3D absorbed dose calculations based on SPECT: evaluation for 111-In/90-Y therapy using Monte Carlo simulations.

  • Ljungberg M
  • Frey E
  • Sjögreen K
 et al. 
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A general method is presented for patient-specific three-dimensional (3D) absorbed dose calculations based on quantitative SPECT activity measurements. The computational scheme includes a method for registration of the CT study to the SPECT image, and compensation for attenuation, scatter, and collimator-detector response including septal penetration, performed as part of an iterative reconstruction method. From SPECT images, the absorbed dose rate is calculated using an EGS4 Monte Carlo code, which converts the activity distribution to an absorbed dose rate distribution. Evaluation of the accuracy in the activity quantification and the absorbed dose calculation is based on realistic Monte Carlo simulated SPECT data of a voxel-computer phantom and (111)In and (90)Y. Septal penetration was not included in this study. The SPECT-based activity concentrations and absorbed dose distributions are compared to the actual values; the results imply that the corrections for attenuation and scatter yield results of high accuracy. The presented method includes compensation for most parameters deteriorating the quantitative image information. Inaccuracies are, however, introduced by the limited spatial resolution of the SPECT system, which are not fully compensated by the collimator-response correction. The proposed evaluation methodology may be used as a basis for future inter-comparison of different dosimetry calculation schemes.

Author-supplied keywords

  • Humans
  • Indium Radioisotopes
  • Indium Radioisotopes: therapeutic use
  • Monte Carlo Method
  • Neoplasms
  • Neoplasms: radionuclide imaging
  • Neoplasms: radiotherapy
  • Radiotherapy Dosage
  • Tomography, Emission-Computed
  • Tomography, Emission-Computed, Single-Photon
  • Yttrium Radioisotopes
  • Yttrium Radioisotopes: therapeutic use

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  • Michael Ljungberg

  • Eric Frey

  • Katarina Sjögreen

  • Xiaowei Liu

  • Yuni Dewaraja

  • Sven-Erik Strand

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