A 3D Monte Carlo method for estimation of patient-specific internal organs absorbed dose for 99m Tc-hynic-Tyr 3 -octreotide imaging

Abstract

Single-photon emission computed tomography (SPECT)-based tracers are easily available and more widely used than positron emission tomography (PET)-based tracers, and SPECT imaging still remains the most prevalent nuclear medicine imaging modality worldwide. The aim of this study is to implement an image-based Monte Carlo method for patient-specific three-dimensional (3D) absorbed dose calculation in patients after injection of 99mTc-hydrazinonicotinamide (hynic)-Tyr3-octreotide as a SPECT radiotracer. 99mTc patient-specific S values and the absorbed doses were calculated with GATE code for each source-target organ pair in four patients who were imaged for suspected neuroendocrine tumors. Each patient underwent multiple whole-body planar scans as well as SPECT imaging over a period of 1-24 h after intravenous injection of 99mhynic-Tyr3-octreotide. The patient-specific S values calculated by GATE Monte Carlo code and the corresponding S values obtained by MIRDOSE program differed within 4.3% on an average for self-irradiation, and differed within 69.6% on an average for cross-irradiation. However, the agreement between total organ doses calculated by GATE code and MIRDOSE program for all patients was reasonably well (percentage difference was about 4.6% on an average). Normal and tumor absorbed doses calculated with GATE were slightly higher than those calculated with MIRDOSE program. The average ratio of GATE absorbed doses to MIRDOSE was 1.07 ± 0.11 (ranging from 0.94 to 1.36). According to the results, it is proposed that when cross-organ irradiation is dominant, a comprehensive approach such as GATE Monte Carlo dosimetry be used since it provides more reliable dosimetric results.

Specific absorbed fractions of internal photon and electron emitters in a human voxel-based phantom: A monte carlo study

“…The assessment of plotted curves in Figure 3 also confirmed that the organs geometry (such as size and shape), density and the interorgan distance have the significant influence on the photon cross-irradiation SAF values. [ 14 15 ]…”

Estimating the Absorbed Dose of Organs in Pediatric Imaging of 99mTc-DTPA Radiopharmaceutical using MIRDOSE Software

“…Then, the 2 dimensional areas drawn were matched and applied manually to all image series of the whole body to obtain the count pertaining to each organ. The correction related to scattering was made using the TEW method [17] and background correction was used through drawing the areas surrounding each organ and subtracting it from the count relating to that organ [6]. After background and scatter correction, the corrected counts were done based on time.…”

“…Dose distribution varies according to the choice of radiopharmaceutical and radiation specifications. Therefore, examining internal dosimetry for each patient is the great importance of this method [6].…”

Prediction of Absorbed Dose to Normal Organs with Endocrine Tumors for I-131 by use of 99mTC Single Photon Emission Computed Tomography/Computed Tomography and Geant4 Application for Tomographic Emission Simulation

“…The development of hybrid imaging technologies, such as PET/CT and SPECT/CT, increased the capability of performing patient-specific dosimetry diagnosis and therapy using radionuclides by providing spatial and temporal distribution of activity with anatomical information. [ 18 19 20 ] Furthermore, in base Monte Carlo methods, it is now possible to consider the precise geometry of the source and target organs, as well as the heterogeneities of tissues within the body for each patient, with the help of scintigraphy and anatomical images. [ 21 ] On the other hand, the patient-specific dosimetry obtained from the images of the patients, along with Monte Carlo calculations, is not only useful for optimizing the prescribed activities and increasing therapeutic efficiency but also they could also be employed for creating the minimum-effective dose and determining the dose-response relationship as a basis for predicting clinical results.…”