Development of a stand-alone precalculated Monte Carlo code to calculate the dose by alpha and beta emitters from the Ra-224 decay chain.

BACKGROUND: Recent developments in alpha and beta emitting radionuclide therapy highlight the importance of developing efficient methods for patient-specific dosimetry. Traditional tabulated methods such as Medical Internal Radiation Dose (MIRD) estimate the dose at the organ level while more recent numerical methods based on Monte Carlo (MC) simulations are able to calculate dose at the voxel level. A precalculated MC (PMC) approach was developed in this work as an alternative to time-consuming fully simulated MC. Once the spatial distribution of alpha and beta emitters is determined using imaging and/or numerical methods, the PMC code can be used to achieve an accurate voxelized 3D distribution of the deposited energy without relying on full MC calculations. PURPOSE: To implement the PMC method to calculate energy deposited by alpha and beta particles emitted from the Ra-224 decay chain. METHODS: The GEANT4 (version 10.7) MC toolkit was used to generate databases of precalculated tracks to be integrated in the PMC code as well as to benchmark its output. In this regard, energy spectra of alpha and beta particles emitted by the Ra-224 decay chain were generated using GAMOS (version 6.2.0) and imported into GEANT4 macro files. Either alpha or beta emitting sources were defined at the center of a homogeneous phantom filled with various materials such as soft tissue, bone, and lung where particles were emitted either mono-directionally (for database generation) or isotropically (for benchmarking). Two heterogeneous phantoms were used to demonstrate PMC code compatibility with boundary crossing events. Each precalculated database was generated step-by-step by storing particle track information from GEANT4 simulations followed by its integration in a PMC code developed in MATLAB. For a user-defined number of histories, one of the tracks in a given database was selected randomly and rotated randomly to reflect an isotropic emission. Afterward, deposited energy was divided between voxels based on step length in each voxel using a ray-tracing approach. The radial distribution of deposited energy was benchmarked against fully simulated MC calculations using GEANT4. The effect of the GEANT4 parameter StepMax on the accuracy and speed of the code was also investigated. RESULTS: In the case of alpha decay, primary alpha particles show the highest contribution (>99%) in deposited energy compared to their secondary particles. In most cases, protons act as the main secondary particles in the deposition of energy. However, for a lung phantom, using a range cutoff parameter of 10 µm on primary alpha particles yields a higher contribution of secondary electrons than protons. Differences between deposited energy calculated by PMC and fully simulated MC are within 2% for all alpha and beta emitters in homogeneous and heterogeneous phantoms. Additionally, statistical uncertainties are less than 1% for voxels with doses higher than 5% of the maximum dose. Moreover, optimization of the parameter StepMax is necessary to achieve the best tradeoff between code accuracy and speed. CONCLUSIONS: The PMC code shows good performance for dose calculations deposited by alpha and beta emitters. As a stand-alone algorithm, it is suitable to be integrated into clinical treatment planning systems.

Comparison of PRIMO Monte Carlo code and Eclipse treatment planning system in calculation of dosimetric parameters in brain cancer radiotherapy.

Background: It is important to evaluate the dose calculated by treatment planning systems (TPSs) and dose distribution in tumor and organs at risk (OARs). The aim of this study is to compare dose calculated by the PRIMO Monte Carlo code and Eclipse TPS in radiotherapy of brain cancer patients. Materials and methods: PRIMO simulation code was used to simulate a Varian Clinac 600C linac. The simulations were validated for the linac by comparison of the simulation and measured results. In the case of brain cancer patients, the dosimetric parameters obtained by the PRIMO code were compared with those calculated by Eclipse TPS. Gamma function analysis with 3%, 3 mm criteria was utilized to compare the dose distributions. The evaluations were based on the dosimetric parameters for the planning target volume (PTV) and OAR including D min, D mean, and D max, homogeneity index (HI), and conformity index (CI). Results: The gamma function analysis showed a 98% agreement between the results obtained by the PRIMO code and measurement for the percent depth dose (PDD) and dose profiles. The corresponding value in comparing the dosimetric parameters from PRIMO code and Eclipse TPS for the brain patients was 94%, on average. The results of the PRIMO simulation were in good agreement with the measured data and Eclipse TPS calculations. Conclusions: Based on the results of this study, the PRIMO code can be utilized to simulate a medical linac with good accuracy and to evaluate the accuracy of treatment plans for patients with brain cancer.

Physically stimulus-responsive nanoparticles for therapy and diagnosis.

