Iranian Journal of Medical Physics
Mashhad University of Medical Sciences
About: Iranian Journal of Medical Physics is an academic journal. The journal publishes majorly in the area(s): Imaging phantom & Dosimetry. It has an ISSN identifier of 1735-160X. Over the lifetime, 410 publications have been published receiving 1218 citations.
Papers published on a yearly basis
TL;DR: The results indicate that the proposed combinatorial model produces optimum and efficacious parameters in comparison to other parameters and can improve the capability and power of globalizing the artificial neural network.
Abstract: Introduction This study is an effort to diagnose breast cancer by processing the quantitative and qualitative information obtained from medical infrared imaging. The medical infrared imaging is free from any harmful radiation and it is one of the best advantages of the proposed method. By analyzing this information, the best diagnostic parameters among the available parameters are selected and its sensitivity and precision in cancer diagnosis is improved by utilizing genetic algorithm and artificial neural network. Materials and Methods In this research, the necessary information is obtained from thermal imaging of 200 people, and 8 diagnostic parameters are extracted from these images by the research team. Then these 8 parameters are used as input of our proposed combinatorial model which is formed using artificial neural network and genetic algorithm. Results Our results have revealed that comparison of the breast areas; thermal pattern and kurtosis are the most important parameters in breast cancer diagnosis from proposed medical infrared imaging. The proposed combinatorial model with a 50% sensitivity, 75% specificity and, 70% accuracy shows good precision in cancer diagnosis. Conclusion The main goal of this article is to describe the capability of infrared imaging in preliminary diagnosis of breast cancer. This method is beneficial to patients with and without symptoms. The results indicate that the proposed combinatorial model produces optimum and efficacious parameters in comparison to other parameters and can improve the capability and power of globalizing the artificial neural network. This will help physicians in more accurate diagnosis of this type of cancer.
TL;DR: A hierarchical classification method for breast cancer detection is developed by including two Adaptive Boosting classifiers, the first classifier is devoted to separate normal and tumorous cases and the second layer is designed to detect tumor type.
Abstract: Introduction Breast cancer is the second cause of mortality among women. Early detection of it can enhance the chance of survival. Screening systems such as mammography cannot perfectly differentiate between patients and healthy individuals. Computer-aided diagnosis can help physicians make a more accurate diagnosis. Materials and Methods Regarding the importance of separating normal and abnormal cases in screening systems, a hierarchical classification system is defined in this paper. The proposed system is including two Adaptive Boosting (AdaBoost) classifiers, the first classifier separates the candidate images into two groups of normal and abnormal. The second classifier is applied on the abnormal group of the previous stage and divides them into benign and malignant categories. The proposed algorithm is evaluated by applying it on publicly available Mammographic Image Analysis Society (MIAS) dataset. 288 images of the database are used, including 208 normal and 80 abnormal images. 47 images of the abnormal images showed benign lesion and 33 of them had malignant lesion. Results Applying the proposed algorithm on MIAS database indicates its advantage compared to previous methods. A major improvement occurred in the first classification stage. Specificity, sensitivity, and accuracy of the first classifier are obtained as 100%, 95.83%, and 97.91%, respectively. These values are calculated as 75% in the second stage Conclusion A hierarchical classification method for breast cancer detection is developed in this paper. Regarding the importance of separating normal and abnormal cases in screening systems, the first classifier is devoted to separate normal and tumorous cases. Experimental results on available database shown that the performance of this step is adequately high (100% specificity). The second layer is designed to detect tumor type. The accuracy in the second layer is obtained 75%.
TL;DR: It was showed that increasing J/Φ, as a measure of beam directionality, leads to improvement of beam performance and survival of healthy tissues surrounding the tumor, and the proposed system based on D-T neutron source, which is suitable for in-hospital installations, satisfies all in-air parameters.
Abstract: Introduction BNCT is an effective method to destroy brain tumoral cells while sparing the healthy tissues. The recommended flux for epithermal neutrons is 109 n/cm2s, which has the most effectiveness on deep-seated tumors. In this paper, it is indicated that using D-T neutron source and optimizing of Beam Shaping Assembly (BSA) leads to treating brain tumors in a reasonable time where all IAEA recommended criteria are met. Materials and Methods The proposed BSA based on a D-T neutron generator consists of a neutron multiplier system, moderators, reflector, and collimator. The simulated Snyder head phantom is used to evaluate dose profiles in tissues due to the irradiation of designed beam. Monte Carlo Code, MCNP-4C, was used in order to perform these calculations. Results The neutron beam associated with the designed and optimized BSA has an adequate epithermal flux at the beam port and neutron and gamma contaminations are removed as much as possible. Moreover, it was showed that increasing J/Φ, as a measure of beam directionality, leads to improvement of beam performance and survival of healthy tissues surrounding the tumor. Conclusion According to the simulation results, the proposed system based on D-T neutron source, which is suitable for in-hospital installations, satisfies all in-air parameters. Moreover, depth-dose curves investigate proper performance of designed beam in tissues. The results are comparable with the performances of other facilities.
