Abedin Saghafipour, Yavar Rassi, Mohammad Reza Abai, Mohammad Ali Oshaghi, Mohammad Reza Yaghoobi Arshadi, Mehdi Mohebali, Homa Hajaran, Reza Mostafavi,
Volume 15, Issue 6 (November 2012)
Abstract
Background: Cutaneous leishmaniasis is a health problem in many areas of Iran. Cutaneous leishmaniasisis reported mostly in the central county of Qom province, including Ghanavat and Qomrood villages. This study was done to identify parasite species in human and rodents in order to illustrate the epidemiologic picture of the disease and provide an appropriate control program in 2010 Materials and Methods: This cross-sectional study was done on microscopic smears of 45 human samples and rodents samples hunted around Ghanavat and Qomrood villages in the central county of Qom province in 2010.In total,15 human samples and one hunted rodent sample were positive. In this study,the DNA of the parasites were extracted from the slides and analyzed by Leishmania specific premiers using ITS1 PCR-amplification (Internal Transcribed Spacer1). PCR (PolymeraseChain Reaction) products were digested by Haelll enzyme. Results: Overall, 15 human samples and one rodent sample from Merioneslibycus species were evaluated by PCR-RFLP (Restriction Fragment Length Polymorphism). After electrophoresis, it was demonstrated that the parasite was Leishmaniamajor in both human and rodent species. Conclusion: PCR-RFLP technique is an effective method to determine Leishmania parasite species in Geimsa stained slides from human and rodent reservoirs. One of the advantages of this technique is that it is possible to recognize the pathogen species of Leishmania parasite without gene sequencing. Besides, PCR-RFLP technique is a method of quite high sensitivity and specificity which can identify parasite species in addition to the diagnosis of leishmaniasis within 24 hours.
Fatholah Mohaghegh , Mehran Mohseni, Nasrin Robatmili, Mohamad Reza Bayatiani , Fatemeh Seif, Nayyer Sadat Mostafavi,
Volume 21, Issue 6 (12-2018)
Abstract
Background and Aim: Radiation therapy is the destruction of cancer cells that in all patients with breast cancer reduces tumor recurrence, relieves pain in local tumors and metastases. There are different treatment methods around the world such as electron, photon alone or a combination of both types of fields.
Materials and Methods: In this study, photon therapy (PT) and mixed photon-electron therapy (MPET) were used to treat malignancies of the supraclavicular lymph nodes. 30 patients with right-sided breast cancer with local lymph node metastasis were recruited. The ISOgray software was utilized to collect data about treatment planning methods with PT and MPET.
Findings: The maximum and mean delivered doses of radiation to the supraclavicular region were 52.08±1.64, 42.59±0.51 Gy and 54.24±1.64, 43.67±0.43 Gy in the PT and MPET methods, respectively. The mean irradiated volumes of supraclavicular fossa that received 90% of the radiation dose were 59.74±1.94% and 70.26±0.94% in the PT and MPET methods, respectively (p=0.004). The maximum doses delivered to the spine were 14.66±1.9 Gy and 10.22±0.92 Gy and the thyroid were 42.62±3.1 Gy and 37.67±5.02 Gy in the PT and MPET methods, respectively.
Conclusion: The maximum doses delivered to the spine and thyroid significantly diminished by the novel method. Additionally, supraclavicular region received higher maximum and mean doses in the new treatment modality compared to the conventional methods. The new method improved dose coverage for the tumor.
Arman Zamani, Abolghasem Babaei, Nayyer Sadat Mostafavi,
Volume 22, Issue 1 (4-2019)
Abstract
Background and Aim: Diagnosis of leukemia is very difficult, therefore, it is necessary to use image processing techniques. The main objective of this study was to provide a system based on intelligent models that could improve the accuracy of the diagnostic system for acute leukemia.
Materials and Methods: The images produced in this study were extracted from the University Degli Studi Dimilan database and processed in the MATlab 2014a software. In this research, Fuzzy-Cmeans method was used in fragmentation and neural network and support vector machine in classification networks.
Ethical Considerations: In this study, all principles of research ethics were considered.
Findings: Feature data were extracted using the original image transfer to RGB, HSV, Lab and Enhanced RGB spaces. The data obtained from the previous step were entered into the SVM network, then the network separated normal data from abnormal data. The results of comparing the output of the proposed method with different educational methods showed the highest mean of accuracy equal to 95.7%.
Conclusion: The application of the proposed network in this study was that eliminate the weak points of all the networks in addition to presenting the advantages of these network. Combining the networks improved the accuracy of output up to 98% and considerably reduced the time required for calculations.