Nanoparticles offer numerous advantages in various fields of science, particularly in medicine. Over recent years, the use of nanoparticles in disease diagnosis and treatments has increased dramatically by the development of stimuli-responsive nano-systems, which can respond to internal or external stimuli. In the last 10 years, many preclinical studies were performed on physically triggered nano-systems to develop and optimize stable, precise, and selective therapeutic or diagnostic agents. In this regard, the systems must meet the requirements of efficacy, toxicity, pharmacokinetics, and safety before clinical investigation. Several undesired aspects need to be addressed to successfully translate these physical stimuli-responsive nano-systems, as biomaterials, into clinical practice. These have to be commonly taken into account when developing physically triggered systems; thus, also applicable for nano-systems based on nanomaterials. This review focuses on physically triggered nano-systems (PTNSs), with diagnostic or therapeutic and theranostic applications. Several types of physically triggered nano-systems based on polymeric micelles and hydrogels, mesoporous silica, and magnets are reviewed and discussed in various aspects.

Diffusion-weighted magnetic resonance imaging at 1.5 T for peripheral zone prostate cancer: the influence of the b-value combination on the diagnostic performance of apparent diffusion coefficient.

Purpose: Diffusion-weighted imaging as a noninvasive functional modality plays a valuable role in the evaluation of prostate cancer. However, there is still no agreement on the number and range of b-values to be used. Therefore, the purpose of this study is to investigate the influence of b-value choice on the diagnostic performance of apparent diffusion coefficient (ADC) values for prostate cancer detection. Material and methods: Fifty-nine consecutive patients with abnormal digital rectal examination findings and raised serum prostate-specific antigen were chosen for magnetic resonance imaging of the prostate before systematic 12-core trans-rectal ultrasound-guided prostate biopsies. ADC values for each ROI were calculated from different b-value combinations (0-1600 s/mm2) by a monoexponential model. Mann-Whitney and the paired-sample t-test were used to compare the mean ADC values for malignant lesions and noncancerous tissues. ROC curve analysis was used to evaluate the diagnostic performance of ADC values in distinguishing prostate cancer from normal-tissue ROIs. Results: The differences between mean ADC values of malignant lesions and contralateral healthy tissues were significant for all the pairs of b-value combinations. The pair of b-values 50 and 1200 provided the highest AUC (0.94), with a sensitivity of 90.2%, a specificity of 92.6%, and an accuracy of 91.2% at an ADC cut-off of 1.23 × 10-3 mm2/s. Conclusions: Our study showed that using a 1.5-Tesla MRI scanner the diagnostic performance of ADC values estimated from the b-value pair 50 and 1200 s/mm2 was highest. However, some other b-value pairs provided statically comparable diagnostic performance.

Investigation of the Scaling Formula Accuracy for Poly-energetic Kernel Calculation in 6 MV Photon Beam.

BACKGROUND: Dose distribution can be obtained from total energy released per unit mass (TERMA) and inhomogeneous energy deposition kernel (EDK) convolution. Since inhomogeneous EDK data is location-dependent, it is calculated by employing the density scaling method rather than Monte Carlo based user code EDKnrc. OBJECTIVE: The present study aimed at investigating EDK scaling formula accuracy in the presence of lung and bone inhomogeneities. MATERIAL AND METHODS: In this theoretical-practical study, six EDKs datasets with lung and bone inhomogeneity in different radii were generated using EDKnrc user code and density scaling formula. Then the scaling method data and corresponding EDKnrc-generated ones were compared to enhance the calculations, and some correction factors for error reduction were also derived to create more consistency between these data. RESULTS: The study has shown that the errors in the theoretical method for calculating inhomogeneous EDKs were significantly reduced based on the attenuation coefficient and ρα rel parameter, with α equal to 1.2 and 0.8 for bone and lung voxels, respectively. CONCLUSION: Although the density scaling method has acceptable accuracy, the error values are significant at the location of lung or bone voxels. By using the mentioned correction factors, the calculation inaccuracy of heterogeneous EDKs can be reduced down to 5%. However, the lung heterogeneity results corrected by the method are not as good as the bone cases.

Applications of Graphene and Graphene Oxide in Smart Drug/Gene Delivery: Is the World Still Flat?

