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Cerenkov luminescence imaging (CLI) is an emerging optical imaging technique, which has been widely investigated for biological imaging. In this study, we proposed to integrate the CLI technique with the radionuclide treatment as a "see-and-treat" approach, and evaluated the performance of the pinhole collimator-based CLI technique. The detection of Cerenkov luminescence during radionuclide therapy was simulated using the Monte Carlo technique for breast cancer treatment as an example. Our results show that with the pinhole collimator-based configuration, the location, size and shape of the tumors can be clearly visualized on the Cerenkov luminescence images of the breast phantom. In addition, the CLI of multiple tumors can reflect the relative density of radioactivity among tumors, indicating that the intensity of Cerenkov luminescence is independent of the size and shape of a tumor. The current study has demonstrated the high-quality performance of the pinhole collimator-based CLI in breast tumor imaging for the "see-and-treat" multi-modality treatment.

Purpose: Accurate modeling of the relative biological effectiveness (RBE) of particle beams requires increased systematic in vitro studies with human cell lines with care towards minimizing uncertainties in biologic assays as well as physical parameters. In this study, we describe a novel high-throughput experimental setup and an optimized parameterization of the Monte Carlo (MC) simulation technique that is universally applicable for accurate determination of RBE of clinical ion beams. Clonogenic cell-survival measurements on a human lung cancer cell line (H460) are presented using proton irradiation., Methods: Experiments were performed at the Heidelberg Ion Therapy Center (HIT) with support from the Deutsches Krebsforschungszentrum (DKFZ) in Heidelberg, Germany using a mono-energetic horizontal proton beam. A custom-made variable range selector was designed for the horizontal beam line using the Geant4 MC toolkit. This unique setup enabled a high-throughput clonogenic assay investigation of multiple, well defined dose and linear energy transfer (LETs) per irradiation for human lung cancer cells (H460) cultured in a 96-well plate. Sensitivity studies based on application of different physics lists in conjunction with different electromagnetic constructors and production threshold values to the MC simulations were undertaken for accurate assessment of the calculated dose and the dose-averaged LET (LET d ). These studies were extended to helium and carbon ion beams., Results: Sensitivity analysis of the MC parameterization revealed substantial dependence of the dose and LET d values on both the choice of physics list and the production threshold values. While the dose and LET d calculations using FTFP_BERT_LIV, FTFP_BERT_EMZ, FTFP_BERT_PEN and QGSP_BIC_EMY physics lists agree well with each other for all three ions, they show large differences when compared to the FTFP_BERT physics list with the default electromagnetic constructor. For carbon ions, the dose corresponding to the largest LET d value is observed to differ by as much as 78% between FTFP_BERT and FTFP_BERT_LIV. Furthermore, between the production threshold of 700 μm and 5 μm, proton dose varies by as much as 19% corresponding to the largest LET d value sampled in the current investigation. Based on the sensitivity studies, the FTFP_BERT physics list with the low energy Livermore electromagnetic constructor and a production threshold of 5 μm was employed for determining accurate dose and LET d . The optimized MC parameterization results in a different LET d dependence of the RBE curve for 10% SF of the H460 cell line irradiated with proton beam when compared with the results from a previous study using the same cell line. When the MC parameters are kept consistent between the studies, the proton RBE results agree well with each other within the experimental uncertainties., Conclusions: A custom high-throughput, high-accuracy experimental design for accurate in vitro cell survival measurements was employed at a horizontal beam line. High sensitivity of the physics-based optimization establishes the importance of accurate MC parameterization and hence the conditioning of the MC system on a case-by-case basis. The proton RBE results from current investigations are observed to agree with a previous measurement made under different experimental conditions. This establishes the consistency of our experimental findings across different experiments and institutions., (© 2017 American Association of Physicists in Medicine.)

