Introducing fitting models for estimating age-specific dose and effective dose in paediatric patients undergoing head, chest and abdomen-pelvis imaging protocols: a patient study.

INTRODUCTION: Concerns regarding the adverse consequences of radiation have increased due to the expanded application of computed tomography (CT) in medical practice. Certain studies have indicated that the radiation dosage depends on the anatomical region, the imaging technique employed and patient-specific variables. The aim of this study is to present fitting models for the estimation of age-specific dose estimates (ASDE), in the same direction of size-specific dose estimates, and effective doses based on patient age, gender and the type of CT examination used in paediatric head, chest and abdomen-pelvis imaging. METHODS: A total of 583 paediatric patients were included in the study. Radiometric data were gathered from DICOM files. The patients were categorised into five distinct groups (under 15 years of age), and the effective dose, organ dose and ASDE were computed for the CT examinations involving the head, chest and abdomen-pelvis. Finally, the best fitting models were presented for estimation of ASDE and effective doses based on patient age, gender and the type of examination. RESULTS: The ASDE in head, chest, and abdomen-pelvis CT examinations increases with increasing age. As age increases, the effective dose in head and abdomen-pelvis CT scans decreased. However, for chest scans, the effective dose initially showed a decreasing trend until the first year of life; after that, it increases in correlation with age. CONCLUSIONS: Based on the presented fitting model for the ASDE, these CT scan quantities depend on factors such as patient age and the type of CT examination. For the effective dose, the gender was also included in the fitting model. By utilising the information about the scan type, region and age, it becomes feasible to estimate the ASDE and effective dose using the models provided in this study.

Prediction of chronic kidney disease in abdominal cancers radiation therapy using the functional assays of normal tissue complication probability models.

Aim: The purpose of this study is to predict chronic kidney disease (CKD) in the radiotherapy of abdominal cancers by evaluating clinical and functional assays of normal tissue complication probability (NTCP) models. Materials and Methods: Radiation renal damage was analyzed in 50 patients with abdominal cancers 12 months after radiotherapy through a clinical estimated glomerular filtration rate (eGFR). According to the common terminology criteria for the scoring system of adverse events, Grade 2 CKD (eGFR ≤30-59 ml/min/1.73 m2) was considered as the radiation therapy endpoint. Modeling and parameter estimation of NTCP models were performed for the Lyman-equivalent uniform dose (EUD), the logit-EUD critical volume (CV), the relative seriality, and the mean dose model. Results: The confidence interval of the fitted parameters was 95%. The parameter value of D50 was obtained 22-38 Gy, and the n and s parameters were equivalent to 0.006 -3 and 1, respectively. According to the Akaike's information criterion, the mean dose model predicts radiation-induced CKD more accurately than the other models. Conclusion: Although the renal medulla consists of many nephrons arranged in parallel, each nephron has a seriality architecture as renal functional subunits. Therefore, based on this principle and modeling results in this study, the whole kidney organs may have a serial-parallel combination or a secret architecture.

Deep Learning Approach for Fusion of Magnetic Resonance Imaging-Positron Emission Tomography Image Based on Extract Image Features using Pretrained Network (VGG19).

Background: The fusion of images is an interesting way to display the information of some different images in one image together. In this paper, we present a deep learning network approach for fusion of magnetic resonance imaging (MRI) and positron emission tomography (PET) images. Methods: We fused two MRI and PET images automatically with a pretrained convolutional neural network (CNN, VGG19). First, the PET image was converted from red-green-blue space to hue-saturation-intensity space to save the hue and saturation information. We started with extracting features from images by using a pretrained CNN. Then, we used the weights extracted from two MRI and PET images to construct a fused image. Fused image was constructed with multiplied weights to images. For solving the problem of reduced contrast, we added the constant coefficient of the original image to the final result. Finally, quantitative criteria (entropy, mutual information, discrepancy, and overall performance [OP]) were applied to evaluate the results of fusion. We compared the results of our method with the most widely used methods in the spatial and transform domain. Results: The quantitative measurement values we used were entropy, mutual information, discrepancy, and OP that were 3.0319, 2.3993, 3.8187, and 0.9899, respectively. The final results showed that our method based on quantitative assessments was the best and easiest way to fused images, especially in the spatial domain. Conclusion: It concluded that our method used for MRI-PET image fusion was more accurate.

