MIRD Pamphlet No. 27: MIRDcell V3, a Revised Software Tool for Multicellular Dosimetry and Bioeffect Modeling

Abstract

Radiopharmaceutical therapy is growing rapidly. However, yet to be addressed is the implementation of methods to plan treatments for circulating tumor cells, disseminated tumor cells, and micrometastases. Given the capacity of radiopharmaceuticals to specifically target and kill single cells and multicellular clusters, a quality not available in chemotherapy and external beam radiation therapy, it is important to develop dosimetry and bioeffect modeling tools that can inform radiopharmaceutical design and predict their effect on the microscopic disease. This pamphlet describes a new version of MIRDcell, a software tool that was initially released by the Medical Internal Radiation Dose (MIRD) Committee several years ago. MethodsMIRDcell V3 uses a combination of analytical and Monte Carlo methods to conduct dosimetry and bioeffect modeling for radiolabeled cells within planar colonies and multicellular clusters. Three worked examples are provided to assist users to learn old and new features of MIRDcell, and test its capacity to recapitulate published responses of tumor cell spheroids to radiopharmaceutical treatments. Prominent capabilities of the new version include radially dependent activity distributions, user-imported activity distributions, cold-regions within the cluster, complex bioeffect modeling that accounts for radiation type and subcellular distribution, and a rich table of output data for subsequent analysis. ResultsMIRDcell V3 effectively reproduces experimental responses of multicellular spheroids to uniform and nonuniform distributions of therapeutic radiopharmaceuticals. ConclusionMIRDcell is a versatile software tool that can be used for educational purposes and design of radiopharmaceutical therapies.

Generalized methods for predicting biological response to mixed radiation types and calculating equieffective doses (EQDX)

“…The focus of this study was to identify a computationally efficient and accurate bioeffect model that is suited for predicting responses to mixed radiations and compatible with the MIRDcell software application 20 . After first eliminating competing models, our approach was twofold: (1) modify the ZRM model to overcome some of the limitations of the model in predicting the biologic response to a mixture of a high‐ and low‐LET radiations and (2) generalize the ZRM and mZRM models within the context of the EQD X .…”

“…The NIM implements the LQ model and treats the biological consequences of the absorbed doses, from m radiation types, independently for each radiation type i 20,23 : $$$$\begin{equation}E_{mix}^{NIM} = \ \sum_{i = 1}^m \left( {{\alpha _i}{D_i} + {\beta _i}D_i^2} \right),\end{equation}$$$$ $$$$\begin{equation}P_{mix}^{NIM}\left( D \right) = {e^{ - E_{mix}^{ZRM}}},\end{equation}$$$$where P is the survival probability, and $${D_i}$$, $${\alpha _i}$$, and $${\beta _i}$$ are the absorbed dose and LQ parameters for acute irradiation with radiation type i .…”

“…In the present work we seek to identify an analytical and computationally efficient model that can be integrated into our MIRDcell software application 20 to predict the surviving fraction of a large cell population following exposure to mixed radiation fields that arise from one or more radiopharmaceuticals. MIRDcell V3.13, and earlier versions, use a non‐interacting model (NIM) that can overestimate the probability of cell survival.…”

ICRU Report 98, Stochastic Nature of Radiation Interactions: Microdosimetry

“…In addition, calculation of cellular S -coefficients is helpful in the design of RPT because the absorbed doses depend on the subcellular distribution of radionuclides among the cell compartments (Goddu et al , 1994a; 1997). The contributions from radionuclide decays within and outside the target cell, namely the self-dose and cross-dose, respectively, must be considered in the evaluation (Goddu et al , 1994b; Katugampola et al , 2022a). Multicellular dosimetry is also important for organs and tissue with microstructure (Sgouros et al , 2011).…”

A Review on Tumor Control Probability (TCP) and Preclinical Dosimetry in Targeted Radionuclide Therapy (TRT)

“…Later on, a Java-applet MIRDcell was developed to calculate both self and cross dose S-values. Both Goddu and MIRDcell use a spherical geometry for the cells, combined with energy deposition based on the continuously slowing down approximation [ 87 ]. The latter one is a semi-analytical method that neglects the finite range of secondary electrons and does not take into account straggling effects [ 88 ].…”