Purpose: (3)He ions may hold great potential for clinical therapy because of both their physical and biological properties. In this study, the authors investigated the physical properties, i.e., the depth-dose curves from primary and secondary particles, and the energy distributions of helium ((3)He) ions. A relative biological effectiveness (RBE) model was applied to assess the biological effectiveness on survival of multiple cell lines., Methods: In light of the lack of experimental measurements and cross sections, the authors used Monte Carlo methods to study the energy deposition of (3)He ions. The transport of (3)He ions in water was simulated by using three Monte Carlo codes-FLUKA, GEANT4, and MCNPX-for incident beams with Gaussian energy distributions with average energies of 527 and 699 MeV and a full width at half maximum of 3.3 MeV in both cases. The RBE of each was evaluated by using the repair-misrepair-fixation model. In all of the simulations with each of the three Monte Carlo codes, the same geometry and primary beam parameters were used., Results: Energy deposition as a function of depth and energy spectra with high resolution was calculated on the central axis of the beam. Secondary proton dose from the primary (3)He beams was predicted quite differently by the three Monte Carlo systems. The predictions differed by as much as a factor of 2. Microdosimetric parameters such as dose mean lineal energy (y(D)), frequency mean lineal energy (y(F)), and frequency mean specific energy (z(F)) were used to characterize the radiation beam quality at four depths of the Bragg curve. Calculated RBE values were close to 1 at the entrance, reached on average 1.8 and 1.6 for prostate and head and neck cancer cell lines at the Bragg peak for both energies, but showed some variations between the different Monte Carlo codes., Conclusions: Although the Monte Carlo codes provided different results in energy deposition and especially in secondary particle production (most of the differences between the three codes were observed close to the Bragg peak, where the energy spectrum broadens), the results in terms of RBE were generally similar.

Purpose: The motivation of this study was to find and eliminate the cause of errors in dose-averaged linear energy transfer (LET) calculations from therapeutic protons in small targets, such as biological cell layers, calculated using the geant 4 Monte Carlo code. Furthermore, the purpose was also to provide a recommendation to select an appropriate LET quantity from geant 4 simulations to correlate with biological effectiveness of therapeutic protons., Methods: The authors developed a particle tracking step based strategy to calculate the average LET quantities (track-averaged LET, LETt and dose-averaged LET, LETd) using geant 4 for different tracking step size limits. A step size limit refers to the maximally allowable tracking step length. The authors investigated how the tracking step size limit influenced the calculated LETt and LETd of protons with six different step limits ranging from 1 to 500 μm in a water phantom irradiated by a 79.7-MeV clinical proton beam. In addition, the authors analyzed the detailed stochastic energy deposition information including fluence spectra and dose spectra of the energy-deposition-per-step of protons. As a reference, the authors also calculated the averaged LET and analyzed the LET spectra combining the Monte Carlo method and the deterministic method. Relative biological effectiveness (RBE) calculations were performed to illustrate the impact of different LET calculation methods on the RBE-weighted dose., Results: Simulation results showed that the step limit effect was small for LETt but significant for LETd. This resulted from differences in the energy-deposition-per-step between the fluence spectra and dose spectra at different depths in the phantom. Using the Monte Carlo particle tracking method in geant 4 can result in incorrect LETd calculation results in the dose plateau region for small step limits. The erroneous LETd results can be attributed to the algorithm to determine fluctuations in energy deposition along the tracking step in geant 4. The incorrect LETd values lead to substantial differences in the calculated RBE., Conclusions: When the geant 4 particle tracking method is used to calculate the average LET values within targets with a small step limit, such as smaller than 500 μm, the authors recommend the use of LETt in the dose plateau region and LETd around the Bragg peak. For a large step limit, i.e., 500 μm, LETd is recommended along the whole Bragg curve. The transition point depends on beam parameters and can be found by determining the location where the gradient of the ratio of LETd and LETt becomes positive.

Coincident counts can be observed in experimental radiation spectroscopy. Accurate quantification of the radiation source requires the detection efficiency of the spectrometer, which is often experimentally determined. However, Monte Carlo analysis can be used to supplement experimental approaches to determine the detection efficiency a priori. The traditional Monte Carlo method overestimates the detection efficiency as a result of omitting coincident counts caused mainly by multiple cascade source particles. In this study, a novel "multi-primary coincident counting" algorithm was developed using the Geant4 Monte Carlo simulation toolkit. A high-purity Germanium detector for ⁶⁰Co gamma-ray spectroscopy problems was accurately modeled to validate the developed algorithm. The simulated pulse height spectrum agreed well qualitatively with the measured spectrum obtained using the high-purity Germanium detector. The developed algorithm can be extended to other applications, with a particular emphasis on challenging radiation fields, such as counting multiple types of coincident radiations released from nuclear fission or used nuclear fuel.