Generating pseudo-computerized tomography (P-CT) scan images from magnetic resonance imaging (MRI) images using machine learning algorithms based on fuzzy theory for radiotherapy treatment planning.

PURPOSE: The substitution of computerized tomography (CT) with magnetic resonance imaging (MRI) has been investigated for external radiotherapy treatment planning. The present study aims to use pseudo-CT (P-CT) images created by MRI images to calculate the dose distribution for facilitating the treatment planning process. METHODS: In this work, following image segmentation with a fuzzy clustering algorithm, an adaptive neuro-fuzzy algorithm was utilized to design the Hounsfield unit (HU) conversion model based on the features vector of MRI images. The model was generated on the set of extracted features from the gray-level co-occurrence matrices and the gray-level run-length matrices for 14 arbitrarily selected patients with brain malady. The performance of the algorithm was investigated on blind datasets through dose-volume histogram and isodose curve evaluations, using the RayPlan treatment planning system (TPS), along with the gamma analysis and statistical indices. RESULTS: In the proposed approach, the mean absolute error within the range of 45.4 HU was found among the test data. Also, the relative dose difference between the planning target volume region of the CT and the P-CT was 0.5%, and the best gamma pass rate for 3%/3 mm was 97.2%. CONCLUSION: The proposed method provides a satisfactory average error rate for the generation of P-CT data in the different parts of the brain region from a collection of MRI series. Also, dosimetric parameters evaluation shows good agreement between reference CT and related P-CT images.

Comparison of dosimetric characteristics of physical wedge and enhanced dynamic wedge in inhomogeneous medium using Monte Carlo simulations.

BACKGROUND: Widely used physical wedges in clinical radiotherapy lead to beam intensity attenuation as well as the beam hardening effect, which must be considered. Dynamic wedges devised to overcome the physical wedges (PWs) problems result in dosimetry complications due to jaw movement while the beam is on. This study was aimed to investigate the usability of physical wedge data instead of enhanced dynamic wedge due to the enhanced dynamic wedge (EDW) dosimetry measurement hardships of Varian 2100CD in inhomogeneous phantom by Monte Carlo code as a reliable method in radiation dosimetry. MATERIALS AND METHODS: A PW and EDW-equipped-linac head was simulated using BEAMnrc code. DOSXYZnrc was used for three-dimensional dosimetry calculation in the CIRS phantom. RESULTS: Based on the isodose curves, EDW generated a less scattered as well as lower penumbra width compared to the PW. The depth dose variations of PWs and EDWs were more in soft tissue than the lung tissue. Beam profiles of PW and EDW indicated good coincidence in all points, except for the heel area. CONCLUSION: Results demonstrated that it is possible to apply PW data instead of EDW due to the dosimetry and commissioning hardships caused by EDW in inhomogeneous media.

Estimation and evaluation of pseudo-CT images using linear regression models and texture feature extraction from MRI images in the brain region to design external radiotherapy planning.

AIM: The aim of this study is to construct and evaluate Pseudo-CT images (P-CTs) for electron density calculation to facilitate external radiotherapy treatment planning. BACKGROUND: Despite numerous benefits, computed tomography (CT) scan does not provide accurate information on soft tissue contrast, which often makes it difficult to precisely differentiate target tissues from the organs at risk and determine the tumor volume. Therefore, MRI imaging can reduce the variability of results when registering with a CT scan. MATERIALS AND METHODS: In this research, a fuzzy clustering algorithm was used to segment images into different tissues, also linear regression methods were used to design the regression model based on the feature extraction method and the brightness intensity values. The results of the proposed algorithm for dose-volume histogram (DVH), Isodose curves, and gamma analysis were investigated using the RayPlan treatment planning system, and VeriSoft software. Furthermore, various statistical indices such as Mean Absolute Error (MAE), Mean Error (ME), and Structural Similarity Index (SSIM) were calculated. RESULTS: The MAE of a range of 45-55 was found from the proposed methods. The relative difference error between the PTV region of the CT and the Pseudo-CT was 0.5, and the best gamma rate was 95.4% based on the polar coordinate feature and proposed polynomial regression model. CONCLUSION: The proposed method could support the generation of P-CT data for different parts of the brain region from a collection of MRI series with an acceptable average error rate by different evaluation criteria.

Commissioning and quality assurance of Euromechanics add-on multileaf collimator.