Graphene, a wonder material, has made far-reaching developments in many different fields such as materials science, electronics, condensed physics, quantum physics, energy systems, etc. Since its discovery in 2004, extensive studies have been done for understanding its physical and chemical properties. Owing to its unique characteristics, it has rapidly became a potential candidate for nano-bio researchers to explore its usage in biomedical applications. In the last decade, remarkable efforts have been devoted to investigating the biomedical utilization of graphene and graphene-based materials, especially in smart drug and gene delivery as well as cancer therapy. Inspired by a great number of successful graphene-based materials integrations into the biomedical area, here we summarize the most recent developments made about graphene applications in biomedicine. In this paper, we review the up-to-date advances of graphene-based materials in drug delivery applications, specifically targeted drug/ gene delivery, delivery of antitumor drugs, controlled and stimuli-responsive drug release, photodynamic therapy applications and optical imaging and theranostics, as well as investigating the future trends and succeeding challenges in this topic to provide an outlook for future researches.

A Review on the Biodistribution, Pharmacokinetics and Toxicity of Bismuth-Based Nanomaterials.

Here, bismuth-based nanomaterials (Bi-based NMs) are introduced as promising theranostic agents to enhance image contrast as well as for the therapeutic gain for numerous diseases. However, understanding the interaction of such novel developed nanoparticles (NPs) within a biological environment is a requisite for the translation of any promising agent from the lab bench to the clinic. This interaction delineates the fate of NPs after circulation in the body. In an ideal setting, a nano-based therapeutic agent should be eliminated via the renal clearance pathway, meanwhile it should have specific targeting to a diseased organ to reach an effective dose and also to overcome off-targeting. Due to their clearance pathway, biodistribution patterns and pharmacokinetics (PK), Bi-based NMs have been found to play a determinative role to pass clinical approval and they have been investigated extensively in vivo to date. In this review, we expansively discuss the possible toxicity induced by Bi-based NMs on cells or organs, as well as biodistribution profiles, PK and the clearance pathways in animal models. A low cytotoxicity of Bi-based NMs has been found in vitro and in vivo, and along with their long-term biodistribution and proper renal clearance in animal models, the translation of Bi-based NMs to the clinic as a useful novel theranostic agent is promising to improve numerous medical applications.

Iron oxide/gold nanoparticles-decorated reduced graphene oxide nanohybrid as the thermo-radiotherapy agent.

The main focus of the current study is the fabrication of a multifunctional nanohybrid based on graphene oxide (GO)/iron oxide/gold nanoparticles (NPs) as the combinatorial cancer treatment agent. Gold and iron oxide NPs formed on the GONPs via the in situ synthesis approach. The characterisations showed that gold and iron oxide NPs formed onto the GO. Cell toxicity assessment revealed that the fabricated nanohybrid exhibited negligible toxicity against MCF-7 cells in low doses (<50 ppm). Temperature measurement showed a time and dose-dependent heat elevation under the interaction of the nanohybrid with the radio frequency (RF) wave. The highest temperature was recorded using 200 ppm concentration nanohybrid during 40 min exposure. The combinatorial treatments demonstrated that the maximum cell death (average of 53%) was induced with the combination of the nanohybrid with RF waves and radiotherapy (RT). The mechanistic study using the flow cytometry technique illustrated that early apoptosis was the main underlying cell death. Moreover, the dose enhancement factor of 1.63 and 2.63 were obtained from RT and RF, respectively. To sum up, the authors' findings indicated that the prepared nanohybrid could be considered as multifunctional and combinatorial cancer therapy agents.

Bismuth-Based Nanomaterials: Recent Advances in Tumor Targeting and Synergistic Cancer Therapy Techniques.

Despite all of the efforts in the field of cancer therapy, the heterogeneous properties of tumor cells induce an insufficient therapeutic outcome when treated with conventional monotherapies, necessitating a shift in cancer treatment from monotherapy to combination therapy for complete cancer treatment. Multifunctional bismuth (Bi)-based nanomaterials (NMs) with therapeutic functions hold great promise for the fields of cancer diagnosis and therapy based on their low toxicity, X-ray sensitive capabilities, high atomic number, near-infrared driven semiconductor properties, and low cost. Herein, a comprehensive review of recent advances in various medicinal aspects of Bi-based NMs is presented including: evaluation of in-tumor site accumulation, tumor targeting, and therapeutic performance, as well as the characteristics, benefits, and shortcomings of Bi-based NM-mediated major monotherapies. In addition, the cooperative enhancement mechanisms between two or more of these monotherapies are described in detail to address common challenges in cancer therapy, such as multidrug resistance, hypoxia, and metastasis. Finally, this review opens new insights into the design of multimodal synergistic therapies for potential future clinical applications of Bi-based NMs.

Targeting of cellular redox metabolism for mitigation of radiation injury.

