a risk indicator and as a value for comparison in medical applications, even though this application for medical imaging was never the original intended use of this radiation protection quantity. However, the risk determination process can be adjusted using newer data, more specific modeling (age and sex), and presented in more clinically relevant terms. The scope of this work was limited to two tracers and represents an initial investigation of the RI value in nuclear medicine. The work can be further developed to include a large library of reference risk indexes. Even if the RI would suggest that the patient has a specific percentage value of higher chance of a radiation induced cancer when compared to their natural probability of cancer incidence, RI values should not be used at a risk assessment for individual patients. Instead, the RI can be used as a tool for optimization of the AA, and it is a promising rational quantity that could be used for justification and risk communication in the medical field. The development of the RI value likely addresses these opportunities for improvement.Keywords: risk assessment, effective dose, LAR, optimization, risk index. Acknowledgements: We gratefully acknowledge funding from the NIH/NCI Cancer Center Support Grant P30 CA008748 and NIH U01 EB028234. ER -