This paper aims to investigate how the spatial distribution of boron in cells and oxygen concentration affect the DNA damage induced by charged particles in boron neutron capture therapy (BNCT) by Monte Carlo simulations, and further to evaluate the relative biological effectiveness (RBE) of DNA double-strand breaks (DSBs) induction. The kinetic energy spectra of α, 7Li particles in BNCT arriving at the nucleus surface were obtained from GEANT4 (Geant4 10.05.p01). The DNA damage caused by BNCT was then evaluated using MCDS (MCDS 3.10A). When α or 7Li particles were distributed in the cytomembrane or cytoplasm, the difference in DNA damage of the same types was less than 0.5%. Taking the 137Cs photons as the reference radiation, when the oxygen concentration varied from 0% to 50%, the RBE of 0.54MeV protons and recoil protons varied from 5 to 2, whereas it decreased from 10 to 3 for α or 7Li particles. The RBE of DSB induction all charged particles in BNCT decreased with the increase of oxygen concentration. This work indicated that the RBE of different radiation particles of BNCT might be affected by many factors, which should be paid attention to in theoretical research or clinical application. [ABSTRACT FROM AUTHOR]

Purpose. Molecular breast imaging (MBI) of 99mTc-sestamibi with dual-headed, pixelated, cadmium–zinc–telluride (CZT) detectors is increasingly used in breast cancer care for screening/detecting lesions, monitoring response to therapy, and predicting risk of cancer. MBI as a truly quantitative tool in these applications, however, is limited due the lack of absolute 99mTc-sestamibi uptake quantification. To help advance the field of quantitative MBI, we have developed a Monte Carlo simulation application of the GE Discovery NM 750b system. Methods. Our simulation consists of a two-step process using the Geant4 toolkit to model the detector and source geometry and to track photon interactions and a MATLAB script to model the charge transport within the pixelated CZT detector. Simulated detector and detector response model parameters were selected to match measured and simulated standard performance characteristics using various 99mTc point-, line-, and film-sources in air. The final model parameters were verified by comparing the count profiles, energy spectra, and region of interest counts between simulated and measured images of a breast phantom with two spherical lesions in 5 cm thick medium of air or water. Results. Final performance characteristics with 99mTc sources in air were: (1) energy resolution: 6.1% measured versus 5.9% simulated photopeak full-width at half-maximum (FWHM), (2) spatial resolution: mean error between measured and simulated FWHM of 0.08 mm across 4.4–14.0 mm FWHM range, and (3) sensitivity: 572 cpm/μCi measured versus 567 cpm/μCi simulated (<1% error). Good agreement was observed in the breast phantom line profiles through the spherical lesions and overall energy spectra, with <5% difference in sphere counts between simulated and measured data. Conclusion. A pixelated CZT charge transport and induction model was successfully implemented and validated to simulate imaging with the GE Discovery NM 750b system. This work will enable investigations improving MBI image quality and developing algorithms for uptake quantification. [ABSTRACT FROM AUTHOR]

Background: Magnetic resonance imaging (MRI)-guided radiotherapy is a promising image-guided cancer radiotherapy method. For MRI-guided radiotherapy, the proper energy of a therapeutic beam is important for beam-designing processes, and the magnetic-induced dose perturbation would be mainly influenced, especially the perturbation surrounding the tissue-air or air-tissue interfaces. Thus, it was necessary to investigate the impact of beam energy from photon, proton, and carbon ion beams on the magnetic-induced dose perturbations.Materials and Methods: Using a phantom of a water-air-water structure, the dose distributions were calculated with or without the presence of a 1.5 T uniform magnetic field through GEANT4. Based on the calculated doses, magnetic-induced dose perturbations were then obtained. For investigating the effects of beam energies on magnetic-induced dose perturbations, low-, middle-, and high-beam energies were adopted for each beam type.Results and Discussion: For photon beams, the dose perturbations were increased as the beam energies increased. At the up water-air interface, the maximum perturbations exceeded 50%. Near the edge of the radiation field, perturbations of 5%-20% were achieved. For proton and carbon ion beams, their Bragg peaks were shifted from original positions, and the shifting distances were increased with the increased beam energies. However, no evident magnetic-induced dose perturbations were noted at the up water-air interface and bottom air-water interface for all the beam energies. To some extent, this study provided references for assessing the effects of beam energies on magnetic-induced dose perturbations, especially the perturbations around the air cavities inside cancer patients.Conclusion: In MRI-guided cancer radiotherapy, the dose perturbation effects for therapeutic beams are relatively obvious, and the beam energies of therapeutic beams have large impacts on the magnetic-induced dose perturbations with the presence of a 1.5 T transverse magnetic field. [ABSTRACT FROM AUTHOR]