Accidental exposure to ionizing radiation is a serious concern to human life. Studies on the mitigation of side effects following exposure to accidental radiation events are ongoing. Recent studies have shown that radiation can activate several signaling pathways, leading to changes in the metabolism of free radicals including reactive oxygen species (ROS) and nitric oxide (NO). Cellular and molecular mechanisms show that radiation can cause disruption of normal reduction/oxidation (redox) system. Mitochondria malfunction following exposure to radiation and mutations in mitochondria DNA (mtDNA) have a key role in chronic oxidative stress. Furthermore, exposure to radiation leads to infiltration of inflammatory cells such as macrophages, lymphocytes and mast cells, which are important sources of ROS and NO. These cells generate free radicals via upregulation of some pro-oxidant enzymes such as NADPH oxidases, inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2). Epigenetic changes also have a key role in a similar way. Other mediators such as mammalian target of rapamycin (mTOR) and peroxisome proliferator-activated receptor (PPAR), which are involved in the normal metabolism of cells have also been shown to regulate cell death following exposure to radiation. These mechanisms are tissue specific. Inhibition or activation of each of these targets can be suggested for mitigation of radiation injury in a specific tissue. In the current paper, we review the cellular and molecular changes in the metabolism of cells and ROS/NO following exposure to radiation. Furthermore, the possible strategies for mitigation of radiation injury through modulation of cellular metabolism in irradiated organs will be discussed.

TGF-ß in radiotherapy: Mechanisms of tumor resistance and normal tissues injury.

Emerging evidences show that changes in tumor stroma can adapt cancer cells to radiotherapy, thereby leading to a reduction in tumor response to treatment. On the other hand, radiotherapy is associated with severe reactions in normal tissues which limit the amount radiation dose received by tumor. These challenges open a window in radiobiology and radiation oncology to explore mechanisms for improving tumor response and also alleviate side effects of radiotherapy. Transforming growth factor beta (TGF-ß) is a well-known and multitasking cytokine that regulates a wide range of reactions and interactions within tumor and normal tissues. Within tumor microenvironment (TME), TGF-ß is the most potent suppressor of immune system activity against cancer cells. This effect is mediated through stimulation of CD4+ which differentiates to T regulatory cells (Tregs), infiltration of fibroblasts and differentiation into cancer associated fibroblasts (CAFs), and also polarization of macrophages to M2 cells. These changes lead to suppression of cytotoxic CD8 + T lymphocytes (CTLs) and natural killer (NK) cells to kill cancer cells. TGF-ß also plays a key role in the angiogenesis, invasion and DNA damage responses (DDR) in cancer cells. In normal tissues, TGF-ß triggers the expression of a wide range of pro-oxidant and pro-fibrosis genes, leading to fibrosis, genomic instability and some other side effects. These properties of TGF-ß make it a potential target to preserve normal tissues and sensitize tumor via its inhibition. In the current review, we aim to explain the mechanisms of upregulation of TGF-ß and its consequences in both tumor and normal tissues.

Targets for protection and mitigation of radiation injury.

Protection of normal tissues against toxic effects of ionizing radiation is a critical issue in clinical and environmental radiobiology. Investigations in recent decades have suggested potential targets that are involved in the protection against radiation-induced damages to normal tissues and can be proposed for mitigation of radiation injury. Emerging evidences have been shown to be in contrast to an old dogma in radiation biology; a major amount of reactive oxygen species (ROS) production and cell toxicity occur during some hours to years after exposure to ionizing radiation. This can be attributed to upregulation of inflammatory and fibrosis mediators, epigenetic changes and disruption of the normal metabolism of oxygen. In the current review, we explain the cellular and molecular changes following exposure of normal tissues to ionizing radiation. Furthermore, we review potential targets that can be proposed for protection and mitigation of radiation toxicity.

A new approach to automatic fetal brain extraction from MRI using a variational level set method.

BACKGROUND AND PURPOSE: Appropriate images extracted from the MRI of mothers' wombs can be of great help in the medical diagnosis of fetal abnormalities. As maternal tissue may appear in such images, affecting visualization of myelination of the fetal brain, it is not possible to use methods routinely used for extraction of adult brains for fetal brains. The aim of the present study was to use a variational level set approach to extract fetal brain from T2-weighted MR images of the womb. METHODS: Coronal T2-weighted images were acquired using fast MRI protocols (to avoid artifacts). The database includes 105 MR images from eight subjects. After correcting the inhomogeneity of the images, the fetal eyes were located, and from that information, the location of the fetus brain was automatically determined. Then, the variational level set was used for fetus brain extraction. The results were analyzed by a clinical specialist (radiologist) and the similarity (Dice and Jaccard coefficients), sensitivity and specificity were calculated. RESULTS AND CONCLUSIONS: The means of the statistical analysis for the Dice and Jaccard coefficients, sensitivity and specificity, were 99.56%, 96.89%, 95.71%, and 97.96%, respectively. Thus, extraction of fetal brain from MR images was confirmed, both statistically and visually through cross-validation.