In this study, the beam characteristics of a Euromechanics add-on MLC that has been installed on a Varian CLINAC 2100 C/D linear accelerator are presented. This was the first installation of 60-leaf PMLC from Euromechanics Company worldwide and all mechanical and dosimetric parameters were measured before clinical use of this kind of MLC. Mechanical tests were executed for different gantry and collimator angles. Leaf position accuracy and leaf gap reproducibility were checked with four different tests. The leaf transmissions, collimator (Sc), phantom (Sp), total (Sc,p) scatter factors, output of the machine, beam profiles for off-axis ratios, central axis depth dose, flatness, symmetry and penumbra have been measured for different field sizes pre and post MLC installation in 6 and 18 MV-mode. To evaluate the effect of new data on clinical plans, different beam setup configurations conformed with MLC and custom blocks were planned on CT images of thorax a CIRS phantom model 002LFC in the same treatment planning system. Leaf position in picket fence test found to be in range between 4.89-5.02 cm instead of nominal 5 cm, however the results of this test with EPIDs image and PIPSpro software showed the higher deviation rather than the results reported from the tests with EBT3 films. The measured data showed that on average Sc,p and Sc were increased 0.22% (P = 0.86) and 0.34% (P = 0.86) for 6 MV and 0.37% (P = 0.84) and 0.42% (P = 0.88) for 18 MV beams for different field sizes, respectively. Good agreement was observed between the PDD and profile curves pre and post MLC installation that was expected based on no changes in beam energy and geometry of the collimators. Based on the mechanical and dosimetry results which have been achieved from our different standard tests, it was found no significant differences between pre and post MLC installation values. This indicates, installation and using this system is clinically acceptable.

A novel algorithm for PET and MRI fusion based on digital curvelet transform via extracting lesions on both images.

BACKGROUND AND AIM: Merging multimodal images is a useful tool for accurate and efficient diagnosis and analysis in medical applications. The acquired data are a high-quality fused image that contains more information than an individual image. In this paper, we focus on the fusion of MRI gray scale images and PET color images. METHODS: For the fusion of MRI gray scale images and PET color images, we used lesion region extracting based on the digital Curvelet transform (DCT) method. As curvelet transform has a better performance in detecting the edges, regions in each image are perfectly segmented. Curvelet decomposes each image into several low- and high-frequency sub-bands. Then, the entropy of each sub-band is calculated. By comparing the entropies and coefficients of the extracted regions, the best coefficients for the fused image are chosen. The fused image is obtained via inverse Curvelet transform. In order to assess the performance, the proposed method was compared with different fusion algorithms, both visually and statistically. RESULT: The analysis of the results showed that our proposed algorithm has high spectral and spatial resolution. According to the results of the quantitative fusion metrics, this method achieves an entropy value of 6.23, an MI of 1.88, and an SSIM of 0.6779. Comparison of these experiments with experiments of four other common fusion algorithms showed that our method is effective. CONCLUSION: The fusion of MRI and PET images is used to gather the useful information of both source images into one image, which is called the fused image. This study introduces a new fusion algorithm based on the digital Curvelet transform. Experiments show that our method has a high fusion effect.

Methoxyamine Enhances 5-Fluorouracil-Induced Radiosensitization in Colon Cancer Cell Line HT29.

OBJECTIVE: This study intended to observe the effects of methoxyamine (Mx) on cytotoxic effects and DNA damage caused by 5-Fluorouracil (5-FU) in combination with gamma radiation in a human colon cancer cell line, HT29. MATERIALS AND METHODS: In this experimental study, HT29 cells were cultured as a monolayer and treated with different concentrations of 5-FU along with 1 mM Mx for 24 hours. Next, the cells were irradiated with 2 Gy gamma radiation. After the treatments, we assessed for DNA damage, cytotoxicity, and viability by alkaline comet, clonogenic survival, and trypan blue dye exclusion assays. RESULTS: Cytotoxicity and DNA damage increased with increasing 5-FU concentration. The 1 mM Mx concentration had no significant effect on cytotoxicity and DNA damage from 5-FU; however, it increased the cytotoxic and genotoxic effects of different concentrations of 5-FU when used in combination with 2 Gy gamma radiation. CONCLUSION: Mx combined with 5-FU enhanced the radiosensitivity of colon cancer cells.

Dosimetric characteristic of physical wedge versus enhanced dynamic wedge based on Monte Carlo simulations.

