Generation of Dose-Volume Histograms Using Monte Carlo Simulations on a Multicellular Model in Radionuclide Therapy

Abstract

An accurate calculation of the absorbed dose at the cellular level can lead to the optimization of the administered activity and the best clinical response in radionuclide therapy. This paper describes the implementation of dose-volume histograms (DVHs) for dosimetry at the cellular level in radionuclide therapy. The FOTELP code, based on Monte Carlo simulations of photon and electron transport, was used on a three-dimensional multicellular tumor model, which includes tumor morphometry and cell-labeling parameters. Differential and cumulated DVHs were generated for different radionuclides (Cu-67, I-131, Sm-153, Y-90, and Re-188) and labeled cell densities (10, 20, 40, 80, and 100%). DVHs were generated as a percentage of tumor cells in the function of a relative absorbed dose, defined as a cell-absorbed dose divided by an average tumor-absorbed dose. DVHs for high-energy beta emitters, such as Re-188 and Y- 90, were very close to the average tumor-absorbed dose. For low-energy beta emitters, such as Cu-67 and I-131, spectra showed that many cells absorbed a much lower dose than the average tumor-absorbed dose. Nonhomogeneity of the radionuclide distribution in tumor, presented by labeled cell density, had a greater influence on DVHs for low-energy beta emitters. Radionuclide therapy plans can be optimized using DVHs.

Monte Carlo simulation of irradiation and killing in three-dimensional cell populations with lognormal cellular uptake of radioactivity

“…Multicellular dosimetry is a growing field of study that has recently led to improvements in our capacity to predict the biological effects of non-uniform distributions of radioactivity that are inherent in radiopharmaceutical delivery (Goddu et al 1994, Charlton 2000, Kvinnsland et al 2001, Howell and Bishayee 2002, Malaroda et al 2003, 2005, Neti and Howell 2003, 2004, 2006, Neti and Howell 2007, 2008, Howell and Neti 2005, Spaic et al 2005, Howell et al 2006, Kalogianni et al 2007, Pinto and Howell 2007, Uusijarvi et al 2008, Cai et al 2010). A semi-empirical approach, that considers the mean cellular self-dose ( D self ), the mean cellular cross-dose ( D cross ), and the fraction of cells labeled f , has been used to predict cell killing in multicellular clusters wherein 1%, 10%, or 100% of the cells were labeled with the beta-particle emitter 131 I (Howell and Neti 2005) or the alpha-particle emitter 210 Po (Neti and Howell 2007).…”

Monte Carlo dosimetry of a realistic multicellular model of follicular lymphoma in a context of radioimmunotherapy

“…Thus, mathematical models of heterogeneous radionuclide biodistributions within the tumors have been studied. [10][11][12][13] As could be expected, these models led to absorbed doses significantly less uniform within the tumor compared to homogeneous biodistributions. Therefore, given the impact of both tumor geometry and radionuclide biodistribution, there are clear calls for the development of small-scale dosimetry based on realistic biological data.…”

“…In practice, the targeting of a tumor is not homogeneous, partly due to the heterogeneous distribution of the receptors (i.e., the antigens). Thus, mathematical models of heterogeneous radionuclide biodistributions within the tumors have been studied 10–13 . As could be expected, these models led to absorbed doses significantly less uniform within the tumor compared to homogeneous biodistributions.…”

A model of cellular dosimetry for macroscopic tumors in radiopharmaceutical therapy

“…Modeling of tumor absorbed dose and TCP and theoretical dependencies based on tumor size, uptake distribution and radionuclide have been studied extensively, [1][2][3][4][5][6][7][8][9] though less frequently with any direct link to experimental data. [10][11][12] The 10 11 -10 14 decays in 10 8 -10 11 cells necessary for a fully cellular simulation are beyond the time frame for a reasonable Monte Carlo simulation and would strain the file storage abilities of any cluster.…”

“…Since EUD and TCP are greatly affected by the lowest outliers in the absorbed dose distribution, 2,3 and all follow from Eq. (6), a simple method of approximating an x-fold increase in absorbed dose is to multiply a by the desired size difference and b by the square of that same difference, thus artificially providing a greater range of absorbed dose variability than that provided by the Monte Carlo simulations.…”