Improvement of dose distribution in ocular brachytherapy with 125I seeds 20-mm COMS plaque followed to loading of choroidal tumor by gold nanoparticles.

AIMS AND OBJECTIVES: Brachytherapy using removable ophthalmic plaques loaded with suitable small sealed radioactive seeds adjacent to the ocular's tumor has been widely used as an effective treatment. The aim of this study was to investigate the dose distribution in a modeled eyeball followed to loading of an ocular melanoma tumor with different concentrations of gold nanoparticles (GNPs) as dose enhancement agent by Monte Carlo (MC) calculations. MATERIALS AND METHODS: The MC code of MCNPX 2.6.0 was used to modeling of COMS standard eye plaque loaded with 24 125I sources (6711 model) located on the sclera of modeled eyeball with detailed structures and materials. A choroidal melanoma tumor was simulated and loaded with different concentrations of spherical gold GNPs (50 nm in diameter). Dose enhancement factors (DEFs) of ocular components were calculated. RESULTS: The dosimetric properties of 125I source (6711 model) and dose distribution of COMS standard eye plaque were calculated successfully as recommended by TG-43U1; AAPM. Loading of tumor with GNPs increased dose to the tumor and decreased dose to the normal tissues; the DEF was increased up to 2.280 and 2.030 for tumor apex, while it was decreased to 0.760 and 0.892 for macula and for gold-tumor mixture and nanolattice distributions, respectively. CONCLUSION: Loading the choroidal tumor volume with GNPs improves the dose distribution by increasing dose to the tumor and decreasing dose to the health components in ocular brachytherapy with 125I seeds 20-mm COMS plaque.

Dosimetric Characteristics of 6 MV Modified Beams by Physical Wedges of a Siemens Linear Accelerator.

Physical wedges still can be used as missing tissue compensators or filters to alter the shape of isodose curves in a target volume to reach an optimal radiotherapy plan without creating a hotspot. The aim of this study was to investigate the dosimetric properties of physical wedges filters such as off-axis photon fluence, photon spectrum, output factor and half value layer. The photon beam quality of a 6 MV Primus Siemens modified by 150 and 450 physical wedges was studied with BEAMnrc Monte Carlo (MC) code. The calculated present depth dose and dose profile curves for open and wedged photon beam were in good agreement with the measurements. Increase of wedge angle increased the beam hardening and this effect was more pronounced at the heal region. Using such an accurate MC model to determine of wedge factors and implementation of it as a calculation algorithm in the future treatment planning systems is recommended.

Determination of Initial Beam Parameters of Varian 2100 CD Linac for Various Therapeutic Electrons Using PRIMO.

The aim of the present research was to establish primary characteristics of electron beams for a Varian 2100C/D linear accelerator with recently developed PRIMO Monte Carlo software and to verify relations between electron energy and dose distribution. To maintain conformity of simulated and measured dose curves within 1%/1mm, mean energy, Full Width at Half Maximum (FWHM) of energy and focal spot FWHM of initial beam were changed iteratively. Mean and most probable energies were extracted from validated phase spaces and compared with related empirical equation results. To explain the importance of correct estimation of primary energy on a clinical case, computed tomography images of a thorax phantom were imported in PRIMO. Dose distributions and dose volume histogram (DVH) curves were compared between validated and artificial cases with overestimated energy. Initial mean energies were obtained of 6.68, 9.73, 13.2 and 16.4 MeV for 6, 9, 12 and 15 nominal energies, respectively. Energy FWHM reduced with increase in energy. Three mm focal spot FWHM for 9 MeV and 4 mm for other energies made proper matches of simulated and measured profiles. In addition, the maximum difference of calculated mean electrons energy at the phantom surface with empirical equation was 2.2 percent. Finally, clear differences in DVH curves of validated and artificial energy were observed as heterogeneity indexes were 0.15 for 7.21 MeV and 0.25 for 6.68 MeV. The Monte Carlo model presented in PRIMO for Varian 2100 CD was precisely validated. IAEA polynomial equations estimated mean energy more accurately than a known linear one. Small displacement of R50 changed DVH curves and homogeneity indexes. PRIMO is a user-friendly software which has suitable capabilities to calculate dose distribution in water phantoms or computerized tomographic volumes accurately.