The physical properties of particles used in radiation therapy, such as protons, have been well characterized, and their dose distributions are superior to photon-based treatments. However, proton therapy may also have inherent biologic advantages that have not been capitalized on. Unlike photon beams, the linear energy transfer (LET) and hence biologic effectiveness of particle beams varies along the beam path. Selective placement of areas of high effectiveness could enhance tumor cell kill and simultaneously spare normal tissues. However, previous methods for mapping spatial variations in biologic effectiveness are time-consuming and often yield inconsistent results with large uncertainties. Thus the data needed to accurately model relative biological effectiveness to guide novel treatment planning approaches are limited. We used Monte Carlo modeling and high-content automated clonogenic survival assays to spatially map the biologic effectiveness of scanned proton beams with high accuracy and throughput while minimizing biological uncertainties. We found that the relationship between cell kill, dose, and LET, is complex and non-unique. Measured biologic effects were substantially greater than in most previous reports, and non-linear surviving fraction response was observed even for the highest LET values. Extension of this approach could generate data needed to optimize proton therapy plans incorporating variable RBE. [ABSTRACT FROM AUTHOR]

To theoretically explore the feasibility of neutron dose characterized by Cerenkov photons, the relationship between Cerenkov photons and neutron dose in a water phantom was quantified using the Monte Carlo toolkit Geant4. Results showed that the ratio of the neutron dose deposited by secondary electrons above Cerenkov threshold energy to the total neutron dose is approximately a constant for monoenergetic neutrons from 0.01 eV to 100 eV. With the initial neutron beam energy from 0.01 eV to 100 eV, the number of Cerenkov photons has a good correlation with the total neutron dose along the central axis of the water phantom. The changes of neutron energy spectrum and mechanism analysis also explored at different depths. And the ratio of total neutron dose to the intensity of Cerenkov photons is independent of neutron energy for neutrons from 0.01 eV to 100 eV. These findings indicate that Cerenkov radiation also has potential in the application of neutron dose measurement in some specific fields. [ABSTRACT FROM AUTHOR]

Purpose: We introduce a methodology to calculate the microdosimetric quantity dose-mean lineal energy for input into the microdosimetric kinetic model (MKM) to model the relative biological effectiveness (RBE) of proton irradiation experiments.Methods and Materials: The data from 7 individual proton RBE experiments were included in this study. In each experiment, the RBE at several points along the Bragg curve was measured. Monte Carlo simulations to calculate the lineal energy probability density function of 172 different proton energies were carried out with use of Geant4 DNA. We calculated the fluence-weighted lineal energy probability density function (fw(y)), based on the proton energy spectra calculated through Monte Carlo at each experimental depth, calculated the dose-mean lineal energy yD¯ for input into the MKM, and then computed the RBE. The radius of the domain (rd) was varied to reach the best agreement between the MKM-predicted RBE and experimental RBE. A generic RBE model as a function of dose-averaged linear energy transfer (LETD) with 1 fitting parameter was presented and fit to the experimental RBE data as well to facilitate a comparison to the MKM.Results: Both the MKM and LETD-based models modeled the RBE from experiments well. Values for rd were similar to those of other cell lines under proton irradiation that were modeled with the MKM. Analysis of the performance of each model revealed that neither model was clearly superior to the other.Conclusions: Our 3 key accomplishments include the following: (1) We developed a method that uses the proton energy spectra and lineal energy distributions of those protons to calculate dose-mean lineal energy. (2) We demonstrated that our application of the MKM provides theoretical validation of proton irradiation experiments that show that RBE is significantly greater than 1.1. (3) We showed that there is no clear evidence that the MKM is better than LETD-based RBE models. [ABSTRACT FROM AUTHOR]