(Tuesday, 7/16/2019) 4:30 PM - 5:30 PM
Room: Exhibit Hall | Forum 1
Purpose: The present study combines Monte Carlo (MC) simulations and pediatric computational models to assess absorbed doses per organ in clinical practice. The goal is to create a dosimetry database which will help clinicians to predict absorbed doses during pediatric CT and Nuclear Medicine acquisitions.
Methods: The GATE MC toolkit was used for modeling a multislice¬¬ helical CT scanner and 5 different radiopharmaceuticals for proof-of-concept. All the procedures were validated against clinical and previously reported data. A series of pediatric computational models in the age range of 2–15 years old were used to simulate realistic i) helical chest, abdomen/pelvis and head CT protocols for 100/120 kVp, and ii) biodistributions of 5 radiopharmaceuticals (99mTc-MDP, 123I-mIBG, 131I-MIBG, 131I-NaI, and 153Sm-EDTMP). Absorbed doses per organ were calculated for each case. Specific characteristics of each phantom were collected creating a dataset that is used for matching each patient to the most similar phantom.
Results: All the simulated models were validated against experimental and published data with statistical differences being lower than ~11% for all cases. The normalized-to-CTDIvol absorbed doses (mGy/mGy) for selected organs were estimated for each protocol for the CT, while the absorbed doses/organ were calculated based on the selected S-values of the MIRD Schema and the administered activity. The software matches the characteristics (age, gender, weight, height, and effective chest diameter) of the patient to the closest pediatric model of the database to extract the absorbed dose.
Conclusion: Anatomical differences, in children in similar age and/or weight, result in differences of up to 100% in specific organs. The effective use of the proposed study requires the extension of the dosimetry database, incorporating more CT scanner models and radiopharmaceuticals, and a large dataset of pediatric models that will be simulated for different protocols.
Funding Support, Disclosures, and Conflict of Interest: This study is part of a project that has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska Curie grant agreement No 691203.
Keywords
Monte Carlo, Dosimetry, Nuclear Medicine
Taxonomy
IM- Nuclear Medicine General: Radiation dosimetry & risk
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