TL;DR: The application of multilayer shield reduces photon dose remarkably in healthy tissues, Hence, using the shielding material to reduce photoneutron and photon dose which can cause reduction in secondary cancer risk is recommended.
Abstract: Introduction: Due to out-of-field effects in radiation therapy, the determination and reduction of both unwanted photon and photoneutron doses are essential for the reasonable assessment of the risks to healthy tissues. Material and Methods: By the application of a multilayer shield throughout the phantom and using two models for photoneutron and photon sources, doses were estimated in a 15-MV linac in tissues and organs. Different neutron moderators were used, and the best materials, such as polyethylene, polystyrene, polyvinyl chloride, paraffin, and water, were reported for shielding purpose. Boron carbide and steel were utilized as neutron and gamma absorbents. Various lengths of the shield in line with phantom stature were also assessed in this study. Results: Except for the target organ, with the shield throughout the phantom, both photoneutron and photon doses approximately reduced by 57-89% and 88-95%, respectively. Extra photoneutron dose in the photon source was also reported due to the shield. Then, unwanted doses, especially photon dose remarkably decreased with increasing the steel thickness. The smaller dimensions of the shield caused also a considerable reduction of the photoneutron and photon doses in the phantom. Conclusion: The application of a multilayer shield reduces the photon dose remarkably in healthy tissues. Therefore, it is recommended to use shielding materials to decrease photoneutron and photon doses, which can cause a reduction in the risk of secondary cancer. Due to the relatively high mass of the shield, it is necessary to design a proper device to maintain and move the structure.
TL;DR: The combination of the sensitizing GNPs with the AS14411 aptamer can be regarded for improved treatment of breast cancer cells especially for the mammosphere MCF-7 cancer cells mimicking cancerous tumors.
Abstract: Introduction: A main choice for cancer treatment is radiotherapy. But, the radiotherapy disadvantage is damages caused by radiation given to normal tissues/organs surrounding cancer. One way to avoid this is via increasing radiosensitization of cancer cells. Gold nanoparticles (GNPs) have shown sensitizing effect on cancer cells by enhancing their absorbed dose. Unlike earlier delivery techniques developed for nanotherapeutics, active targeting can achieve specific effect and higher uptake of GNPs in tumors while leave healthy cells untouched and consequently improve the therapeutic index. To achieve active targeting, GNPs should be equipped with functional ligands which can recognize and adhere to the receptors of cancer cells. Aptamers are small DNA-molecule/RNA-fragments with high specificity and affinity towards target molecules. AS1411 aptamer can specifically bind to over-expressed nucleolin on the membrane of tumor cells including breast cancer. This aptamer is capable to enter cancer cells through specific ligand–receptor interaction. Greater uptake of GNPs by cells may induce increased radiation effects. Cancer stem cells are a small population of cells within a tumor capable for self-renewal and differentiation into various cell types. Materials and Methods: We hypothesized that conjugation of GNPs with AS1411 (AS1411/GNPs) could increase GNPs-mediated radiosensitization in breast cancer cells. We hypothesized that AS1411/GNPs would radiosensitize breast cancer stem/progenitor cells grown to three- dimensional (3D) mammospheres. Cytotoxicity studies of the GNPs and AS1411/GNPs were done on two different cancer cell lines of MCF-7 and MDA-MB-231 with MTT assay. Atomic absorption spectroscopy (AAS) confirmed the cellular uptake of particles. Radiosensitizing effect of GNPs and AS1411/GNPs on MDA-MB 231 and MCF- 7 cells assessed by clonogenic assay. Results: Clonogenic survival data revealed that AS1411/GNPs at 12.5 mg/L results in radiosensitization of breast cancer cells. Mammosphere of MCF-7 was more resistant than their monolayer counterparts. Conclusion: The combination of the sensitizing GNPs with the AS14411 aptamer can be regarded for improved treatment of breast cancer cells especially for the mammosphere MCF-7 cancer cells mimicking cancerous tumors.
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