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A Review of Organ Dose Calculation Methods and Tools for Patients Undergoing Diagnostic Nuclear Medicine Procedures

  • Received : 2023.02.28
  • Accepted : 2023.03.17
  • Published : 2024.03.31

Abstract

Exponential growth has been observed in nuclear medicine procedures worldwide in the past decades. The considerable increase is attributed to the advance of positron emission tomography and single photon emission computed tomography, as well as the introduction of new radiopharmaceuticals. Although nuclear medicine procedures provide undisputable diagnostic and therapeutic benefits to patients, the substantial increase in radiation exposure to nuclear medicine patients raises concerns about potential adverse health effects and calls for the urgent need to monitor exposure levels. In the current article, model-based internal dosimetry methods were reviewed, focusing on Medical Internal Radiation Dose (MIRD) formalism, biokinetic data, human anatomy models (stylized, voxel, and hybrid computational human phantoms), and energy spectrum data of radionuclides. Key results from many articles on nuclear medicine dosimetry and comparisons of dosimetry quantities based on different types of human anatomy models were summarized. Key characteristics of seven model-based dose calculation tools were tabulated and discussed, including dose quantities, computational human phantoms used for dose calculations, decay data for radionuclides, biokinetic data, and user interface. Lastly, future research needs in nuclear medicine dosimetry were discussed. Model-based internal dosimetry methods were reviewed focusing on MIRD formalism, biokinetic data, human anatomy models, and energy spectrum data of radionuclides. Future research should focus on updating biokinetic data, revising energy transfer quantities for alimentary and gastrointestinal tracts, accounting for body size in nuclear medicine dosimetry, and recalculating dose coefficients based on the latest biokinetic and energy transfer data.

Keywords

Acknowledgement

This research was funded by the intramural research program of the National Institutes of Health, National Cancer Institute, Division of Cancer Epidemiology and Genetics.

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