AIM OF STUDY: Physical wedges (PWs) are widely used in radiotherapy to obtain tilted isodose curves, but they alter beam quality. Dynamic wedges (DWs) using moving collimator overcome this problem, but measuring their beam data is not simple. The main aim of this study is to obtain all dosimetric parameters of DWs produced by Varian 2100CD with Monte Carlo simulation and compare them to those from PWs. SUBJECTS AND METHODS: To simulate 6 MV photon beams equipped with PW and DW, BEAMnrc code was used. All dosimetric data were obtained with EDR2 films and two-dimensional diode array detector. RESULTS: Good agreement between simulated and measured dosimetric data for PW and DW fields was obtained. Our results showed that percentage depth dose and beam profiles at nonwedged direction for DWs are the same as open fields and can be used to each other. CONCLUSION: From Monte Carlo simulations, it can be concluded that DWs in spite of PW do not have effect on beam quality and are good options for treatment planning system which cannot consider hardening effect produced by PWs. Furthermore, BEAMnrc is a powerful code to acquire all date required by DWs.

Multi-parametric Improvements in the CCD Camera-based EPID for Portal Dosimetry.

Dosimetric verification of radiation treatment has recently been extended by the introduction of electronic portal imaging devices (EPIDs). Detailed dose response specifications of EPID should be addressed prior to any dosimetric application. The present study evaluates improvements of dosimetric properties of the low elbow camera-based EPID Theraview (Cablon Medical, Leusden, The Netherlands) equipped with a cooled charge coupled device (CCD) for portal dosimetry. The dose response, warm-up behavior, stability over long- and short-term scales (throughout a day) were studied. The field size dependency of the EPID response was also investigated and compared with ion chamber measurements under the same conditions. The EPID response without saturation for doses up to 2 Gy was linear for both beam qualities (6 and 15 MV). There was no evident warm-up characteristic. The detector sensitivity showed excellent stability in short term [standard deviation (SD) 0.38%]. In long-term stability (over a period of approximately 3 months), a negligible linear decline of 0.01% per day was observed. It was concluded that the cooled CCD camera-based EPID could be used for portal dosimetry, after accurate corrections for the field size dependency and sensitivity loss.

A Novel Active Contour Model for MRI Brain Segmentation used in Radiotherapy Treatment Planning.

INTRODUCTION: Brain image segmentation is one of the most important clinical tools used in radiology and radiotherapy. But accurate segmentation is a very difficult task because these images mostly contain noise, inhomogeneities, and sometimes aberrations. The purpose of this study was to introduce a novel, locally statistical active contour model (ACM) for magnetic resonance image segmentation in the presence of intense inhomogeneity with the ability to determine the position of contour and energy diagram. METHODS: A Gaussian distribution model with different means and variances was used for inhomogeneity, and a moving window was used to map the original image into another domain in which the intensity distributions of inhomogeneous objects were still Gaussian but were better separated. The means of the Gaussian distributions in the transformed domain can be adaptively estimated by multiplying a bias field by the original signal within the window. Then, a statistical energy function is defined for each local region. Also, to evaluate the performance of our method, experiments were conducted on MR images of the brain for segment tumors or normal tissue as visualization and energy functions. RESULTS: In the proposed method, we were able to determine the size and position of the initial contour and to count iterations to have a better segmentation. The energy function for 20 to 430 iterations was calculated. The energy function was reduced by about 5 and 7% after 70 and 430 iterations, respectively. These results showed that, with increasing iterations, the energy function decreased, but it decreased faster during the early iterations, after which it decreased slowly. Also, this method enables us to stop the segmentation based on the threshold that we define for the energy equation. CONCLUSION: An active contour model based on the energy function is a useful tool for medical image segmentation. The proposed method combined the information about neighboring pixels that belonged to the same class, thereby making it strong to separate the desired objects from the background.

Effects of resveratrol and methoxyamine on the radiosensitivity of iododeoxyuridine in U87MG glioblastoma cell line.

