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Radioactive atoms attached to monoclonal antibodies are used in radioimmunotherapy to treat cancer while limiting radiation to healthy tissues. One limitation of this method is that only one radioactive atom is linked to each antibody and the deposited dose is often insufficient to eradicate solid and radioresistant tumors. In a previous study, simulations with the Monte Carlo N-Particle eXtended code showed that physical doses up to 50 Gy can be delivered inside tumors by replacing the single radionuclide by a radioactive nanoparticle of 5 nm diameter containing hundreds of radioactive atoms. However, tumoral and normal tissues are not equally sensitive to radiation, and previous works did not take account the biological effects such as cellular repair processes or the presence of less radiosensitive cells such as hypoxic cells.The idea is to adapt the linear-quadratic expression to the tumor model and to determine biological effective doses (BEDs) delivered through and around a tumor. This BED is then incorporated into a Poisson formula to determine the shell control probability (SCP) which predicts the cell cluster-killing efficiency at different distances "r" from the center of the tumor. BED and SCP models are used to analyze the advantages of injecting radioactive nanoparticles instead of a single radionuclide per vector in radioimmunotherapy.Calculations of BED and SCP for different distances r from the center of a solid tumor, using the non-small-cell lung cancer as an example, were investigated for 90Y2O3 nanoparticles. With a total activity of about 3.5 and 20 MBq for tumor radii of 0.5 and 1.0 cm, respectively, results show that a very high BED is deposited in the well oxygenated part of the spherical carcinoma.For either small or large solid tumors, BED and SCP calculations highlight the important benefit in replacing the single beta-emitter 90Y attached to each antibody by a 90Y2O3 nanoparticle.

A model based on the linear quadratic model that has been corrected for repopulation, sublethal cell damage repair, and RBE effect has been used to determine the prescription dose for prostate permanent brachytherapy using seeds loaded with a mixture of 103Pd and 125I or a mixture of 103Pd and 131Cs. The prescription dose was determined by comparing the tumor cell survival fractions between the considered biradionuclide seed implant and one monoradionuclide seed implant chosen from 103Pd, 125I, and 131Cs. Prostate edema is included in the model. The influence of the value of the radiobiological parameters and RBE were also investigated. Two mixtures of radionuclides were considered: 103Pd0.75-125I0.25 and 103Pd0.25-131Cs0.75, where the subscripts indicate the fractions of total initial internal activity in the biradionuclide seed. These fractions were selected in order to obtain a dose distribution that lies between that of 103Pd and 125I/131Cs. As expected, the computed prescription dose values are dependent on the model parameters (edema half-life and magnitude, radiobiogical parameters, and RBE). The radionuclide used as a benchmark also has a strong impact on the derived prescribed dose. The large uncertainties in the radiobiological parameters and RBE values produce big errors in the computed prescribed dose. Averaged over the range of all the parameters and depending on the radionuclide used as a benchmark (in subscript), the derived prescription dose for the first mixture (PdI) would be: D(PdI)(Pd)=142(+15)(-16) Gy and D(PdI)(I)=142(+6)(-8) Gy; and D(PdCs)(Pd)=128(+13)(-13) Gy and D(PdCs)(Cs)=115(+6)(-7) Gy for the PdCs mixture. The uncertainties could be reduced if the radiobiological parameters and RBE value were known more accurately. However, as edema characteristics are patient dependent and can be obtained only after the treatment, an unpredictable error is unavoidable.

Radioimmunotherapy uses monoclonal antibodies that are still labeled with only one radioactive atom. The aim of this paper is to assess, by means of MCNPX simulations, the doses delivered around and throughout a solid tumor when the radioactive atom linked to each antibody is replaced by a 5 nm diameter nanoparticle composed of numerous radionuclides. A new model for a spherical vascularized tumor has been developed in which the antibody distributions inside the tumor can be uniform or heterogeneous. It is also possible to simulate a central necrotic core inside the tumor where the concentration of radiolabeled antibodies is assumed to be zero. Dosimetry calculations have been performed for the beta-emitting radionuclide (90)Y2O3. Preliminary results show that the irregularity of vasculature and the presence of a necrotic core have a noticeable influence on the deposited dose profiles. Moreover, with a total activity of 5 and 34 MBq for tumor radii of 0.5 and 1.0 cm, respectively, viable tumor cells can receive doses of up to 50 Gy, even if high nonuniformity of the total activity is observed in the tumor. These simulations still require accurate information about antibody characteristics and necrosis sizes but clearly confirm that the use of monoclonal antibodies conjugated to nanoparticles could lead to a considerable enhancement of treatment efficacy against cancer.

This paper presents a preliminary study on multiple-radionuclide sources for brachytherapy. An adaptation of the AAPM TG-43U1 formalism is proposed in order to derive the dosimetry parameters of multiple-radionuclide sources from mono-radionuclides. The adapted formalism is applied to a bi-radionuclide case with the help of Monte Carlo calculations (MCNPX 2.5.0). InterSource seed loaded with 103Pd and 125I was chosen. This combination promotes a higher dose rate than InterSource125 (loaded with 125I) and deeper tissue penetration than InterSource103 (loaded with 103Pd) while reducing the dose at long distance (beyond 2.5 cm) relative to InterSource125. In conclusion, this work shows the benefits of combining different radionuclides inside the same seed and proposes an adaptation of the AAPM TG-43U1 formalism for the implementation of multiple-radionuclide sources in current treatment planning systems.