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

BACKGROUND: Predicting biological responses to mixed radiation types is of considerable importance when combining radiation therapies that use multiple radiation types and delivery regimens. These may include the use of both low- and high-linear energy transfer (LET) radiations. A number of theoretical models have been developed to address this issue. However, model predictions do not consistently match published experimental data for mixed radiation exposures. Furthermore, the models are often computationally intensive. Accordingly, there is a need for efficient analytical models that can predict responses to mixtures of low- and high-LET radiations. Additionally, a general formalism to calculate equieffective dose (EQDX) for mixed radiations is needed. PURPOSE: To develop a computationally efficient analytical model that can predict responses to complex mixtures of low- and high-LET radiations as a function of either absorbed dose or EQDX. METHODS: The Zaider-Rossi model (ZRM) was modified by replacing the geometric mean of the quadratic coefficients in the interaction term with the arithmetic mean. This modified ZRM model (mZRM) was then further generalized to any number of radiation types and its validity was tested against published experimental observations. Comparisons between the predictions of the ZRM and mZRM, and other models, were made using two and three radiation types. In addition, a generalized formalism for calculating EQDX for mixed radiations was developed within the context of mZRM and validated with published experimental results. RESULTS: The predictions of biological responses to mixed-LET radiations calculated with the mZRM are in better agreement with experimental observations than ZRM, especially when high- and low-LET radiations are mixed. In these situations, the ZRM overestimated the surviving fraction. Furthermore, the EQDX calculated with mZRM are in better agreement with experimental observations. CONCLUSION: The mZRM is a computationally efficient model that can be used to predict biological response to mixed radiations that have low- and high-LET characteristics. Importantly, interaction terms are retained in the calculation of EQDX for mixed radiation exposures within the mZRM framework. The mZRM has application in a wide range of radiation therapies, including radiopharmaceutical therapy.

Efficacy of HER2-Targeted Intraperitoneal 225Ac α-Pretargeted Radioimmunotherapy for Small-Volume Ovarian Peritoneal Carcinomatosis.

Epithelial ovarian cancer (EOC) is often asymptomatic and presents clinically in an advanced stage as widespread peritoneal microscopic disease that is generally considered to be surgically incurable. Targeted α-therapy with the α-particle-emitting radionuclide 225Ac (half-life, 9.92 d) is a high-linear-energy-transfer treatment approach effective for small-volume disease and even single cells. Here, we report the use of human epidermal growth factor receptor 2 (HER2) 225Ac-pretargeted radioimmunotherapy (PRIT) to treat a mouse model of human EOC SKOV3 xenografts growing as peritoneal carcinomatosis (PC). Methods: On day 0, 105 SKOV3 cells transduced with a luciferase reporter gene were implanted intraperitoneally in nude mice, and tumor engraftment was verified by bioluminescent imaging (BLI). On day 15, treatment was started using 1 or 2 cycles of 3-step anti-HER2 225Ac-PRIT (37 kBq/cycle as 225Ac-Proteus DOTA), separated by a 1-wk interval. Efficacy and toxicity were monitored for up to 154 d. Results: Untreated PC-tumor-bearing nude mice showed a median survival of 112 d. We used 2 independent measures of response to evaluate the efficacy of 225Ac-PRIT. First, a greater proportion of the treated mice (9/10 1-cycle and 8/10 2-cycle; total, 17/20; 85%) survived long-term compared with controls (9/27, 33%), and significantly prolonged survival was documented (log-rank [Mantel-Cox] P = 0.0042). Second, using BLI, a significant difference in the integrated BLI signal area to 98 d was noted between controls and treated groups (P = 0.0354). Of a total of 8 mice from the 2-cycle treatment group (74 kBq total) that were evaluated by necropsy, kidney radiotoxicity was mild and did not manifest itself clinically (normal serum blood urea nitrogen and creatinine). Dosimetry estimates (relative biological effectiveness-weighted dose, where relative biological effectiveness = 5) per 37 kBq administered for tumors and kidneys were 56.9 and 16.1 Gy, respectively. One-cycle and 2-cycle treatments were equally effective. With immunohistology, mild tubular changes attributable to α-toxicity were observed in both therapeutic groups. Conclusion: Treatment of EOC PC-tumor-bearing mice with anti-HER2 225Ac-PRIT resulted in histologic cures and prolonged survival with minimal toxicity. Targeted α-therapy using the anti-HER2 225Ac-PRIT system is a potential treatment for otherwise incurable EOC.

Predicting response of micrometastases with MIRDcell V3: proof of principle with 225Ac-DOTA encapsulating liposomes that produce different activity distributions in tumor spheroids.

PURPOSE: The spatial distribution of radiopharmaceuticals within multicellular clusters is known to have a significant effect on their biological response. Most therapeutic radiopharmaceuticals distribute nonuniformly in tissues which makes predicting responses of micrometastases challenging. The work presented here analyzes published temporally dependent nonuniform activity distributions within tumor spheroids treated with actinium-225-DOTA encapsulating liposomes (225Ac-liposomes) and uses these data in MIRDcell V3.11 to calculate absorbed dose distributions and predict biological response. The predicted responses are compared with experimental responses. METHODS: Four types of liposomes were prepared having membranes with different combinations of release (R) and adhesion (A) properties. The combinations were R-A-, R-A+, R+A-, and R+A+. These afford different penetrating properties into tissue. The liposomes were loaded with either carboxyfluorescein diacetate succinimidyl ester (CFDA-SE) or 225Ac. MDA-MB-231 spheroids were treated with the CFDA-SE-liposomes, harvested at different times, and the time-integrated CFDA-SE concentration at each radial position within the spheroid was determined. This was translated into mean 225Ac decays/cell versus radial position, uploaded to MIRDcell, and the surviving fraction of cells in spherical multicellular clusters was simulated. The MIRDcell-predicted surviving fractions were compared with experimental fractional-outgrowths of the spheroids following treatment with 225Ac-liposomes. RESULTS: The biological responses of the multicellular clusters treated with 225Ac-liposomes with physicochemical properties R+A+, R-A+, and R-A- were predicted by MIRDcell with statistically significant accuracy. The prediction for R+A- was not predicted accurately. CONCLUSION: In most instances, MIRDcell predicts responses of spheroids treated with 225Ac-liposomes that result in different tissue-penetrating profiles of the delivered radionuclides.

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

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 microscopic disease. This pamphlet describes a new version of MIRDcell, a software tool that was initially released by the MIRD committee several years ago. Methods: Version 3 (V3) of MIRDcell uses a combination of analytic and Monte Carlo methods to conduct dosimetry and bioeffect modeling for radiolabeled cells within planar colonies and multicellular clusters. A worked example is 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. Results: MIRDcell V3 effectively reproduces experimental responses of multicellular spheroids to uniform and nonuniform distributions of therapeutic radiopharmaceuticals. Conclusion: MIRDcell is a versatile software tool that can be used for educational purposes and design of radiopharmaceutical therapies.