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Validation of the SIMIND simulation code using the myocardial phantom HL.

Yoshiaki Yasumoto1, Hiromitsu Daisaki2, Mitsuru Sato2

  • 1Central Radiology Department, Saitama City Hospital, Saitama City, Japan.

Biomedical Physics & Engineering Express
|November 22, 2024
PubMed
Summary
This summary is machine-generated.

Monte Carlo simulation codes simulating medical imaging nuclear detectors (SIMIND) can be an alternative for nuclear medicine experiments. SIMIND showed favorable accuracy (<10% error) with a cardiac phantom, though some areas require caution.

Keywords:
Monte Carlo simulationSIMINDmyocardial phantom HLvalidation

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Area of Science:

  • Nuclear Medicine
  • Medical Imaging Physics
  • Computational Modeling

Background:

  • Monte Carlo simulation codes simulating medical imaging nuclear detectors (SIMIND) are valuable for modeling nuclear medicine experiments.
  • Validation of simulation tools against experimental data is crucial for their reliable application.

Purpose of the Study:

  • To evaluate SIMIND's usability as an alternative to physical experiments in nuclear medicine.
  • To compare SIMIND simulation data with experimental data using a cardiac phantom (HL).

Main Methods:

  • A cardiac phantom (HL) simulating myocardial scintigraphy with 123I-MIBG was used for SPECT/CT imaging.
  • SIMIND simulations were conducted under identical conditions to the physical experiment.
  • Regions of interest (ROIs) and polar maps were analyzed to calculate relative errors for accuracy assessment.

Main Results:

  • Overall relative errors were below 10% for the main energy window, indicating favorable simulation accuracy.
  • Higher relative errors (>10%) were observed in the low and high sub-energy windows.
  • Mean values within ROIs yielded the smallest errors, while the cardiac base showed higher errors in polar map evaluation.

Conclusions:

  • SIMIND is a viable alternative for nuclear medicine experiments when using realistic phantoms like the cardiac phantom HL.
  • Accuracy of SIMIND may vary under specific conditions, necessitating careful validation for different experimental setups.