The purpose of this study was to evaluate the combination effect of resveratrol and methoxyamine on radiosensitivity of iododeoxyuridine in spheroid culture of U87MG glioblastoma cell line using colony formation and alkaline comet assays. Spheroids on day-20 with 350 µm diameters were treated with 20 µM resveratrol and/or 6 mM methoxyamine and/or 1 µM iododeoxyuridine for one volume doubling time (67 h), and then irradiated with 2 Gy gamma-radiation ((60)Co) in different groups. After treatment, viability of the cells, colony forming ability and DNA damages were obtained by blue dye exclusion, colony formation and alkaline comet assay, respectively. Our results showed that methoxyamine and resveratrol could significantly reduce colony number and induce the DNA damages of glioblastoma spheroid cells treated with iododeoxyuridine in combination with gamma-rays. Therefore, methoxyamine as base excision repair inhibitor and resveratrol as hypoxia inducible factor 1-alpha inhibitor in combination with iododeoxyuridine as radiosensitizer enhanced the radiosensitization of glioblastoma spheroid cells.

Incidence of Seminoma Cancer in Staffs that Worked in Electromagnetic Waves Station; Three Cases Report.

Physical agents such as ultraviolet or ionizing radiation and repetitive trauma have been related to the causation of cancer in humans. Much less clear is the association between exposure to radiofrequency, such as radar and microwave radiation to the development of cancer. Sporadic case reports and small series suggest that this type of radiation might lead to cancer or contribute to its evolution. The association between radiofrequency and testicular damage and cancer is unproved, but clinical and experimental data are suggestive of such possibility. In this paper we have reported three cases of seminoma in person who worked in the same place that exposed to radio frequency (RF) waves.

Evaluation of The Combined Effects of Hyperthermia, Cobalt-60 Gamma Rays and IUdR on Cultured Glioblastoma Spheroid Cells and Dosimetry Using TLD-100.

OBJECTIVE: In radiation treatment, the irradiation which is effective enough to control the tumors far exceeds normal-tissues tolerance. Thus to avoid such unfavourable outcomes, some methods sensitizing the tumor cells to radiation are used. Iododeoxyuridine (IUdR) is a halogenated thymidine analogue that known to be effective as a radiosensitizer in human cancer therapy. Improving the potential efficacy of radiation therapy after combining to hyperthermia depends on the magnitude of the differential sensitization of the hyperthermic effects or on the differential cytotoxicity of the radiation effects on the tumor cells. In this study, we evaluated the combined effects of IUdR, hyperthermia and gamma rays of (60)Co on human glioblastoma spheroids culture. MATERIALS AND METHODS: In this experimental study,the cultured spheroids with 100µm diameter were treated by 1 µM IUdR, 43°C hyperthermia for an hour and 2 Gy gamma rays, respectively. The DNA damages induced in cells were compared using alkaline comet assay method, and dosimetry was then performed by TLD-100. Comet scores were calculated as mean ± standard error of mean (SEM) using one-way ANOVA. RESULTS: Comparison of DNA damages induced by IUdR and hyperthermia + gamma treatment showed 2.67- and 1.92-fold enhancement, respectively, as compared to the damages induced by radiation alone or radiation combined IUdR. Dosimetry results showed the accurate dose delivered to cells. CONCLUSION: Analysis of the comet tail moments of spheroids showed that the radiation treatments combined with hyperthermia and IUdR caused significant radiosensitization when compared to related results of irradiation alone or of irradiation with IUdR. These results suggest a potential clinical advantage of combining radiation with hyperthermia and indicate effectiveness of hyperthermia treatment in inducing cytotoxicity of tumor cells.

Conjugation of glucosamine with Gd3+-based nanoporous silica using a heterobifunctional ANB-NOS crosslinker for imaging of cancer cells.

BACKGROUND: The aim of this study was to synthesize Gd(3+)-based silica nanoparticles that conjugate easily with glucosamine and to investigate their use as a nanoprobe for detection of human fibrosarcoma cells. METHODS: Based on the structure of the 2-fluoro-2-deoxy-D-glucose molecule ((18)FDG), a new compound consisting of D-glucose (1.1 nm) was conjugated with a Gd(3+)-based mesoporous silica nanoparticle using an N-5-azido-2-nitrobenzoyloxy succinimide (ANB-NOS) crosslinker The contrast agent obtained was characterized using a variety of methods, including Fourier transform infrared spectroscopy, nitrogen physisorption, thermogravimetric analysis, scanning and transmission electron microscopy, and inductively coupled plasma atomic emission spectrometry (ICP-AES). In vitro studies included cell toxicity, apoptosis, tumor necrosis factor-alpha, and hexokinase assays, and in vivo tests consisted of evaluation of blood glucose levels using the contrast compound and tumor imaging. The cellular uptake study was validated using ICP-AES. Magnetic resonance relaxivity of the contrast agent was determined using a 1.5 Tesla scanner. RESULTS: ANB-NOS was found to be the preferred linker for attaching glucosamine onto the surface of the mesoporous silica nanospheres. The r1 relaxivity for the nanoparticles was 17.70 mM(-1)s(-1) per Gd(3+) ion, which is 4.4 times larger than that for Magnevist® (r1 approximately 4 mM(-1)s(-1) per Gd(3+) ion). The compound showed suitable cellular uptake (75.6% ± 2.01%) without any appreciable cytotoxicity. CONCLUSION: Our results suggest that covalently attaching glucosamine molecules to mesoporous silica nanoparticles enables effective targeted delivery of a contrast agent.

Cellular uptake and imaging studies of glycosylated silica nanoprobe (GSN) in human colon adenocarcinoma (HT 29 cell line).

PURPOSE: In recent years, molecular imaging by magnetic resonance imaging (MRI) has gained prominence in the detection of tumor cells. The scope of this study is on molecular imaging and on the cellular uptake study of a glycosylated silica nanoprobe (GSN). METHODS: In this study, intracellular uptake (HT 29 cell line) of GSN was analyzed quantitatively and qualitatively with inductively coupled plasma atomic emission spectroscopy, flow cytometry, and fluorescent microscopy. In vitro and in vivo relaxometry of this nanoparticle was determined using a 3 Tesla MRI; biodistribution of GSN and Magnevist® were measured in different tissues. RESULTS: Results suggest that the cellular uptake of GSN was about 70%. The r1 relaxivity of this nanoparticle in the cells was measured to be 12.9 ± 1.6 mM(-1) s(-1) and on a per lanthanide gadolinium (Gd(3+)) basis. Results also indicate an average cellular uptake of 0.7 ± 0.009 pg Gd(3+) per cell. It should be noted that 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay demonstrated that the cells were effectively labeled without cytotoxicity, and that using MRI for quantitative estimation of delivery and uptake of targeted contrast agents and early detection of human colon cancer cells using targeted contrast agents, is feasible. CONCLUSION: These results showed that GSN provided a critical guideline in selecting these nanoparticles as an appropriate contrast agent for nanomedicine applications.

Commissioning and initial acceptance tests for a commercial convolution dose calculation algorithm for radiotherapy treatment planning in comparison with Monte Carlo simulation and measurement.

In this study the commissioning of a dose calculation algorithm in a currently used treatment planning system was performed and the calculation accuracy of two available methods in the treatment planning system i.e., collapsed cone convolution (CCC) and equivalent tissue air ratio (ETAR) was verified in tissue heterogeneities. For this purpose an inhomogeneous phantom (IMRT thorax phantom) was used and dose curves obtained by the TPS (treatment planning system) were compared with experimental measurements and Monte Carlo (MCNP code) simulation. Dose measurements were performed by using EDR2 radiographic films within the phantom. Dose difference (DD) between experimental results and two calculation methods was obtained. Results indicate maximum difference of 12% in the lung and 3% in the bone tissue of the phantom between two methods and the CCC algorithm shows more accurate depth dose curves in tissue heterogeneities. Simulation results show the accurate dose estimation by MCNP4C in soft tissue region of the phantom and also better results than ETAR method in bone and lung tissues.

Conformal fields in prostate radiotherapy: a comparison between measurement, calculation and simulation.

AIMS: The objective of this study is to evaluate the accuracy of a treatment planning system (TPS) for calculating the dose distribution parameters in conformal fields (CF). Dosimetric parameters of CF's were compared between measurement, Monte Carlo simulation (MCNP4C) and TPS calculation. MATERIALS AND METHODS: Field analyzer water phantom was used for obtaining percentage depth dose (PDD) curves and beam profiles (BP) of different conformal fields. MCNP4C was used to model conformal fields dose specification factors and head of linear accelerator varian model 2100C/D. RESULTS: Results showed that the distance to agreement (DTA) and dose difference (DD) of our findings were well within the acceptance criteria of 3 mm and 3%, respectively. CONCLUSIONS: According to this study it can be revealed that TPS using equivalent tissue air ratio calculation method is still convenient for dose prediction in non small conformal fields normally used in prostate radiotherapy. It was also showed that, since there is a close correlation with Monte Carlo simulation, measurements and TPS, Monte Carlo can be further confirmed for implementation and calculation dose distribution in non standard and complex conformal irradiation field for treatment planning systems.